License cleanup: add SPDX GPL-2.0 license identifier to files with no license
Many source files in the tree are missing licensing information, which
makes it harder for compliance tools to determine the correct license.
By default all files without license information are under the default
license of the kernel, which is GPL version 2.
Update the files which contain no license information with the 'GPL-2.0'
SPDX license identifier. The SPDX identifier is a legally binding
shorthand, which can be used instead of the full boiler plate text.
This patch is based on work done by Thomas Gleixner and Kate Stewart and
Philippe Ombredanne.
How this work was done:
Patches were generated and checked against linux-4.14-rc6 for a subset of
the use cases:
- file had no licensing information it it.
- file was a */uapi/* one with no licensing information in it,
- file was a */uapi/* one with existing licensing information,
Further patches will be generated in subsequent months to fix up cases
where non-standard license headers were used, and references to license
had to be inferred by heuristics based on keywords.
The analysis to determine which SPDX License Identifier to be applied to
a file was done in a spreadsheet of side by side results from of the
output of two independent scanners (ScanCode & Windriver) producing SPDX
tag:value files created by Philippe Ombredanne. Philippe prepared the
base worksheet, and did an initial spot review of a few 1000 files.
The 4.13 kernel was the starting point of the analysis with 60,537 files
assessed. Kate Stewart did a file by file comparison of the scanner
results in the spreadsheet to determine which SPDX license identifier(s)
to be applied to the file. She confirmed any determination that was not
immediately clear with lawyers working with the Linux Foundation.
Criteria used to select files for SPDX license identifier tagging was:
- Files considered eligible had to be source code files.
- Make and config files were included as candidates if they contained >5
lines of source
- File already had some variant of a license header in it (even if <5
lines).
All documentation files were explicitly excluded.
The following heuristics were used to determine which SPDX license
identifiers to apply.
- when both scanners couldn't find any license traces, file was
considered to have no license information in it, and the top level
COPYING file license applied.
For non */uapi/* files that summary was:
SPDX license identifier # files
---------------------------------------------------|-------
GPL-2.0 11139
and resulted in the first patch in this series.
If that file was a */uapi/* path one, it was "GPL-2.0 WITH
Linux-syscall-note" otherwise it was "GPL-2.0". Results of that was:
SPDX license identifier # files
---------------------------------------------------|-------
GPL-2.0 WITH Linux-syscall-note 930
and resulted in the second patch in this series.
- if a file had some form of licensing information in it, and was one
of the */uapi/* ones, it was denoted with the Linux-syscall-note if
any GPL family license was found in the file or had no licensing in
it (per prior point). Results summary:
SPDX license identifier # files
---------------------------------------------------|------
GPL-2.0 WITH Linux-syscall-note 270
GPL-2.0+ WITH Linux-syscall-note 169
((GPL-2.0 WITH Linux-syscall-note) OR BSD-2-Clause) 21
((GPL-2.0 WITH Linux-syscall-note) OR BSD-3-Clause) 17
LGPL-2.1+ WITH Linux-syscall-note 15
GPL-1.0+ WITH Linux-syscall-note 14
((GPL-2.0+ WITH Linux-syscall-note) OR BSD-3-Clause) 5
LGPL-2.0+ WITH Linux-syscall-note 4
LGPL-2.1 WITH Linux-syscall-note 3
((GPL-2.0 WITH Linux-syscall-note) OR MIT) 3
((GPL-2.0 WITH Linux-syscall-note) AND MIT) 1
and that resulted in the third patch in this series.
- when the two scanners agreed on the detected license(s), that became
the concluded license(s).
- when there was disagreement between the two scanners (one detected a
license but the other didn't, or they both detected different
licenses) a manual inspection of the file occurred.
- In most cases a manual inspection of the information in the file
resulted in a clear resolution of the license that should apply (and
which scanner probably needed to revisit its heuristics).
- When it was not immediately clear, the license identifier was
confirmed with lawyers working with the Linux Foundation.
- If there was any question as to the appropriate license identifier,
the file was flagged for further research and to be revisited later
in time.
In total, over 70 hours of logged manual review was done on the
spreadsheet to determine the SPDX license identifiers to apply to the
source files by Kate, Philippe, Thomas and, in some cases, confirmation
by lawyers working with the Linux Foundation.
Kate also obtained a third independent scan of the 4.13 code base from
FOSSology, and compared selected files where the other two scanners
disagreed against that SPDX file, to see if there was new insights. The
Windriver scanner is based on an older version of FOSSology in part, so
they are related.
Thomas did random spot checks in about 500 files from the spreadsheets
for the uapi headers and agreed with SPDX license identifier in the
files he inspected. For the non-uapi files Thomas did random spot checks
in about 15000 files.
In initial set of patches against 4.14-rc6, 3 files were found to have
copy/paste license identifier errors, and have been fixed to reflect the
correct identifier.
Additionally Philippe spent 10 hours this week doing a detailed manual
inspection and review of the 12,461 patched files from the initial patch
version early this week with:
- a full scancode scan run, collecting the matched texts, detected
license ids and scores
- reviewing anything where there was a license detected (about 500+
files) to ensure that the applied SPDX license was correct
- reviewing anything where there was no detection but the patch license
was not GPL-2.0 WITH Linux-syscall-note to ensure that the applied
SPDX license was correct
This produced a worksheet with 20 files needing minor correction. This
worksheet was then exported into 3 different .csv files for the
different types of files to be modified.
These .csv files were then reviewed by Greg. Thomas wrote a script to
parse the csv files and add the proper SPDX tag to the file, in the
format that the file expected. This script was further refined by Greg
based on the output to detect more types of files automatically and to
distinguish between header and source .c files (which need different
comment types.) Finally Greg ran the script using the .csv files to
generate the patches.
Reviewed-by: Kate Stewart <kstewart@linuxfoundation.org>
Reviewed-by: Philippe Ombredanne <pombredanne@nexb.com>
Reviewed-by: Thomas Gleixner <tglx@linutronix.de>
Signed-off-by: Greg Kroah-Hartman <gregkh@linuxfoundation.org>
2017-11-01 17:07:57 +03:00
// SPDX-License-Identifier: GPL-2.0
2005-04-17 02:20:36 +04:00
/*
* linux / mm / swap_state . c
*
* Copyright ( C ) 1991 , 1992 , 1993 , 1994 Linus Torvalds
* Swap reorganised 29.12 .95 , Stephen Tweedie
*
* Rewritten to use page cache , ( C ) 1998 Stephen Tweedie
*/
# include <linux/mm.h>
include cleanup: Update gfp.h and slab.h includes to prepare for breaking implicit slab.h inclusion from percpu.h
percpu.h is included by sched.h and module.h and thus ends up being
included when building most .c files. percpu.h includes slab.h which
in turn includes gfp.h making everything defined by the two files
universally available and complicating inclusion dependencies.
percpu.h -> slab.h dependency is about to be removed. Prepare for
this change by updating users of gfp and slab facilities include those
headers directly instead of assuming availability. As this conversion
needs to touch large number of source files, the following script is
used as the basis of conversion.
http://userweb.kernel.org/~tj/misc/slabh-sweep.py
The script does the followings.
* Scan files for gfp and slab usages and update includes such that
only the necessary includes are there. ie. if only gfp is used,
gfp.h, if slab is used, slab.h.
* When the script inserts a new include, it looks at the include
blocks and try to put the new include such that its order conforms
to its surrounding. It's put in the include block which contains
core kernel includes, in the same order that the rest are ordered -
alphabetical, Christmas tree, rev-Xmas-tree or at the end if there
doesn't seem to be any matching order.
* If the script can't find a place to put a new include (mostly
because the file doesn't have fitting include block), it prints out
an error message indicating which .h file needs to be added to the
file.
The conversion was done in the following steps.
1. The initial automatic conversion of all .c files updated slightly
over 4000 files, deleting around 700 includes and adding ~480 gfp.h
and ~3000 slab.h inclusions. The script emitted errors for ~400
files.
2. Each error was manually checked. Some didn't need the inclusion,
some needed manual addition while adding it to implementation .h or
embedding .c file was more appropriate for others. This step added
inclusions to around 150 files.
3. The script was run again and the output was compared to the edits
from #2 to make sure no file was left behind.
4. Several build tests were done and a couple of problems were fixed.
e.g. lib/decompress_*.c used malloc/free() wrappers around slab
APIs requiring slab.h to be added manually.
5. The script was run on all .h files but without automatically
editing them as sprinkling gfp.h and slab.h inclusions around .h
files could easily lead to inclusion dependency hell. Most gfp.h
inclusion directives were ignored as stuff from gfp.h was usually
wildly available and often used in preprocessor macros. Each
slab.h inclusion directive was examined and added manually as
necessary.
6. percpu.h was updated not to include slab.h.
7. Build test were done on the following configurations and failures
were fixed. CONFIG_GCOV_KERNEL was turned off for all tests (as my
distributed build env didn't work with gcov compiles) and a few
more options had to be turned off depending on archs to make things
build (like ipr on powerpc/64 which failed due to missing writeq).
* x86 and x86_64 UP and SMP allmodconfig and a custom test config.
* powerpc and powerpc64 SMP allmodconfig
* sparc and sparc64 SMP allmodconfig
* ia64 SMP allmodconfig
* s390 SMP allmodconfig
* alpha SMP allmodconfig
* um on x86_64 SMP allmodconfig
8. percpu.h modifications were reverted so that it could be applied as
a separate patch and serve as bisection point.
Given the fact that I had only a couple of failures from tests on step
6, I'm fairly confident about the coverage of this conversion patch.
If there is a breakage, it's likely to be something in one of the arch
headers which should be easily discoverable easily on most builds of
the specific arch.
Signed-off-by: Tejun Heo <tj@kernel.org>
Guess-its-ok-by: Christoph Lameter <cl@linux-foundation.org>
Cc: Ingo Molnar <mingo@redhat.com>
Cc: Lee Schermerhorn <Lee.Schermerhorn@hp.com>
2010-03-24 11:04:11 +03:00
# include <linux/gfp.h>
2005-04-17 02:20:36 +04:00
# include <linux/kernel_stat.h>
# include <linux/swap.h>
2008-02-05 09:28:41 +03:00
# include <linux/swapops.h>
2005-04-17 02:20:36 +04:00
# include <linux/init.h>
# include <linux/pagemap.h>
# include <linux/backing-dev.h>
swap: allow swap readahead to be merged
Swap readahead works fine, but the I/O to disk is almost always done in
page size requests, despite the fact that readahead submits
1<<page-cluster pages at a time.
On older kernels the old per device plugging behavior might have captured
this and merged the requests, but currently all comes down to much more
I/Os than required.
On a single device this might not be an issue, but as soon as a server
runs on shared san resources savin I/Os not only improves swapin
throughput but also provides a lower resource utilization.
With a load running KVM in a lot of memory overcommitment (the hot memory
is 1.5 times the host memory) swapping throughput improves significantly
and the lead feels more responsive as well as achieves more throughput.
In a test setup with 16 swap disks running blocktrace on one of those disks
shows the improved merging:
Prior:
Reads Queued: 560,888, 2,243MiB Writes Queued: 226,242, 904,968KiB
Read Dispatches: 544,701, 2,243MiB Write Dispatches: 159,318, 904,968KiB
Reads Requeued: 0 Writes Requeued: 0
Reads Completed: 544,716, 2,243MiB Writes Completed: 159,321, 904,980KiB
Read Merges: 16,187, 64,748KiB Write Merges: 61,744, 246,976KiB
IO unplugs: 149,614 Timer unplugs: 2,940
With the patch:
Reads Queued: 734,315, 2,937MiB Writes Queued: 300,188, 1,200MiB
Read Dispatches: 214,972, 2,937MiB Write Dispatches: 215,176, 1,200MiB
Reads Requeued: 0 Writes Requeued: 0
Reads Completed: 214,971, 2,937MiB Writes Completed: 215,177, 1,200MiB
Read Merges: 519,343, 2,077MiB Write Merges: 73,325, 293,300KiB
IO unplugs: 337,130 Timer unplugs: 11,184
I got ~10% to ~40% more throughput in my cases and at the same time much
lower cpu consumption when broken down per transferred kilobyte (the
majority of that due to saved interrupts and better cache handling). In a
shared SAN others might get an additional benefit as well, because this
now causes less protocol overhead.
Signed-off-by: Christian Ehrhardt <ehrhardt@linux.vnet.ibm.com>
Acked-by: Rik van Riel <riel@redhat.com>
Acked-by: Jens Axboe <axboe@kernel.dk>
Reviewed-by: Minchan Kim <minchan@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2012-08-01 03:41:44 +04:00
# include <linux/blkdev.h>
2006-01-06 11:10:55 +03:00
# include <linux/pagevec.h>
2006-03-22 11:09:12 +03:00
# include <linux/migrate.h>
mm/swap: split swap cache into 64MB trunks
The patch is to improve the scalability of the swap out/in via using
fine grained locks for the swap cache. In current kernel, one address
space will be used for each swap device. And in the common
configuration, the number of the swap device is very small (one is
typical). This causes the heavy lock contention on the radix tree of
the address space if multiple tasks swap out/in concurrently.
But in fact, there is no dependency between pages in the swap cache. So
that, we can split the one shared address space for each swap device
into several address spaces to reduce the lock contention. In the
patch, the shared address space is split into 64MB trunks. 64MB is
chosen to balance the memory space usage and effect of lock contention
reduction.
The size of struct address_space on x86_64 architecture is 408B, so with
the patch, 6528B more memory will be used for every 1GB swap space on
x86_64 architecture.
One address space is still shared for the swap entries in the same 64M
trunks. To avoid lock contention for the first round of swap space
allocation, the order of the swap clusters in the initial free clusters
list is changed. The swap space distance between the consecutive swap
clusters in the free cluster list is at least 64M. After the first
round of allocation, the swap clusters are expected to be freed
randomly, so the lock contention should be reduced effectively.
Link: http://lkml.kernel.org/r/735bab895e64c930581ffb0a05b661e01da82bc5.1484082593.git.tim.c.chen@linux.intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Signed-off-by: Tim Chen <tim.c.chen@linux.intel.com>
Cc: Aaron Lu <aaron.lu@intel.com>
Cc: Andi Kleen <ak@linux.intel.com>
Cc: Andrea Arcangeli <aarcange@redhat.com>
Cc: Christian Borntraeger <borntraeger@de.ibm.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Cc: Hillf Danton <hillf.zj@alibaba-inc.com>
Cc: Huang Ying <ying.huang@intel.com>
Cc: Hugh Dickins <hughd@google.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Jonathan Corbet <corbet@lwn.net> escreveu:
Cc: Kirill A. Shutemov <kirill.shutemov@linux.intel.com>
Cc: Michal Hocko <mhocko@kernel.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Vladimir Davydov <vdavydov.dev@gmail.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-02-23 02:45:26 +03:00
# include <linux/vmalloc.h>
2017-02-23 02:45:39 +03:00
# include <linux/swap_slots.h>
mm, THP, swap: delay splitting THP during swap out
Patch series "THP swap: Delay splitting THP during swapping out", v11.
This patchset is to optimize the performance of Transparent Huge Page
(THP) swap.
Recently, the performance of the storage devices improved so fast that
we cannot saturate the disk bandwidth with single logical CPU when do
page swap out even on a high-end server machine. Because the
performance of the storage device improved faster than that of single
logical CPU. And it seems that the trend will not change in the near
future. On the other hand, the THP becomes more and more popular
because of increased memory size. So it becomes necessary to optimize
THP swap performance.
The advantages of the THP swap support include:
- Batch the swap operations for the THP to reduce lock
acquiring/releasing, including allocating/freeing the swap space,
adding/deleting to/from the swap cache, and writing/reading the swap
space, etc. This will help improve the performance of the THP swap.
- The THP swap space read/write will be 2M sequential IO. It is
particularly helpful for the swap read, which are usually 4k random
IO. This will improve the performance of the THP swap too.
- It will help the memory fragmentation, especially when the THP is
heavily used by the applications. The 2M continuous pages will be
free up after THP swapping out.
- It will improve the THP utilization on the system with the swap
turned on. Because the speed for khugepaged to collapse the normal
pages into the THP is quite slow. After the THP is split during the
swapping out, it will take quite long time for the normal pages to
collapse back into the THP after being swapped in. The high THP
utilization helps the efficiency of the page based memory management
too.
There are some concerns regarding THP swap in, mainly because possible
enlarged read/write IO size (for swap in/out) may put more overhead on
the storage device. To deal with that, the THP swap in should be turned
on only when necessary. For example, it can be selected via
"always/never/madvise" logic, to be turned on globally, turned off
globally, or turned on only for VMA with MADV_HUGEPAGE, etc.
This patchset is the first step for the THP swap support. The plan is
to delay splitting THP step by step, finally avoid splitting THP during
the THP swapping out and swap out/in the THP as a whole.
As the first step, in this patchset, the splitting huge page is delayed
from almost the first step of swapping out to after allocating the swap
space for the THP and adding the THP into the swap cache. This will
reduce lock acquiring/releasing for the locks used for the swap cache
management.
With the patchset, the swap out throughput improves 15.5% (from about
3.73GB/s to about 4.31GB/s) in the vm-scalability swap-w-seq test case
with 8 processes. The test is done on a Xeon E5 v3 system. The swap
device used is a RAM simulated PMEM (persistent memory) device. To test
the sequential swapping out, the test case creates 8 processes, which
sequentially allocate and write to the anonymous pages until the RAM and
part of the swap device is used up.
This patch (of 5):
In this patch, splitting huge page is delayed from almost the first step
of swapping out to after allocating the swap space for the THP
(Transparent Huge Page) and adding the THP into the swap cache. This
will batch the corresponding operation, thus improve THP swap out
throughput.
This is the first step for the THP swap optimization. The plan is to
delay splitting the THP step by step and avoid splitting the THP
finally.
In this patch, one swap cluster is used to hold the contents of each THP
swapped out. So, the size of the swap cluster is changed to that of the
THP (Transparent Huge Page) on x86_64 architecture (512). For other
architectures which want such THP swap optimization,
ARCH_USES_THP_SWAP_CLUSTER needs to be selected in the Kconfig file for
the architecture. In effect, this will enlarge swap cluster size by 2
times on x86_64. Which may make it harder to find a free cluster when
the swap space becomes fragmented. So that, this may reduce the
continuous swap space allocation and sequential write in theory. The
performance test in 0day shows no regressions caused by this.
In the future of THP swap optimization, some information of the swapped
out THP (such as compound map count) will be recorded in the
swap_cluster_info data structure.
The mem cgroup swap accounting functions are enhanced to support charge
or uncharge a swap cluster backing a THP as a whole.
The swap cluster allocate/free functions are added to allocate/free a
swap cluster for a THP. A fair simple algorithm is used for swap
cluster allocation, that is, only the first swap device in priority list
will be tried to allocate the swap cluster. The function will fail if
the trying is not successful, and the caller will fallback to allocate a
single swap slot instead. This works good enough for normal cases. If
the difference of the number of the free swap clusters among multiple
swap devices is significant, it is possible that some THPs are split
earlier than necessary. For example, this could be caused by big size
difference among multiple swap devices.
The swap cache functions is enhanced to support add/delete THP to/from
the swap cache as a set of (HPAGE_PMD_NR) sub-pages. This may be
enhanced in the future with multi-order radix tree. But because we will
split the THP soon during swapping out, that optimization doesn't make
much sense for this first step.
The THP splitting functions are enhanced to support to split THP in swap
cache during swapping out. The page lock will be held during allocating
the swap cluster, adding the THP into the swap cache and splitting the
THP. So in the code path other than swapping out, if the THP need to be
split, the PageSwapCache(THP) will be always false.
The swap cluster is only available for SSD, so the THP swap optimization
in this patchset has no effect for HDD.
[ying.huang@intel.com: fix two issues in THP optimize patch]
Link: http://lkml.kernel.org/r/87k25ed8zo.fsf@yhuang-dev.intel.com
[hannes@cmpxchg.org: extensive cleanups and simplifications, reduce code size]
Link: http://lkml.kernel.org/r/20170515112522.32457-2-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Signed-off-by: Johannes Weiner <hannes@cmpxchg.org>
Suggested-by: Andrew Morton <akpm@linux-foundation.org> [for config option]
Acked-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> [for changes in huge_memory.c and huge_mm.h]
Cc: Andrea Arcangeli <aarcange@redhat.com>
Cc: Ebru Akagunduz <ebru.akagunduz@gmail.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Michal Hocko <mhocko@kernel.org>
Cc: Tejun Heo <tj@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-07 01:37:18 +03:00
# include <linux/huge_mm.h>
2020-10-14 02:51:17 +03:00
# include <linux/shmem_fs.h>
mm: fix swap cache node allocation mask
Chris Murphy reports that a slightly overcommitted load, testing swap
and zram along with i915, splats and keeps on splatting, when it had
better fail less noisily:
gnome-shell: page allocation failure: order:0,
mode:0x400d0(__GFP_IO|__GFP_FS|__GFP_COMP|__GFP_RECLAIMABLE),
nodemask=(null),cpuset=/,mems_allowed=0
CPU: 2 PID: 1155 Comm: gnome-shell Not tainted 5.7.0-1.fc33.x86_64 #1
Call Trace:
dump_stack+0x64/0x88
warn_alloc.cold+0x75/0xd9
__alloc_pages_slowpath.constprop.0+0xcfa/0xd30
__alloc_pages_nodemask+0x2df/0x320
alloc_slab_page+0x195/0x310
allocate_slab+0x3c5/0x440
___slab_alloc+0x40c/0x5f0
__slab_alloc+0x1c/0x30
kmem_cache_alloc+0x20e/0x220
xas_nomem+0x28/0x70
add_to_swap_cache+0x321/0x400
__read_swap_cache_async+0x105/0x240
swap_cluster_readahead+0x22c/0x2e0
shmem_swapin+0x8e/0xc0
shmem_swapin_page+0x196/0x740
shmem_getpage_gfp+0x3a2/0xa60
shmem_read_mapping_page_gfp+0x32/0x60
shmem_get_pages+0x155/0x5e0 [i915]
__i915_gem_object_get_pages+0x68/0xa0 [i915]
i915_vma_pin+0x3fe/0x6c0 [i915]
eb_add_vma+0x10b/0x2c0 [i915]
i915_gem_do_execbuffer+0x704/0x3430 [i915]
i915_gem_execbuffer2_ioctl+0x1ea/0x3e0 [i915]
drm_ioctl_kernel+0x86/0xd0 [drm]
drm_ioctl+0x206/0x390 [drm]
ksys_ioctl+0x82/0xc0
__x64_sys_ioctl+0x16/0x20
do_syscall_64+0x5b/0xf0
entry_SYSCALL_64_after_hwframe+0x44/0xa9
Reported on 5.7, but it goes back really to 3.1: when
shmem_read_mapping_page_gfp() was implemented for use by i915, and
allowed for __GFP_NORETRY and __GFP_NOWARN flags in most places, but
missed swapin's "& GFP_KERNEL" mask for page tree node allocation in
__read_swap_cache_async() - that was to mask off HIGHUSER_MOVABLE bits
from what page cache uses, but GFP_RECLAIM_MASK is now what's needed.
Link: https://bugzilla.kernel.org/show_bug.cgi?id=208085
Link: http://lkml.kernel.org/r/alpine.LSU.2.11.2006151330070.11064@eggly.anvils
Fixes: 68da9f055755 ("tmpfs: pass gfp to shmem_getpage_gfp")
Signed-off-by: Hugh Dickins <hughd@google.com>
Reviewed-by: Vlastimil Babka <vbabka@suse.cz>
Reviewed-by: Matthew Wilcox (Oracle) <willy@infradead.org>
Reported-by: Chris Murphy <lists@colorremedies.com>
Analyzed-by: Vlastimil Babka <vbabka@suse.cz>
Analyzed-by: Matthew Wilcox <willy@infradead.org>
Tested-by: Chris Murphy <lists@colorremedies.com>
Cc: <stable@vger.kernel.org> [3.1+]
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2020-06-26 06:29:59 +03:00
# include "internal.h"
2005-04-17 02:20:36 +04:00
/*
* swapper_space is a fiction , retained to simplify the path through
2011-03-10 10:52:07 +03:00
* vmscan ' s shrink_page_list .
2005-04-17 02:20:36 +04:00
*/
2006-06-28 15:26:44 +04:00
static const struct address_space_operations swap_aops = {
2005-04-17 02:20:36 +04:00
. writepage = swap_writepage ,
2022-02-09 23:22:10 +03:00
. dirty_folio = swap_dirty_folio ,
2014-10-10 02:27:59 +04:00
# ifdef CONFIG_MIGRATION
2006-02-01 14:05:41 +03:00
. migratepage = migrate_page ,
2014-10-10 02:27:59 +04:00
# endif
2005-04-17 02:20:36 +04:00
} ;
2017-11-16 04:36:06 +03:00
struct address_space * swapper_spaces [ MAX_SWAPFILES ] __read_mostly ;
static unsigned int nr_swapper_spaces [ MAX_SWAPFILES ] __read_mostly ;
2018-04-06 02:25:05 +03:00
static bool enable_vma_readahead __read_mostly = true ;
mm, swap: VMA based swap readahead
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory. And the different tasks in the system may have different access
patterns, which makes the global space locality estimation incorrect.
In this patch, when page fault occurs, the virtual pages near the fault
address will be readahead instead of the swap slots near the fault swap
slot in swap device. This avoid to readahead the unrelated swap slots.
At the same time, the swap readahead is changed to work on per-VMA from
globally. So that the different access patterns of the different VMAs
could be distinguished, and the different readahead policy could be
applied accordingly. The original core readahead detection and scaling
algorithm is reused, because it is an effect algorithm to detect the
space locality.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device:
NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:36 +03:00
# define SWAP_RA_WIN_SHIFT (PAGE_SHIFT / 2)
# define SWAP_RA_HITS_MASK ((1UL << SWAP_RA_WIN_SHIFT) - 1)
# define SWAP_RA_HITS_MAX SWAP_RA_HITS_MASK
# define SWAP_RA_WIN_MASK (~PAGE_MASK & ~SWAP_RA_HITS_MASK)
# define SWAP_RA_HITS(v) ((v) & SWAP_RA_HITS_MASK)
# define SWAP_RA_WIN(v) (((v) & SWAP_RA_WIN_MASK) >> SWAP_RA_WIN_SHIFT)
# define SWAP_RA_ADDR(v) ((v) & PAGE_MASK)
# define SWAP_RA_VAL(addr, win, hits) \
( ( ( addr ) & PAGE_MASK ) | \
( ( ( win ) < < SWAP_RA_WIN_SHIFT ) & SWAP_RA_WIN_MASK ) | \
( ( hits ) & SWAP_RA_HITS_MASK ) )
/* Initial readahead hits is 4 to start up with a small window */
# define GET_SWAP_RA_VAL(vma) \
( atomic_long_read ( & ( vma ) - > swap_readahead_info ) ? : 4 )
2005-04-17 02:20:36 +04:00
2020-08-15 03:31:24 +03:00
# define INC_CACHE_INFO(x) data_race(swap_cache_info.x++)
# define ADD_CACHE_INFO(x, nr) data_race(swap_cache_info.x += (nr))
2005-04-17 02:20:36 +04:00
static struct {
unsigned long add_total ;
unsigned long del_total ;
unsigned long find_success ;
unsigned long find_total ;
} swap_cache_info ;
swap: add a simple detector for inappropriate swapin readahead
This is a patch to improve swap readahead algorithm. It's from Hugh and
I slightly changed it.
Hugh's original changelog:
swapin readahead does a blind readahead, whether or not the swapin is
sequential. This may be ok on harddisk, because large reads have
relatively small costs, and if the readahead pages are unneeded they can
be reclaimed easily - though, what if their allocation forced reclaim of
useful pages? But on SSD devices large reads are more expensive than
small ones: if the readahead pages are unneeded, reading them in caused
significant overhead.
This patch adds very simplistic random read detection. Stealing the
PageReadahead technique from Konstantin Khlebnikov's patch, avoiding the
vma/anon_vma sophistications of Shaohua Li's patch, swapin_nr_pages()
simply looks at readahead's current success rate, and narrows or widens
its readahead window accordingly. There is little science to its
heuristic: it's about as stupid as can be whilst remaining effective.
The table below shows elapsed times (in centiseconds) when running a
single repetitive swapping load across a 1000MB mapping in 900MB ram
with 1GB swap (the harddisk tests had taken painfully too long when I
used mem=500M, but SSD shows similar results for that).
Vanilla is the 3.6-rc7 kernel on which I started; Shaohua denotes his
Sep 3 patch in mmotm and linux-next; HughOld denotes my Oct 1 patch
which Shaohua showed to be defective; HughNew this Nov 14 patch, with
page_cluster as usual at default of 3 (8-page reads); HughPC4 this same
patch with page_cluster 4 (16-page reads); HughPC0 with page_cluster 0
(1-page reads: no readahead).
HDD for swapping to harddisk, SSD for swapping to VertexII SSD. Seq for
sequential access to the mapping, cycling five times around; Rand for
the same number of random touches. Anon for a MAP_PRIVATE anon mapping;
Shmem for a MAP_SHARED anon mapping, equivalent to tmpfs.
One weakness of Shaohua's vma/anon_vma approach was that it did not
optimize Shmem: seen below. Konstantin's approach was perhaps mistuned,
50% slower on Seq: did not compete and is not shown below.
HDD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0
Seq Anon 73921 76210 75611 76904 78191 121542
Seq Shmem 73601 73176 73855 72947 74543 118322
Rand Anon 895392 831243 871569 845197 846496 841680
Rand Shmem 1058375 1053486 827935 764955 764376 756489
SSD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0
Seq Anon 24634 24198 24673 25107 21614 70018
Seq Shmem 24959 24932 25052 25703 22030 69678
Rand Anon 43014 26146 28075 25989 26935 25901
Rand Shmem 45349 45215 28249 24268 24138 24332
These tests are, of course, two extremes of a very simple case: under
heavier mixed loads I've not yet observed any consistent improvement or
degradation, and wider testing would be welcome.
Shaohua Li:
Test shows Vanilla is slightly better in sequential workload than Hugh's
patch. I observed with Hugh's patch sometimes the readahead size is
shrinked too fast (from 8 to 1 immediately) in sequential workload if
there is no hit. And in such case, continuing doing readahead is good
actually.
I don't prepare a sophisticated algorithm for the sequential workload
because so far we can't guarantee sequential accessed pages are swap out
sequentially. So I slightly change Hugh's heuristic - don't shrink
readahead size too fast.
Here is my test result (unit second, 3 runs average):
Vanilla Hugh New
Seq 356 370 360
Random 4525 2447 2444
Attached graph is the swapin/swapout throughput I collected with 'vmstat
2'. The first part is running a random workload (till around 1200 of
the x-axis) and the second part is running a sequential workload.
swapin and swapout throughput are almost identical in steady state in
both workloads. These are expected behavior. while in Vanilla, swapin
is much bigger than swapout especially in random workload (because wrong
readahead).
Original patches by: Shaohua Li and Konstantin Khlebnikov.
[fengguang.wu@intel.com: swapin_nr_pages() can be static]
Signed-off-by: Hugh Dickins <hughd@google.com>
Signed-off-by: Shaohua Li <shli@fusionio.com>
Signed-off-by: Fengguang Wu <fengguang.wu@intel.com>
Cc: Rik van Riel <riel@redhat.com>
Cc: Wu Fengguang <fengguang.wu@intel.com>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Konstantin Khlebnikov <khlebnikov@openvz.org>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2014-02-07 00:04:21 +04:00
static atomic_t swapin_readahead_hits = ATOMIC_INIT ( 4 ) ;
2005-04-17 02:20:36 +04:00
void show_swap_cache_info ( void )
{
2013-02-23 04:34:37 +04:00
printk ( " %lu pages in swap cache \n " , total_swapcache_pages ( ) ) ;
2008-07-26 06:46:01 +04:00
printk ( " Swap cache stats: add %lu, delete %lu, find %lu/%lu \n " ,
2005-04-17 02:20:36 +04:00
swap_cache_info . add_total , swap_cache_info . del_total ,
2008-02-05 09:28:49 +03:00
swap_cache_info . find_success , swap_cache_info . find_total ) ;
swap: add per-partition lock for swapfile
swap_lock is heavily contended when I test swap to 3 fast SSD (even
slightly slower than swap to 2 such SSD). The main contention comes
from swap_info_get(). This patch tries to fix the gap with adding a new
per-partition lock.
Global data like nr_swapfiles, total_swap_pages, least_priority and
swap_list are still protected by swap_lock.
nr_swap_pages is an atomic now, it can be changed without swap_lock. In
theory, it's possible get_swap_page() finds no swap pages but actually
there are free swap pages. But sounds not a big problem.
Accessing partition specific data (like scan_swap_map and so on) is only
protected by swap_info_struct.lock.
Changing swap_info_struct.flags need hold swap_lock and
swap_info_struct.lock, because scan_scan_map() will check it. read the
flags is ok with either the locks hold.
If both swap_lock and swap_info_struct.lock must be hold, we always hold
the former first to avoid deadlock.
swap_entry_free() can change swap_list. To delete that code, we add a
new highest_priority_index. Whenever get_swap_page() is called, we
check it. If it's valid, we use it.
It's a pity get_swap_page() still holds swap_lock(). But in practice,
swap_lock() isn't heavily contended in my test with this patch (or I can
say there are other much more heavier bottlenecks like TLB flush). And
BTW, looks get_swap_page() doesn't really need the lock. We never free
swap_info[] and we check SWAP_WRITEOK flag. The only risk without the
lock is we could swapout to some low priority swap, but we can quickly
recover after several rounds of swap, so sounds not a big deal to me.
But I'd prefer to fix this if it's a real problem.
"swap: make each swap partition have one address_space" improved the
swapout speed from 1.7G/s to 2G/s. This patch further improves the
speed to 2.3G/s, so around 15% improvement. It's a multi-process test,
so TLB flush isn't the biggest bottleneck before the patches.
[arnd@arndb.de: fix it for nommu]
[hughd@google.com: add missing unlock]
[minchan@kernel.org: get rid of lockdep whinge on sys_swapon]
Signed-off-by: Shaohua Li <shli@fusionio.com>
Cc: Hugh Dickins <hughd@google.com>
Cc: Rik van Riel <riel@redhat.com>
Cc: Minchan Kim <minchan.kim@gmail.com>
Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org>
Cc: Seth Jennings <sjenning@linux.vnet.ibm.com>
Cc: Konrad Rzeszutek Wilk <konrad.wilk@oracle.com>
Cc: Xiao Guangrong <xiaoguangrong@linux.vnet.ibm.com>
Cc: Dan Magenheimer <dan.magenheimer@oracle.com>
Cc: Stephen Rothwell <sfr@canb.auug.org.au>
Signed-off-by: Arnd Bergmann <arnd@arndb.de>
Signed-off-by: Hugh Dickins <hughd@google.com>
Signed-off-by: Minchan Kim <minchan@kernel.org>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2013-02-23 04:34:38 +04:00
printk ( " Free swap = %ldkB \n " ,
get_nr_swap_pages ( ) < < ( PAGE_SHIFT - 10 ) ) ;
2005-04-17 02:20:36 +04:00
printk ( " Total swap = %lukB \n " , total_swap_pages < < ( PAGE_SHIFT - 10 ) ) ;
}
2020-08-12 04:30:50 +03:00
void * get_shadow_from_swap_cache ( swp_entry_t entry )
{
struct address_space * address_space = swap_address_space ( entry ) ;
pgoff_t idx = swp_offset ( entry ) ;
struct page * page ;
2021-02-26 04:15:33 +03:00
page = xa_load ( & address_space - > i_pages , idx ) ;
2020-08-12 04:30:50 +03:00
if ( xa_is_value ( page ) )
return page ;
return NULL ;
}
2005-04-17 02:20:36 +04:00
/*
2017-11-27 23:46:54 +03:00
* add_to_swap_cache resembles add_to_page_cache_locked on swapper_space ,
2005-04-17 02:20:36 +04:00
* but sets SwapCache flag and private instead of mapping and index .
*/
2020-08-12 04:30:47 +03:00
int add_to_swap_cache ( struct page * page , swp_entry_t entry ,
gfp_t gfp , void * * shadowp )
2005-04-17 02:20:36 +04:00
{
2017-11-27 23:46:54 +03:00
struct address_space * address_space = swap_address_space ( entry ) ;
mm, THP, swap: delay splitting THP during swap out
Patch series "THP swap: Delay splitting THP during swapping out", v11.
This patchset is to optimize the performance of Transparent Huge Page
(THP) swap.
Recently, the performance of the storage devices improved so fast that
we cannot saturate the disk bandwidth with single logical CPU when do
page swap out even on a high-end server machine. Because the
performance of the storage device improved faster than that of single
logical CPU. And it seems that the trend will not change in the near
future. On the other hand, the THP becomes more and more popular
because of increased memory size. So it becomes necessary to optimize
THP swap performance.
The advantages of the THP swap support include:
- Batch the swap operations for the THP to reduce lock
acquiring/releasing, including allocating/freeing the swap space,
adding/deleting to/from the swap cache, and writing/reading the swap
space, etc. This will help improve the performance of the THP swap.
- The THP swap space read/write will be 2M sequential IO. It is
particularly helpful for the swap read, which are usually 4k random
IO. This will improve the performance of the THP swap too.
- It will help the memory fragmentation, especially when the THP is
heavily used by the applications. The 2M continuous pages will be
free up after THP swapping out.
- It will improve the THP utilization on the system with the swap
turned on. Because the speed for khugepaged to collapse the normal
pages into the THP is quite slow. After the THP is split during the
swapping out, it will take quite long time for the normal pages to
collapse back into the THP after being swapped in. The high THP
utilization helps the efficiency of the page based memory management
too.
There are some concerns regarding THP swap in, mainly because possible
enlarged read/write IO size (for swap in/out) may put more overhead on
the storage device. To deal with that, the THP swap in should be turned
on only when necessary. For example, it can be selected via
"always/never/madvise" logic, to be turned on globally, turned off
globally, or turned on only for VMA with MADV_HUGEPAGE, etc.
This patchset is the first step for the THP swap support. The plan is
to delay splitting THP step by step, finally avoid splitting THP during
the THP swapping out and swap out/in the THP as a whole.
As the first step, in this patchset, the splitting huge page is delayed
from almost the first step of swapping out to after allocating the swap
space for the THP and adding the THP into the swap cache. This will
reduce lock acquiring/releasing for the locks used for the swap cache
management.
With the patchset, the swap out throughput improves 15.5% (from about
3.73GB/s to about 4.31GB/s) in the vm-scalability swap-w-seq test case
with 8 processes. The test is done on a Xeon E5 v3 system. The swap
device used is a RAM simulated PMEM (persistent memory) device. To test
the sequential swapping out, the test case creates 8 processes, which
sequentially allocate and write to the anonymous pages until the RAM and
part of the swap device is used up.
This patch (of 5):
In this patch, splitting huge page is delayed from almost the first step
of swapping out to after allocating the swap space for the THP
(Transparent Huge Page) and adding the THP into the swap cache. This
will batch the corresponding operation, thus improve THP swap out
throughput.
This is the first step for the THP swap optimization. The plan is to
delay splitting the THP step by step and avoid splitting the THP
finally.
In this patch, one swap cluster is used to hold the contents of each THP
swapped out. So, the size of the swap cluster is changed to that of the
THP (Transparent Huge Page) on x86_64 architecture (512). For other
architectures which want such THP swap optimization,
ARCH_USES_THP_SWAP_CLUSTER needs to be selected in the Kconfig file for
the architecture. In effect, this will enlarge swap cluster size by 2
times on x86_64. Which may make it harder to find a free cluster when
the swap space becomes fragmented. So that, this may reduce the
continuous swap space allocation and sequential write in theory. The
performance test in 0day shows no regressions caused by this.
In the future of THP swap optimization, some information of the swapped
out THP (such as compound map count) will be recorded in the
swap_cluster_info data structure.
The mem cgroup swap accounting functions are enhanced to support charge
or uncharge a swap cluster backing a THP as a whole.
The swap cluster allocate/free functions are added to allocate/free a
swap cluster for a THP. A fair simple algorithm is used for swap
cluster allocation, that is, only the first swap device in priority list
will be tried to allocate the swap cluster. The function will fail if
the trying is not successful, and the caller will fallback to allocate a
single swap slot instead. This works good enough for normal cases. If
the difference of the number of the free swap clusters among multiple
swap devices is significant, it is possible that some THPs are split
earlier than necessary. For example, this could be caused by big size
difference among multiple swap devices.
The swap cache functions is enhanced to support add/delete THP to/from
the swap cache as a set of (HPAGE_PMD_NR) sub-pages. This may be
enhanced in the future with multi-order radix tree. But because we will
split the THP soon during swapping out, that optimization doesn't make
much sense for this first step.
The THP splitting functions are enhanced to support to split THP in swap
cache during swapping out. The page lock will be held during allocating
the swap cluster, adding the THP into the swap cache and splitting the
THP. So in the code path other than swapping out, if the THP need to be
split, the PageSwapCache(THP) will be always false.
The swap cluster is only available for SSD, so the THP swap optimization
in this patchset has no effect for HDD.
[ying.huang@intel.com: fix two issues in THP optimize patch]
Link: http://lkml.kernel.org/r/87k25ed8zo.fsf@yhuang-dev.intel.com
[hannes@cmpxchg.org: extensive cleanups and simplifications, reduce code size]
Link: http://lkml.kernel.org/r/20170515112522.32457-2-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Signed-off-by: Johannes Weiner <hannes@cmpxchg.org>
Suggested-by: Andrew Morton <akpm@linux-foundation.org> [for config option]
Acked-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> [for changes in huge_memory.c and huge_mm.h]
Cc: Andrea Arcangeli <aarcange@redhat.com>
Cc: Ebru Akagunduz <ebru.akagunduz@gmail.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Michal Hocko <mhocko@kernel.org>
Cc: Tejun Heo <tj@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-07 01:37:18 +03:00
pgoff_t idx = swp_offset ( entry ) ;
2017-11-27 23:46:54 +03:00
XA_STATE_ORDER ( xas , & address_space - > i_pages , idx , compound_order ( page ) ) ;
2020-08-15 03:30:37 +03:00
unsigned long i , nr = thp_nr_pages ( page ) ;
2020-08-12 04:30:47 +03:00
void * old ;
2005-04-17 02:20:36 +04:00
2014-01-24 03:52:54 +04:00
VM_BUG_ON_PAGE ( ! PageLocked ( page ) , page ) ;
VM_BUG_ON_PAGE ( PageSwapCache ( page ) , page ) ;
VM_BUG_ON_PAGE ( ! PageSwapBacked ( page ) , page ) ;
2009-01-07 01:39:25 +03:00
mm, THP, swap: delay splitting THP during swap out
Patch series "THP swap: Delay splitting THP during swapping out", v11.
This patchset is to optimize the performance of Transparent Huge Page
(THP) swap.
Recently, the performance of the storage devices improved so fast that
we cannot saturate the disk bandwidth with single logical CPU when do
page swap out even on a high-end server machine. Because the
performance of the storage device improved faster than that of single
logical CPU. And it seems that the trend will not change in the near
future. On the other hand, the THP becomes more and more popular
because of increased memory size. So it becomes necessary to optimize
THP swap performance.
The advantages of the THP swap support include:
- Batch the swap operations for the THP to reduce lock
acquiring/releasing, including allocating/freeing the swap space,
adding/deleting to/from the swap cache, and writing/reading the swap
space, etc. This will help improve the performance of the THP swap.
- The THP swap space read/write will be 2M sequential IO. It is
particularly helpful for the swap read, which are usually 4k random
IO. This will improve the performance of the THP swap too.
- It will help the memory fragmentation, especially when the THP is
heavily used by the applications. The 2M continuous pages will be
free up after THP swapping out.
- It will improve the THP utilization on the system with the swap
turned on. Because the speed for khugepaged to collapse the normal
pages into the THP is quite slow. After the THP is split during the
swapping out, it will take quite long time for the normal pages to
collapse back into the THP after being swapped in. The high THP
utilization helps the efficiency of the page based memory management
too.
There are some concerns regarding THP swap in, mainly because possible
enlarged read/write IO size (for swap in/out) may put more overhead on
the storage device. To deal with that, the THP swap in should be turned
on only when necessary. For example, it can be selected via
"always/never/madvise" logic, to be turned on globally, turned off
globally, or turned on only for VMA with MADV_HUGEPAGE, etc.
This patchset is the first step for the THP swap support. The plan is
to delay splitting THP step by step, finally avoid splitting THP during
the THP swapping out and swap out/in the THP as a whole.
As the first step, in this patchset, the splitting huge page is delayed
from almost the first step of swapping out to after allocating the swap
space for the THP and adding the THP into the swap cache. This will
reduce lock acquiring/releasing for the locks used for the swap cache
management.
With the patchset, the swap out throughput improves 15.5% (from about
3.73GB/s to about 4.31GB/s) in the vm-scalability swap-w-seq test case
with 8 processes. The test is done on a Xeon E5 v3 system. The swap
device used is a RAM simulated PMEM (persistent memory) device. To test
the sequential swapping out, the test case creates 8 processes, which
sequentially allocate and write to the anonymous pages until the RAM and
part of the swap device is used up.
This patch (of 5):
In this patch, splitting huge page is delayed from almost the first step
of swapping out to after allocating the swap space for the THP
(Transparent Huge Page) and adding the THP into the swap cache. This
will batch the corresponding operation, thus improve THP swap out
throughput.
This is the first step for the THP swap optimization. The plan is to
delay splitting the THP step by step and avoid splitting the THP
finally.
In this patch, one swap cluster is used to hold the contents of each THP
swapped out. So, the size of the swap cluster is changed to that of the
THP (Transparent Huge Page) on x86_64 architecture (512). For other
architectures which want such THP swap optimization,
ARCH_USES_THP_SWAP_CLUSTER needs to be selected in the Kconfig file for
the architecture. In effect, this will enlarge swap cluster size by 2
times on x86_64. Which may make it harder to find a free cluster when
the swap space becomes fragmented. So that, this may reduce the
continuous swap space allocation and sequential write in theory. The
performance test in 0day shows no regressions caused by this.
In the future of THP swap optimization, some information of the swapped
out THP (such as compound map count) will be recorded in the
swap_cluster_info data structure.
The mem cgroup swap accounting functions are enhanced to support charge
or uncharge a swap cluster backing a THP as a whole.
The swap cluster allocate/free functions are added to allocate/free a
swap cluster for a THP. A fair simple algorithm is used for swap
cluster allocation, that is, only the first swap device in priority list
will be tried to allocate the swap cluster. The function will fail if
the trying is not successful, and the caller will fallback to allocate a
single swap slot instead. This works good enough for normal cases. If
the difference of the number of the free swap clusters among multiple
swap devices is significant, it is possible that some THPs are split
earlier than necessary. For example, this could be caused by big size
difference among multiple swap devices.
The swap cache functions is enhanced to support add/delete THP to/from
the swap cache as a set of (HPAGE_PMD_NR) sub-pages. This may be
enhanced in the future with multi-order radix tree. But because we will
split the THP soon during swapping out, that optimization doesn't make
much sense for this first step.
The THP splitting functions are enhanced to support to split THP in swap
cache during swapping out. The page lock will be held during allocating
the swap cluster, adding the THP into the swap cache and splitting the
THP. So in the code path other than swapping out, if the THP need to be
split, the PageSwapCache(THP) will be always false.
The swap cluster is only available for SSD, so the THP swap optimization
in this patchset has no effect for HDD.
[ying.huang@intel.com: fix two issues in THP optimize patch]
Link: http://lkml.kernel.org/r/87k25ed8zo.fsf@yhuang-dev.intel.com
[hannes@cmpxchg.org: extensive cleanups and simplifications, reduce code size]
Link: http://lkml.kernel.org/r/20170515112522.32457-2-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Signed-off-by: Johannes Weiner <hannes@cmpxchg.org>
Suggested-by: Andrew Morton <akpm@linux-foundation.org> [for config option]
Acked-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> [for changes in huge_memory.c and huge_mm.h]
Cc: Andrea Arcangeli <aarcange@redhat.com>
Cc: Ebru Akagunduz <ebru.akagunduz@gmail.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Michal Hocko <mhocko@kernel.org>
Cc: Tejun Heo <tj@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-07 01:37:18 +03:00
page_ref_add ( page , nr ) ;
2009-09-22 04:02:50 +04:00
SetPageSwapCache ( page ) ;
2017-11-27 23:46:54 +03:00
do {
xas_lock_irq ( & xas ) ;
xas_create_range ( & xas ) ;
if ( xas_error ( & xas ) )
goto unlock ;
for ( i = 0 ; i < nr ; i + + ) {
VM_BUG_ON_PAGE ( xas . xa_index ! = idx + i , page ) ;
2020-08-12 04:30:47 +03:00
old = xas_load ( & xas ) ;
if ( xa_is_value ( old ) ) {
if ( shadowp )
* shadowp = old ;
}
2017-11-27 23:46:54 +03:00
set_page_private ( page + i , entry . val + i ) ;
2019-09-24 01:34:52 +03:00
xas_store ( & xas , page ) ;
2017-11-27 23:46:54 +03:00
xas_next ( & xas ) ;
}
mm, THP, swap: delay splitting THP during swap out
Patch series "THP swap: Delay splitting THP during swapping out", v11.
This patchset is to optimize the performance of Transparent Huge Page
(THP) swap.
Recently, the performance of the storage devices improved so fast that
we cannot saturate the disk bandwidth with single logical CPU when do
page swap out even on a high-end server machine. Because the
performance of the storage device improved faster than that of single
logical CPU. And it seems that the trend will not change in the near
future. On the other hand, the THP becomes more and more popular
because of increased memory size. So it becomes necessary to optimize
THP swap performance.
The advantages of the THP swap support include:
- Batch the swap operations for the THP to reduce lock
acquiring/releasing, including allocating/freeing the swap space,
adding/deleting to/from the swap cache, and writing/reading the swap
space, etc. This will help improve the performance of the THP swap.
- The THP swap space read/write will be 2M sequential IO. It is
particularly helpful for the swap read, which are usually 4k random
IO. This will improve the performance of the THP swap too.
- It will help the memory fragmentation, especially when the THP is
heavily used by the applications. The 2M continuous pages will be
free up after THP swapping out.
- It will improve the THP utilization on the system with the swap
turned on. Because the speed for khugepaged to collapse the normal
pages into the THP is quite slow. After the THP is split during the
swapping out, it will take quite long time for the normal pages to
collapse back into the THP after being swapped in. The high THP
utilization helps the efficiency of the page based memory management
too.
There are some concerns regarding THP swap in, mainly because possible
enlarged read/write IO size (for swap in/out) may put more overhead on
the storage device. To deal with that, the THP swap in should be turned
on only when necessary. For example, it can be selected via
"always/never/madvise" logic, to be turned on globally, turned off
globally, or turned on only for VMA with MADV_HUGEPAGE, etc.
This patchset is the first step for the THP swap support. The plan is
to delay splitting THP step by step, finally avoid splitting THP during
the THP swapping out and swap out/in the THP as a whole.
As the first step, in this patchset, the splitting huge page is delayed
from almost the first step of swapping out to after allocating the swap
space for the THP and adding the THP into the swap cache. This will
reduce lock acquiring/releasing for the locks used for the swap cache
management.
With the patchset, the swap out throughput improves 15.5% (from about
3.73GB/s to about 4.31GB/s) in the vm-scalability swap-w-seq test case
with 8 processes. The test is done on a Xeon E5 v3 system. The swap
device used is a RAM simulated PMEM (persistent memory) device. To test
the sequential swapping out, the test case creates 8 processes, which
sequentially allocate and write to the anonymous pages until the RAM and
part of the swap device is used up.
This patch (of 5):
In this patch, splitting huge page is delayed from almost the first step
of swapping out to after allocating the swap space for the THP
(Transparent Huge Page) and adding the THP into the swap cache. This
will batch the corresponding operation, thus improve THP swap out
throughput.
This is the first step for the THP swap optimization. The plan is to
delay splitting the THP step by step and avoid splitting the THP
finally.
In this patch, one swap cluster is used to hold the contents of each THP
swapped out. So, the size of the swap cluster is changed to that of the
THP (Transparent Huge Page) on x86_64 architecture (512). For other
architectures which want such THP swap optimization,
ARCH_USES_THP_SWAP_CLUSTER needs to be selected in the Kconfig file for
the architecture. In effect, this will enlarge swap cluster size by 2
times on x86_64. Which may make it harder to find a free cluster when
the swap space becomes fragmented. So that, this may reduce the
continuous swap space allocation and sequential write in theory. The
performance test in 0day shows no regressions caused by this.
In the future of THP swap optimization, some information of the swapped
out THP (such as compound map count) will be recorded in the
swap_cluster_info data structure.
The mem cgroup swap accounting functions are enhanced to support charge
or uncharge a swap cluster backing a THP as a whole.
The swap cluster allocate/free functions are added to allocate/free a
swap cluster for a THP. A fair simple algorithm is used for swap
cluster allocation, that is, only the first swap device in priority list
will be tried to allocate the swap cluster. The function will fail if
the trying is not successful, and the caller will fallback to allocate a
single swap slot instead. This works good enough for normal cases. If
the difference of the number of the free swap clusters among multiple
swap devices is significant, it is possible that some THPs are split
earlier than necessary. For example, this could be caused by big size
difference among multiple swap devices.
The swap cache functions is enhanced to support add/delete THP to/from
the swap cache as a set of (HPAGE_PMD_NR) sub-pages. This may be
enhanced in the future with multi-order radix tree. But because we will
split the THP soon during swapping out, that optimization doesn't make
much sense for this first step.
The THP splitting functions are enhanced to support to split THP in swap
cache during swapping out. The page lock will be held during allocating
the swap cluster, adding the THP into the swap cache and splitting the
THP. So in the code path other than swapping out, if the THP need to be
split, the PageSwapCache(THP) will be always false.
The swap cluster is only available for SSD, so the THP swap optimization
in this patchset has no effect for HDD.
[ying.huang@intel.com: fix two issues in THP optimize patch]
Link: http://lkml.kernel.org/r/87k25ed8zo.fsf@yhuang-dev.intel.com
[hannes@cmpxchg.org: extensive cleanups and simplifications, reduce code size]
Link: http://lkml.kernel.org/r/20170515112522.32457-2-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Signed-off-by: Johannes Weiner <hannes@cmpxchg.org>
Suggested-by: Andrew Morton <akpm@linux-foundation.org> [for config option]
Acked-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> [for changes in huge_memory.c and huge_mm.h]
Cc: Andrea Arcangeli <aarcange@redhat.com>
Cc: Ebru Akagunduz <ebru.akagunduz@gmail.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Michal Hocko <mhocko@kernel.org>
Cc: Tejun Heo <tj@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-07 01:37:18 +03:00
address_space - > nrpages + = nr ;
__mod_node_page_state ( page_pgdat ( page ) , NR_FILE_PAGES , nr ) ;
2021-02-24 23:03:55 +03:00
__mod_lruvec_page_state ( page , NR_SWAPCACHE , nr ) ;
mm, THP, swap: delay splitting THP during swap out
Patch series "THP swap: Delay splitting THP during swapping out", v11.
This patchset is to optimize the performance of Transparent Huge Page
(THP) swap.
Recently, the performance of the storage devices improved so fast that
we cannot saturate the disk bandwidth with single logical CPU when do
page swap out even on a high-end server machine. Because the
performance of the storage device improved faster than that of single
logical CPU. And it seems that the trend will not change in the near
future. On the other hand, the THP becomes more and more popular
because of increased memory size. So it becomes necessary to optimize
THP swap performance.
The advantages of the THP swap support include:
- Batch the swap operations for the THP to reduce lock
acquiring/releasing, including allocating/freeing the swap space,
adding/deleting to/from the swap cache, and writing/reading the swap
space, etc. This will help improve the performance of the THP swap.
- The THP swap space read/write will be 2M sequential IO. It is
particularly helpful for the swap read, which are usually 4k random
IO. This will improve the performance of the THP swap too.
- It will help the memory fragmentation, especially when the THP is
heavily used by the applications. The 2M continuous pages will be
free up after THP swapping out.
- It will improve the THP utilization on the system with the swap
turned on. Because the speed for khugepaged to collapse the normal
pages into the THP is quite slow. After the THP is split during the
swapping out, it will take quite long time for the normal pages to
collapse back into the THP after being swapped in. The high THP
utilization helps the efficiency of the page based memory management
too.
There are some concerns regarding THP swap in, mainly because possible
enlarged read/write IO size (for swap in/out) may put more overhead on
the storage device. To deal with that, the THP swap in should be turned
on only when necessary. For example, it can be selected via
"always/never/madvise" logic, to be turned on globally, turned off
globally, or turned on only for VMA with MADV_HUGEPAGE, etc.
This patchset is the first step for the THP swap support. The plan is
to delay splitting THP step by step, finally avoid splitting THP during
the THP swapping out and swap out/in the THP as a whole.
As the first step, in this patchset, the splitting huge page is delayed
from almost the first step of swapping out to after allocating the swap
space for the THP and adding the THP into the swap cache. This will
reduce lock acquiring/releasing for the locks used for the swap cache
management.
With the patchset, the swap out throughput improves 15.5% (from about
3.73GB/s to about 4.31GB/s) in the vm-scalability swap-w-seq test case
with 8 processes. The test is done on a Xeon E5 v3 system. The swap
device used is a RAM simulated PMEM (persistent memory) device. To test
the sequential swapping out, the test case creates 8 processes, which
sequentially allocate and write to the anonymous pages until the RAM and
part of the swap device is used up.
This patch (of 5):
In this patch, splitting huge page is delayed from almost the first step
of swapping out to after allocating the swap space for the THP
(Transparent Huge Page) and adding the THP into the swap cache. This
will batch the corresponding operation, thus improve THP swap out
throughput.
This is the first step for the THP swap optimization. The plan is to
delay splitting the THP step by step and avoid splitting the THP
finally.
In this patch, one swap cluster is used to hold the contents of each THP
swapped out. So, the size of the swap cluster is changed to that of the
THP (Transparent Huge Page) on x86_64 architecture (512). For other
architectures which want such THP swap optimization,
ARCH_USES_THP_SWAP_CLUSTER needs to be selected in the Kconfig file for
the architecture. In effect, this will enlarge swap cluster size by 2
times on x86_64. Which may make it harder to find a free cluster when
the swap space becomes fragmented. So that, this may reduce the
continuous swap space allocation and sequential write in theory. The
performance test in 0day shows no regressions caused by this.
In the future of THP swap optimization, some information of the swapped
out THP (such as compound map count) will be recorded in the
swap_cluster_info data structure.
The mem cgroup swap accounting functions are enhanced to support charge
or uncharge a swap cluster backing a THP as a whole.
The swap cluster allocate/free functions are added to allocate/free a
swap cluster for a THP. A fair simple algorithm is used for swap
cluster allocation, that is, only the first swap device in priority list
will be tried to allocate the swap cluster. The function will fail if
the trying is not successful, and the caller will fallback to allocate a
single swap slot instead. This works good enough for normal cases. If
the difference of the number of the free swap clusters among multiple
swap devices is significant, it is possible that some THPs are split
earlier than necessary. For example, this could be caused by big size
difference among multiple swap devices.
The swap cache functions is enhanced to support add/delete THP to/from
the swap cache as a set of (HPAGE_PMD_NR) sub-pages. This may be
enhanced in the future with multi-order radix tree. But because we will
split the THP soon during swapping out, that optimization doesn't make
much sense for this first step.
The THP splitting functions are enhanced to support to split THP in swap
cache during swapping out. The page lock will be held during allocating
the swap cluster, adding the THP into the swap cache and splitting the
THP. So in the code path other than swapping out, if the THP need to be
split, the PageSwapCache(THP) will be always false.
The swap cluster is only available for SSD, so the THP swap optimization
in this patchset has no effect for HDD.
[ying.huang@intel.com: fix two issues in THP optimize patch]
Link: http://lkml.kernel.org/r/87k25ed8zo.fsf@yhuang-dev.intel.com
[hannes@cmpxchg.org: extensive cleanups and simplifications, reduce code size]
Link: http://lkml.kernel.org/r/20170515112522.32457-2-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Signed-off-by: Johannes Weiner <hannes@cmpxchg.org>
Suggested-by: Andrew Morton <akpm@linux-foundation.org> [for config option]
Acked-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> [for changes in huge_memory.c and huge_mm.h]
Cc: Andrea Arcangeli <aarcange@redhat.com>
Cc: Ebru Akagunduz <ebru.akagunduz@gmail.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Michal Hocko <mhocko@kernel.org>
Cc: Tejun Heo <tj@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-07 01:37:18 +03:00
ADD_CACHE_INFO ( add_total , nr ) ;
2017-11-27 23:46:54 +03:00
unlock :
xas_unlock_irq ( & xas ) ;
} while ( xas_nomem ( & xas , gfp ) ) ;
2009-09-22 04:02:50 +04:00
2017-11-27 23:46:54 +03:00
if ( ! xas_error ( & xas ) )
return 0 ;
2009-09-22 04:02:50 +04:00
2017-11-27 23:46:54 +03:00
ClearPageSwapCache ( page ) ;
page_ref_sub ( page , nr ) ;
return xas_error ( & xas ) ;
2005-04-17 02:20:36 +04:00
}
/*
* This must be called only on pages that have
* been verified to be in the swap cache .
*/
2020-08-12 04:30:47 +03:00
void __delete_from_swap_cache ( struct page * page ,
swp_entry_t entry , void * shadow )
2005-04-17 02:20:36 +04:00
{
2017-11-29 16:32:39 +03:00
struct address_space * address_space = swap_address_space ( entry ) ;
2020-08-15 03:30:37 +03:00
int i , nr = thp_nr_pages ( page ) ;
2017-11-29 16:32:39 +03:00
pgoff_t idx = swp_offset ( entry ) ;
XA_STATE ( xas , & address_space - > i_pages , idx ) ;
2013-02-23 04:34:37 +04:00
2014-01-24 03:52:54 +04:00
VM_BUG_ON_PAGE ( ! PageLocked ( page ) , page ) ;
VM_BUG_ON_PAGE ( ! PageSwapCache ( page ) , page ) ;
VM_BUG_ON_PAGE ( PageWriteback ( page ) , page ) ;
2005-04-17 02:20:36 +04:00
mm, THP, swap: delay splitting THP during swap out
Patch series "THP swap: Delay splitting THP during swapping out", v11.
This patchset is to optimize the performance of Transparent Huge Page
(THP) swap.
Recently, the performance of the storage devices improved so fast that
we cannot saturate the disk bandwidth with single logical CPU when do
page swap out even on a high-end server machine. Because the
performance of the storage device improved faster than that of single
logical CPU. And it seems that the trend will not change in the near
future. On the other hand, the THP becomes more and more popular
because of increased memory size. So it becomes necessary to optimize
THP swap performance.
The advantages of the THP swap support include:
- Batch the swap operations for the THP to reduce lock
acquiring/releasing, including allocating/freeing the swap space,
adding/deleting to/from the swap cache, and writing/reading the swap
space, etc. This will help improve the performance of the THP swap.
- The THP swap space read/write will be 2M sequential IO. It is
particularly helpful for the swap read, which are usually 4k random
IO. This will improve the performance of the THP swap too.
- It will help the memory fragmentation, especially when the THP is
heavily used by the applications. The 2M continuous pages will be
free up after THP swapping out.
- It will improve the THP utilization on the system with the swap
turned on. Because the speed for khugepaged to collapse the normal
pages into the THP is quite slow. After the THP is split during the
swapping out, it will take quite long time for the normal pages to
collapse back into the THP after being swapped in. The high THP
utilization helps the efficiency of the page based memory management
too.
There are some concerns regarding THP swap in, mainly because possible
enlarged read/write IO size (for swap in/out) may put more overhead on
the storage device. To deal with that, the THP swap in should be turned
on only when necessary. For example, it can be selected via
"always/never/madvise" logic, to be turned on globally, turned off
globally, or turned on only for VMA with MADV_HUGEPAGE, etc.
This patchset is the first step for the THP swap support. The plan is
to delay splitting THP step by step, finally avoid splitting THP during
the THP swapping out and swap out/in the THP as a whole.
As the first step, in this patchset, the splitting huge page is delayed
from almost the first step of swapping out to after allocating the swap
space for the THP and adding the THP into the swap cache. This will
reduce lock acquiring/releasing for the locks used for the swap cache
management.
With the patchset, the swap out throughput improves 15.5% (from about
3.73GB/s to about 4.31GB/s) in the vm-scalability swap-w-seq test case
with 8 processes. The test is done on a Xeon E5 v3 system. The swap
device used is a RAM simulated PMEM (persistent memory) device. To test
the sequential swapping out, the test case creates 8 processes, which
sequentially allocate and write to the anonymous pages until the RAM and
part of the swap device is used up.
This patch (of 5):
In this patch, splitting huge page is delayed from almost the first step
of swapping out to after allocating the swap space for the THP
(Transparent Huge Page) and adding the THP into the swap cache. This
will batch the corresponding operation, thus improve THP swap out
throughput.
This is the first step for the THP swap optimization. The plan is to
delay splitting the THP step by step and avoid splitting the THP
finally.
In this patch, one swap cluster is used to hold the contents of each THP
swapped out. So, the size of the swap cluster is changed to that of the
THP (Transparent Huge Page) on x86_64 architecture (512). For other
architectures which want such THP swap optimization,
ARCH_USES_THP_SWAP_CLUSTER needs to be selected in the Kconfig file for
the architecture. In effect, this will enlarge swap cluster size by 2
times on x86_64. Which may make it harder to find a free cluster when
the swap space becomes fragmented. So that, this may reduce the
continuous swap space allocation and sequential write in theory. The
performance test in 0day shows no regressions caused by this.
In the future of THP swap optimization, some information of the swapped
out THP (such as compound map count) will be recorded in the
swap_cluster_info data structure.
The mem cgroup swap accounting functions are enhanced to support charge
or uncharge a swap cluster backing a THP as a whole.
The swap cluster allocate/free functions are added to allocate/free a
swap cluster for a THP. A fair simple algorithm is used for swap
cluster allocation, that is, only the first swap device in priority list
will be tried to allocate the swap cluster. The function will fail if
the trying is not successful, and the caller will fallback to allocate a
single swap slot instead. This works good enough for normal cases. If
the difference of the number of the free swap clusters among multiple
swap devices is significant, it is possible that some THPs are split
earlier than necessary. For example, this could be caused by big size
difference among multiple swap devices.
The swap cache functions is enhanced to support add/delete THP to/from
the swap cache as a set of (HPAGE_PMD_NR) sub-pages. This may be
enhanced in the future with multi-order radix tree. But because we will
split the THP soon during swapping out, that optimization doesn't make
much sense for this first step.
The THP splitting functions are enhanced to support to split THP in swap
cache during swapping out. The page lock will be held during allocating
the swap cluster, adding the THP into the swap cache and splitting the
THP. So in the code path other than swapping out, if the THP need to be
split, the PageSwapCache(THP) will be always false.
The swap cluster is only available for SSD, so the THP swap optimization
in this patchset has no effect for HDD.
[ying.huang@intel.com: fix two issues in THP optimize patch]
Link: http://lkml.kernel.org/r/87k25ed8zo.fsf@yhuang-dev.intel.com
[hannes@cmpxchg.org: extensive cleanups and simplifications, reduce code size]
Link: http://lkml.kernel.org/r/20170515112522.32457-2-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Signed-off-by: Johannes Weiner <hannes@cmpxchg.org>
Suggested-by: Andrew Morton <akpm@linux-foundation.org> [for config option]
Acked-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> [for changes in huge_memory.c and huge_mm.h]
Cc: Andrea Arcangeli <aarcange@redhat.com>
Cc: Ebru Akagunduz <ebru.akagunduz@gmail.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Michal Hocko <mhocko@kernel.org>
Cc: Tejun Heo <tj@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-07 01:37:18 +03:00
for ( i = 0 ; i < nr ; i + + ) {
2020-08-12 04:30:47 +03:00
void * entry = xas_store ( & xas , shadow ) ;
2019-09-24 01:34:52 +03:00
VM_BUG_ON_PAGE ( entry ! = page , entry ) ;
mm, THP, swap: delay splitting THP during swap out
Patch series "THP swap: Delay splitting THP during swapping out", v11.
This patchset is to optimize the performance of Transparent Huge Page
(THP) swap.
Recently, the performance of the storage devices improved so fast that
we cannot saturate the disk bandwidth with single logical CPU when do
page swap out even on a high-end server machine. Because the
performance of the storage device improved faster than that of single
logical CPU. And it seems that the trend will not change in the near
future. On the other hand, the THP becomes more and more popular
because of increased memory size. So it becomes necessary to optimize
THP swap performance.
The advantages of the THP swap support include:
- Batch the swap operations for the THP to reduce lock
acquiring/releasing, including allocating/freeing the swap space,
adding/deleting to/from the swap cache, and writing/reading the swap
space, etc. This will help improve the performance of the THP swap.
- The THP swap space read/write will be 2M sequential IO. It is
particularly helpful for the swap read, which are usually 4k random
IO. This will improve the performance of the THP swap too.
- It will help the memory fragmentation, especially when the THP is
heavily used by the applications. The 2M continuous pages will be
free up after THP swapping out.
- It will improve the THP utilization on the system with the swap
turned on. Because the speed for khugepaged to collapse the normal
pages into the THP is quite slow. After the THP is split during the
swapping out, it will take quite long time for the normal pages to
collapse back into the THP after being swapped in. The high THP
utilization helps the efficiency of the page based memory management
too.
There are some concerns regarding THP swap in, mainly because possible
enlarged read/write IO size (for swap in/out) may put more overhead on
the storage device. To deal with that, the THP swap in should be turned
on only when necessary. For example, it can be selected via
"always/never/madvise" logic, to be turned on globally, turned off
globally, or turned on only for VMA with MADV_HUGEPAGE, etc.
This patchset is the first step for the THP swap support. The plan is
to delay splitting THP step by step, finally avoid splitting THP during
the THP swapping out and swap out/in the THP as a whole.
As the first step, in this patchset, the splitting huge page is delayed
from almost the first step of swapping out to after allocating the swap
space for the THP and adding the THP into the swap cache. This will
reduce lock acquiring/releasing for the locks used for the swap cache
management.
With the patchset, the swap out throughput improves 15.5% (from about
3.73GB/s to about 4.31GB/s) in the vm-scalability swap-w-seq test case
with 8 processes. The test is done on a Xeon E5 v3 system. The swap
device used is a RAM simulated PMEM (persistent memory) device. To test
the sequential swapping out, the test case creates 8 processes, which
sequentially allocate and write to the anonymous pages until the RAM and
part of the swap device is used up.
This patch (of 5):
In this patch, splitting huge page is delayed from almost the first step
of swapping out to after allocating the swap space for the THP
(Transparent Huge Page) and adding the THP into the swap cache. This
will batch the corresponding operation, thus improve THP swap out
throughput.
This is the first step for the THP swap optimization. The plan is to
delay splitting the THP step by step and avoid splitting the THP
finally.
In this patch, one swap cluster is used to hold the contents of each THP
swapped out. So, the size of the swap cluster is changed to that of the
THP (Transparent Huge Page) on x86_64 architecture (512). For other
architectures which want such THP swap optimization,
ARCH_USES_THP_SWAP_CLUSTER needs to be selected in the Kconfig file for
the architecture. In effect, this will enlarge swap cluster size by 2
times on x86_64. Which may make it harder to find a free cluster when
the swap space becomes fragmented. So that, this may reduce the
continuous swap space allocation and sequential write in theory. The
performance test in 0day shows no regressions caused by this.
In the future of THP swap optimization, some information of the swapped
out THP (such as compound map count) will be recorded in the
swap_cluster_info data structure.
The mem cgroup swap accounting functions are enhanced to support charge
or uncharge a swap cluster backing a THP as a whole.
The swap cluster allocate/free functions are added to allocate/free a
swap cluster for a THP. A fair simple algorithm is used for swap
cluster allocation, that is, only the first swap device in priority list
will be tried to allocate the swap cluster. The function will fail if
the trying is not successful, and the caller will fallback to allocate a
single swap slot instead. This works good enough for normal cases. If
the difference of the number of the free swap clusters among multiple
swap devices is significant, it is possible that some THPs are split
earlier than necessary. For example, this could be caused by big size
difference among multiple swap devices.
The swap cache functions is enhanced to support add/delete THP to/from
the swap cache as a set of (HPAGE_PMD_NR) sub-pages. This may be
enhanced in the future with multi-order radix tree. But because we will
split the THP soon during swapping out, that optimization doesn't make
much sense for this first step.
The THP splitting functions are enhanced to support to split THP in swap
cache during swapping out. The page lock will be held during allocating
the swap cluster, adding the THP into the swap cache and splitting the
THP. So in the code path other than swapping out, if the THP need to be
split, the PageSwapCache(THP) will be always false.
The swap cluster is only available for SSD, so the THP swap optimization
in this patchset has no effect for HDD.
[ying.huang@intel.com: fix two issues in THP optimize patch]
Link: http://lkml.kernel.org/r/87k25ed8zo.fsf@yhuang-dev.intel.com
[hannes@cmpxchg.org: extensive cleanups and simplifications, reduce code size]
Link: http://lkml.kernel.org/r/20170515112522.32457-2-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Signed-off-by: Johannes Weiner <hannes@cmpxchg.org>
Suggested-by: Andrew Morton <akpm@linux-foundation.org> [for config option]
Acked-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> [for changes in huge_memory.c and huge_mm.h]
Cc: Andrea Arcangeli <aarcange@redhat.com>
Cc: Ebru Akagunduz <ebru.akagunduz@gmail.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Michal Hocko <mhocko@kernel.org>
Cc: Tejun Heo <tj@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-07 01:37:18 +03:00
set_page_private ( page + i , 0 ) ;
2017-11-29 16:32:39 +03:00
xas_next ( & xas ) ;
mm, THP, swap: delay splitting THP during swap out
Patch series "THP swap: Delay splitting THP during swapping out", v11.
This patchset is to optimize the performance of Transparent Huge Page
(THP) swap.
Recently, the performance of the storage devices improved so fast that
we cannot saturate the disk bandwidth with single logical CPU when do
page swap out even on a high-end server machine. Because the
performance of the storage device improved faster than that of single
logical CPU. And it seems that the trend will not change in the near
future. On the other hand, the THP becomes more and more popular
because of increased memory size. So it becomes necessary to optimize
THP swap performance.
The advantages of the THP swap support include:
- Batch the swap operations for the THP to reduce lock
acquiring/releasing, including allocating/freeing the swap space,
adding/deleting to/from the swap cache, and writing/reading the swap
space, etc. This will help improve the performance of the THP swap.
- The THP swap space read/write will be 2M sequential IO. It is
particularly helpful for the swap read, which are usually 4k random
IO. This will improve the performance of the THP swap too.
- It will help the memory fragmentation, especially when the THP is
heavily used by the applications. The 2M continuous pages will be
free up after THP swapping out.
- It will improve the THP utilization on the system with the swap
turned on. Because the speed for khugepaged to collapse the normal
pages into the THP is quite slow. After the THP is split during the
swapping out, it will take quite long time for the normal pages to
collapse back into the THP after being swapped in. The high THP
utilization helps the efficiency of the page based memory management
too.
There are some concerns regarding THP swap in, mainly because possible
enlarged read/write IO size (for swap in/out) may put more overhead on
the storage device. To deal with that, the THP swap in should be turned
on only when necessary. For example, it can be selected via
"always/never/madvise" logic, to be turned on globally, turned off
globally, or turned on only for VMA with MADV_HUGEPAGE, etc.
This patchset is the first step for the THP swap support. The plan is
to delay splitting THP step by step, finally avoid splitting THP during
the THP swapping out and swap out/in the THP as a whole.
As the first step, in this patchset, the splitting huge page is delayed
from almost the first step of swapping out to after allocating the swap
space for the THP and adding the THP into the swap cache. This will
reduce lock acquiring/releasing for the locks used for the swap cache
management.
With the patchset, the swap out throughput improves 15.5% (from about
3.73GB/s to about 4.31GB/s) in the vm-scalability swap-w-seq test case
with 8 processes. The test is done on a Xeon E5 v3 system. The swap
device used is a RAM simulated PMEM (persistent memory) device. To test
the sequential swapping out, the test case creates 8 processes, which
sequentially allocate and write to the anonymous pages until the RAM and
part of the swap device is used up.
This patch (of 5):
In this patch, splitting huge page is delayed from almost the first step
of swapping out to after allocating the swap space for the THP
(Transparent Huge Page) and adding the THP into the swap cache. This
will batch the corresponding operation, thus improve THP swap out
throughput.
This is the first step for the THP swap optimization. The plan is to
delay splitting the THP step by step and avoid splitting the THP
finally.
In this patch, one swap cluster is used to hold the contents of each THP
swapped out. So, the size of the swap cluster is changed to that of the
THP (Transparent Huge Page) on x86_64 architecture (512). For other
architectures which want such THP swap optimization,
ARCH_USES_THP_SWAP_CLUSTER needs to be selected in the Kconfig file for
the architecture. In effect, this will enlarge swap cluster size by 2
times on x86_64. Which may make it harder to find a free cluster when
the swap space becomes fragmented. So that, this may reduce the
continuous swap space allocation and sequential write in theory. The
performance test in 0day shows no regressions caused by this.
In the future of THP swap optimization, some information of the swapped
out THP (such as compound map count) will be recorded in the
swap_cluster_info data structure.
The mem cgroup swap accounting functions are enhanced to support charge
or uncharge a swap cluster backing a THP as a whole.
The swap cluster allocate/free functions are added to allocate/free a
swap cluster for a THP. A fair simple algorithm is used for swap
cluster allocation, that is, only the first swap device in priority list
will be tried to allocate the swap cluster. The function will fail if
the trying is not successful, and the caller will fallback to allocate a
single swap slot instead. This works good enough for normal cases. If
the difference of the number of the free swap clusters among multiple
swap devices is significant, it is possible that some THPs are split
earlier than necessary. For example, this could be caused by big size
difference among multiple swap devices.
The swap cache functions is enhanced to support add/delete THP to/from
the swap cache as a set of (HPAGE_PMD_NR) sub-pages. This may be
enhanced in the future with multi-order radix tree. But because we will
split the THP soon during swapping out, that optimization doesn't make
much sense for this first step.
The THP splitting functions are enhanced to support to split THP in swap
cache during swapping out. The page lock will be held during allocating
the swap cluster, adding the THP into the swap cache and splitting the
THP. So in the code path other than swapping out, if the THP need to be
split, the PageSwapCache(THP) will be always false.
The swap cluster is only available for SSD, so the THP swap optimization
in this patchset has no effect for HDD.
[ying.huang@intel.com: fix two issues in THP optimize patch]
Link: http://lkml.kernel.org/r/87k25ed8zo.fsf@yhuang-dev.intel.com
[hannes@cmpxchg.org: extensive cleanups and simplifications, reduce code size]
Link: http://lkml.kernel.org/r/20170515112522.32457-2-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Signed-off-by: Johannes Weiner <hannes@cmpxchg.org>
Suggested-by: Andrew Morton <akpm@linux-foundation.org> [for config option]
Acked-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> [for changes in huge_memory.c and huge_mm.h]
Cc: Andrea Arcangeli <aarcange@redhat.com>
Cc: Ebru Akagunduz <ebru.akagunduz@gmail.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Michal Hocko <mhocko@kernel.org>
Cc: Tejun Heo <tj@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-07 01:37:18 +03:00
}
2005-04-17 02:20:36 +04:00
ClearPageSwapCache ( page ) ;
mm, THP, swap: delay splitting THP during swap out
Patch series "THP swap: Delay splitting THP during swapping out", v11.
This patchset is to optimize the performance of Transparent Huge Page
(THP) swap.
Recently, the performance of the storage devices improved so fast that
we cannot saturate the disk bandwidth with single logical CPU when do
page swap out even on a high-end server machine. Because the
performance of the storage device improved faster than that of single
logical CPU. And it seems that the trend will not change in the near
future. On the other hand, the THP becomes more and more popular
because of increased memory size. So it becomes necessary to optimize
THP swap performance.
The advantages of the THP swap support include:
- Batch the swap operations for the THP to reduce lock
acquiring/releasing, including allocating/freeing the swap space,
adding/deleting to/from the swap cache, and writing/reading the swap
space, etc. This will help improve the performance of the THP swap.
- The THP swap space read/write will be 2M sequential IO. It is
particularly helpful for the swap read, which are usually 4k random
IO. This will improve the performance of the THP swap too.
- It will help the memory fragmentation, especially when the THP is
heavily used by the applications. The 2M continuous pages will be
free up after THP swapping out.
- It will improve the THP utilization on the system with the swap
turned on. Because the speed for khugepaged to collapse the normal
pages into the THP is quite slow. After the THP is split during the
swapping out, it will take quite long time for the normal pages to
collapse back into the THP after being swapped in. The high THP
utilization helps the efficiency of the page based memory management
too.
There are some concerns regarding THP swap in, mainly because possible
enlarged read/write IO size (for swap in/out) may put more overhead on
the storage device. To deal with that, the THP swap in should be turned
on only when necessary. For example, it can be selected via
"always/never/madvise" logic, to be turned on globally, turned off
globally, or turned on only for VMA with MADV_HUGEPAGE, etc.
This patchset is the first step for the THP swap support. The plan is
to delay splitting THP step by step, finally avoid splitting THP during
the THP swapping out and swap out/in the THP as a whole.
As the first step, in this patchset, the splitting huge page is delayed
from almost the first step of swapping out to after allocating the swap
space for the THP and adding the THP into the swap cache. This will
reduce lock acquiring/releasing for the locks used for the swap cache
management.
With the patchset, the swap out throughput improves 15.5% (from about
3.73GB/s to about 4.31GB/s) in the vm-scalability swap-w-seq test case
with 8 processes. The test is done on a Xeon E5 v3 system. The swap
device used is a RAM simulated PMEM (persistent memory) device. To test
the sequential swapping out, the test case creates 8 processes, which
sequentially allocate and write to the anonymous pages until the RAM and
part of the swap device is used up.
This patch (of 5):
In this patch, splitting huge page is delayed from almost the first step
of swapping out to after allocating the swap space for the THP
(Transparent Huge Page) and adding the THP into the swap cache. This
will batch the corresponding operation, thus improve THP swap out
throughput.
This is the first step for the THP swap optimization. The plan is to
delay splitting the THP step by step and avoid splitting the THP
finally.
In this patch, one swap cluster is used to hold the contents of each THP
swapped out. So, the size of the swap cluster is changed to that of the
THP (Transparent Huge Page) on x86_64 architecture (512). For other
architectures which want such THP swap optimization,
ARCH_USES_THP_SWAP_CLUSTER needs to be selected in the Kconfig file for
the architecture. In effect, this will enlarge swap cluster size by 2
times on x86_64. Which may make it harder to find a free cluster when
the swap space becomes fragmented. So that, this may reduce the
continuous swap space allocation and sequential write in theory. The
performance test in 0day shows no regressions caused by this.
In the future of THP swap optimization, some information of the swapped
out THP (such as compound map count) will be recorded in the
swap_cluster_info data structure.
The mem cgroup swap accounting functions are enhanced to support charge
or uncharge a swap cluster backing a THP as a whole.
The swap cluster allocate/free functions are added to allocate/free a
swap cluster for a THP. A fair simple algorithm is used for swap
cluster allocation, that is, only the first swap device in priority list
will be tried to allocate the swap cluster. The function will fail if
the trying is not successful, and the caller will fallback to allocate a
single swap slot instead. This works good enough for normal cases. If
the difference of the number of the free swap clusters among multiple
swap devices is significant, it is possible that some THPs are split
earlier than necessary. For example, this could be caused by big size
difference among multiple swap devices.
The swap cache functions is enhanced to support add/delete THP to/from
the swap cache as a set of (HPAGE_PMD_NR) sub-pages. This may be
enhanced in the future with multi-order radix tree. But because we will
split the THP soon during swapping out, that optimization doesn't make
much sense for this first step.
The THP splitting functions are enhanced to support to split THP in swap
cache during swapping out. The page lock will be held during allocating
the swap cluster, adding the THP into the swap cache and splitting the
THP. So in the code path other than swapping out, if the THP need to be
split, the PageSwapCache(THP) will be always false.
The swap cluster is only available for SSD, so the THP swap optimization
in this patchset has no effect for HDD.
[ying.huang@intel.com: fix two issues in THP optimize patch]
Link: http://lkml.kernel.org/r/87k25ed8zo.fsf@yhuang-dev.intel.com
[hannes@cmpxchg.org: extensive cleanups and simplifications, reduce code size]
Link: http://lkml.kernel.org/r/20170515112522.32457-2-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Signed-off-by: Johannes Weiner <hannes@cmpxchg.org>
Suggested-by: Andrew Morton <akpm@linux-foundation.org> [for config option]
Acked-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> [for changes in huge_memory.c and huge_mm.h]
Cc: Andrea Arcangeli <aarcange@redhat.com>
Cc: Ebru Akagunduz <ebru.akagunduz@gmail.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Michal Hocko <mhocko@kernel.org>
Cc: Tejun Heo <tj@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-07 01:37:18 +03:00
address_space - > nrpages - = nr ;
__mod_node_page_state ( page_pgdat ( page ) , NR_FILE_PAGES , - nr ) ;
2021-02-24 23:03:55 +03:00
__mod_lruvec_page_state ( page , NR_SWAPCACHE , - nr ) ;
mm, THP, swap: delay splitting THP during swap out
Patch series "THP swap: Delay splitting THP during swapping out", v11.
This patchset is to optimize the performance of Transparent Huge Page
(THP) swap.
Recently, the performance of the storage devices improved so fast that
we cannot saturate the disk bandwidth with single logical CPU when do
page swap out even on a high-end server machine. Because the
performance of the storage device improved faster than that of single
logical CPU. And it seems that the trend will not change in the near
future. On the other hand, the THP becomes more and more popular
because of increased memory size. So it becomes necessary to optimize
THP swap performance.
The advantages of the THP swap support include:
- Batch the swap operations for the THP to reduce lock
acquiring/releasing, including allocating/freeing the swap space,
adding/deleting to/from the swap cache, and writing/reading the swap
space, etc. This will help improve the performance of the THP swap.
- The THP swap space read/write will be 2M sequential IO. It is
particularly helpful for the swap read, which are usually 4k random
IO. This will improve the performance of the THP swap too.
- It will help the memory fragmentation, especially when the THP is
heavily used by the applications. The 2M continuous pages will be
free up after THP swapping out.
- It will improve the THP utilization on the system with the swap
turned on. Because the speed for khugepaged to collapse the normal
pages into the THP is quite slow. After the THP is split during the
swapping out, it will take quite long time for the normal pages to
collapse back into the THP after being swapped in. The high THP
utilization helps the efficiency of the page based memory management
too.
There are some concerns regarding THP swap in, mainly because possible
enlarged read/write IO size (for swap in/out) may put more overhead on
the storage device. To deal with that, the THP swap in should be turned
on only when necessary. For example, it can be selected via
"always/never/madvise" logic, to be turned on globally, turned off
globally, or turned on only for VMA with MADV_HUGEPAGE, etc.
This patchset is the first step for the THP swap support. The plan is
to delay splitting THP step by step, finally avoid splitting THP during
the THP swapping out and swap out/in the THP as a whole.
As the first step, in this patchset, the splitting huge page is delayed
from almost the first step of swapping out to after allocating the swap
space for the THP and adding the THP into the swap cache. This will
reduce lock acquiring/releasing for the locks used for the swap cache
management.
With the patchset, the swap out throughput improves 15.5% (from about
3.73GB/s to about 4.31GB/s) in the vm-scalability swap-w-seq test case
with 8 processes. The test is done on a Xeon E5 v3 system. The swap
device used is a RAM simulated PMEM (persistent memory) device. To test
the sequential swapping out, the test case creates 8 processes, which
sequentially allocate and write to the anonymous pages until the RAM and
part of the swap device is used up.
This patch (of 5):
In this patch, splitting huge page is delayed from almost the first step
of swapping out to after allocating the swap space for the THP
(Transparent Huge Page) and adding the THP into the swap cache. This
will batch the corresponding operation, thus improve THP swap out
throughput.
This is the first step for the THP swap optimization. The plan is to
delay splitting the THP step by step and avoid splitting the THP
finally.
In this patch, one swap cluster is used to hold the contents of each THP
swapped out. So, the size of the swap cluster is changed to that of the
THP (Transparent Huge Page) on x86_64 architecture (512). For other
architectures which want such THP swap optimization,
ARCH_USES_THP_SWAP_CLUSTER needs to be selected in the Kconfig file for
the architecture. In effect, this will enlarge swap cluster size by 2
times on x86_64. Which may make it harder to find a free cluster when
the swap space becomes fragmented. So that, this may reduce the
continuous swap space allocation and sequential write in theory. The
performance test in 0day shows no regressions caused by this.
In the future of THP swap optimization, some information of the swapped
out THP (such as compound map count) will be recorded in the
swap_cluster_info data structure.
The mem cgroup swap accounting functions are enhanced to support charge
or uncharge a swap cluster backing a THP as a whole.
The swap cluster allocate/free functions are added to allocate/free a
swap cluster for a THP. A fair simple algorithm is used for swap
cluster allocation, that is, only the first swap device in priority list
will be tried to allocate the swap cluster. The function will fail if
the trying is not successful, and the caller will fallback to allocate a
single swap slot instead. This works good enough for normal cases. If
the difference of the number of the free swap clusters among multiple
swap devices is significant, it is possible that some THPs are split
earlier than necessary. For example, this could be caused by big size
difference among multiple swap devices.
The swap cache functions is enhanced to support add/delete THP to/from
the swap cache as a set of (HPAGE_PMD_NR) sub-pages. This may be
enhanced in the future with multi-order radix tree. But because we will
split the THP soon during swapping out, that optimization doesn't make
much sense for this first step.
The THP splitting functions are enhanced to support to split THP in swap
cache during swapping out. The page lock will be held during allocating
the swap cluster, adding the THP into the swap cache and splitting the
THP. So in the code path other than swapping out, if the THP need to be
split, the PageSwapCache(THP) will be always false.
The swap cluster is only available for SSD, so the THP swap optimization
in this patchset has no effect for HDD.
[ying.huang@intel.com: fix two issues in THP optimize patch]
Link: http://lkml.kernel.org/r/87k25ed8zo.fsf@yhuang-dev.intel.com
[hannes@cmpxchg.org: extensive cleanups and simplifications, reduce code size]
Link: http://lkml.kernel.org/r/20170515112522.32457-2-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Signed-off-by: Johannes Weiner <hannes@cmpxchg.org>
Suggested-by: Andrew Morton <akpm@linux-foundation.org> [for config option]
Acked-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> [for changes in huge_memory.c and huge_mm.h]
Cc: Andrea Arcangeli <aarcange@redhat.com>
Cc: Ebru Akagunduz <ebru.akagunduz@gmail.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Michal Hocko <mhocko@kernel.org>
Cc: Tejun Heo <tj@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-07 01:37:18 +03:00
ADD_CACHE_INFO ( del_total , nr ) ;
2005-04-17 02:20:36 +04:00
}
/**
* add_to_swap - allocate swap space for a page
* @ page : page we want to move to swap
*
* Allocate swap space for the page and add the page to the
* swap cache . Caller needs to hold the page lock .
*/
2017-07-07 01:37:24 +03:00
int add_to_swap ( struct page * page )
2005-04-17 02:20:36 +04:00
{
swp_entry_t entry ;
int err ;
2014-01-24 03:52:54 +04:00
VM_BUG_ON_PAGE ( ! PageLocked ( page ) , page ) ;
VM_BUG_ON_PAGE ( ! PageUptodate ( page ) , page ) ;
2005-04-17 02:20:36 +04:00
mm, THP, swap: delay splitting THP during swap out
Patch series "THP swap: Delay splitting THP during swapping out", v11.
This patchset is to optimize the performance of Transparent Huge Page
(THP) swap.
Recently, the performance of the storage devices improved so fast that
we cannot saturate the disk bandwidth with single logical CPU when do
page swap out even on a high-end server machine. Because the
performance of the storage device improved faster than that of single
logical CPU. And it seems that the trend will not change in the near
future. On the other hand, the THP becomes more and more popular
because of increased memory size. So it becomes necessary to optimize
THP swap performance.
The advantages of the THP swap support include:
- Batch the swap operations for the THP to reduce lock
acquiring/releasing, including allocating/freeing the swap space,
adding/deleting to/from the swap cache, and writing/reading the swap
space, etc. This will help improve the performance of the THP swap.
- The THP swap space read/write will be 2M sequential IO. It is
particularly helpful for the swap read, which are usually 4k random
IO. This will improve the performance of the THP swap too.
- It will help the memory fragmentation, especially when the THP is
heavily used by the applications. The 2M continuous pages will be
free up after THP swapping out.
- It will improve the THP utilization on the system with the swap
turned on. Because the speed for khugepaged to collapse the normal
pages into the THP is quite slow. After the THP is split during the
swapping out, it will take quite long time for the normal pages to
collapse back into the THP after being swapped in. The high THP
utilization helps the efficiency of the page based memory management
too.
There are some concerns regarding THP swap in, mainly because possible
enlarged read/write IO size (for swap in/out) may put more overhead on
the storage device. To deal with that, the THP swap in should be turned
on only when necessary. For example, it can be selected via
"always/never/madvise" logic, to be turned on globally, turned off
globally, or turned on only for VMA with MADV_HUGEPAGE, etc.
This patchset is the first step for the THP swap support. The plan is
to delay splitting THP step by step, finally avoid splitting THP during
the THP swapping out and swap out/in the THP as a whole.
As the first step, in this patchset, the splitting huge page is delayed
from almost the first step of swapping out to after allocating the swap
space for the THP and adding the THP into the swap cache. This will
reduce lock acquiring/releasing for the locks used for the swap cache
management.
With the patchset, the swap out throughput improves 15.5% (from about
3.73GB/s to about 4.31GB/s) in the vm-scalability swap-w-seq test case
with 8 processes. The test is done on a Xeon E5 v3 system. The swap
device used is a RAM simulated PMEM (persistent memory) device. To test
the sequential swapping out, the test case creates 8 processes, which
sequentially allocate and write to the anonymous pages until the RAM and
part of the swap device is used up.
This patch (of 5):
In this patch, splitting huge page is delayed from almost the first step
of swapping out to after allocating the swap space for the THP
(Transparent Huge Page) and adding the THP into the swap cache. This
will batch the corresponding operation, thus improve THP swap out
throughput.
This is the first step for the THP swap optimization. The plan is to
delay splitting the THP step by step and avoid splitting the THP
finally.
In this patch, one swap cluster is used to hold the contents of each THP
swapped out. So, the size of the swap cluster is changed to that of the
THP (Transparent Huge Page) on x86_64 architecture (512). For other
architectures which want such THP swap optimization,
ARCH_USES_THP_SWAP_CLUSTER needs to be selected in the Kconfig file for
the architecture. In effect, this will enlarge swap cluster size by 2
times on x86_64. Which may make it harder to find a free cluster when
the swap space becomes fragmented. So that, this may reduce the
continuous swap space allocation and sequential write in theory. The
performance test in 0day shows no regressions caused by this.
In the future of THP swap optimization, some information of the swapped
out THP (such as compound map count) will be recorded in the
swap_cluster_info data structure.
The mem cgroup swap accounting functions are enhanced to support charge
or uncharge a swap cluster backing a THP as a whole.
The swap cluster allocate/free functions are added to allocate/free a
swap cluster for a THP. A fair simple algorithm is used for swap
cluster allocation, that is, only the first swap device in priority list
will be tried to allocate the swap cluster. The function will fail if
the trying is not successful, and the caller will fallback to allocate a
single swap slot instead. This works good enough for normal cases. If
the difference of the number of the free swap clusters among multiple
swap devices is significant, it is possible that some THPs are split
earlier than necessary. For example, this could be caused by big size
difference among multiple swap devices.
The swap cache functions is enhanced to support add/delete THP to/from
the swap cache as a set of (HPAGE_PMD_NR) sub-pages. This may be
enhanced in the future with multi-order radix tree. But because we will
split the THP soon during swapping out, that optimization doesn't make
much sense for this first step.
The THP splitting functions are enhanced to support to split THP in swap
cache during swapping out. The page lock will be held during allocating
the swap cluster, adding the THP into the swap cache and splitting the
THP. So in the code path other than swapping out, if the THP need to be
split, the PageSwapCache(THP) will be always false.
The swap cluster is only available for SSD, so the THP swap optimization
in this patchset has no effect for HDD.
[ying.huang@intel.com: fix two issues in THP optimize patch]
Link: http://lkml.kernel.org/r/87k25ed8zo.fsf@yhuang-dev.intel.com
[hannes@cmpxchg.org: extensive cleanups and simplifications, reduce code size]
Link: http://lkml.kernel.org/r/20170515112522.32457-2-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Signed-off-by: Johannes Weiner <hannes@cmpxchg.org>
Suggested-by: Andrew Morton <akpm@linux-foundation.org> [for config option]
Acked-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> [for changes in huge_memory.c and huge_mm.h]
Cc: Andrea Arcangeli <aarcange@redhat.com>
Cc: Ebru Akagunduz <ebru.akagunduz@gmail.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Michal Hocko <mhocko@kernel.org>
Cc: Tejun Heo <tj@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-07 01:37:18 +03:00
entry = get_swap_page ( page ) ;
2009-09-22 04:02:52 +04:00
if ( ! entry . val )
2017-07-07 01:37:24 +03:00
return 0 ;
2009-09-22 04:02:52 +04:00
/*
2017-11-27 23:46:54 +03:00
* XArray node allocations from PF_MEMALLOC contexts could
2009-09-22 04:02:52 +04:00
* completely exhaust the page allocator . __GFP_NOMEMALLOC
* stops emergency reserves from being allocated .
*
* TODO : this could cause a theoretical memory reclaim
* deadlock in the swap out path .
*/
/*
mm: support madvise(MADV_FREE)
Linux doesn't have an ability to free pages lazy while other OS already
have been supported that named by madvise(MADV_FREE).
The gain is clear that kernel can discard freed pages rather than
swapping out or OOM if memory pressure happens.
Without memory pressure, freed pages would be reused by userspace
without another additional overhead(ex, page fault + allocation +
zeroing).
Jason Evans said:
: Facebook has been using MAP_UNINITIALIZED
: (https://lkml.org/lkml/2012/1/18/308) in some of its applications for
: several years, but there are operational costs to maintaining this
: out-of-tree in our kernel and in jemalloc, and we are anxious to retire it
: in favor of MADV_FREE. When we first enabled MAP_UNINITIALIZED it
: increased throughput for much of our workload by ~5%, and although the
: benefit has decreased using newer hardware and kernels, there is still
: enough benefit that we cannot reasonably retire it without a replacement.
:
: Aside from Facebook operations, there are numerous broadly used
: applications that would benefit from MADV_FREE. The ones that immediately
: come to mind are redis, varnish, and MariaDB. I don't have much insight
: into Android internals and development process, but I would hope to see
: MADV_FREE support eventually end up there as well to benefit applications
: linked with the integrated jemalloc.
:
: jemalloc will use MADV_FREE once it becomes available in the Linux kernel.
: In fact, jemalloc already uses MADV_FREE or equivalent everywhere it's
: available: *BSD, OS X, Windows, and Solaris -- every platform except Linux
: (and AIX, but I'm not sure it even compiles on AIX). The lack of
: MADV_FREE on Linux forced me down a long series of increasingly
: sophisticated heuristics for madvise() volume reduction, and even so this
: remains a common performance issue for people using jemalloc on Linux.
: Please integrate MADV_FREE; many people will benefit substantially.
How it works:
When madvise syscall is called, VM clears dirty bit of ptes of the
range. If memory pressure happens, VM checks dirty bit of page table
and if it found still "clean", it means it's a "lazyfree pages" so VM
could discard the page instead of swapping out. Once there was store
operation for the page before VM peek a page to reclaim, dirty bit is
set so VM can swap out the page instead of discarding.
One thing we should notice is that basically, MADV_FREE relies on dirty
bit in page table entry to decide whether VM allows to discard the page
or not. IOW, if page table entry includes marked dirty bit, VM
shouldn't discard the page.
However, as a example, if swap-in by read fault happens, page table
entry doesn't have dirty bit so MADV_FREE could discard the page
wrongly.
For avoiding the problem, MADV_FREE did more checks with PageDirty and
PageSwapCache. It worked out because swapped-in page lives on swap
cache and since it is evicted from the swap cache, the page has PG_dirty
flag. So both page flags check effectively prevent wrong discarding by
MADV_FREE.
However, a problem in above logic is that swapped-in page has PG_dirty
still after they are removed from swap cache so VM cannot consider the
page as freeable any more even if madvise_free is called in future.
Look at below example for detail.
ptr = malloc();
memset(ptr);
..
..
.. heavy memory pressure so all of pages are swapped out
..
..
var = *ptr; -> a page swapped-in and could be removed from
swapcache. Then, page table doesn't mark
dirty bit and page descriptor includes PG_dirty
..
..
madvise_free(ptr); -> It doesn't clear PG_dirty of the page.
..
..
..
.. heavy memory pressure again.
.. In this time, VM cannot discard the page because the page
.. has *PG_dirty*
To solve the problem, this patch clears PG_dirty if only the page is
owned exclusively by current process when madvise is called because
PG_dirty represents ptes's dirtiness in several processes so we could
clear it only if we own it exclusively.
Firstly, heavy users would be general allocators(ex, jemalloc, tcmalloc
and hope glibc supports it) and jemalloc/tcmalloc already have supported
the feature for other OS(ex, FreeBSD)
barrios@blaptop:~/benchmark/ebizzy$ lscpu
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Byte Order: Little Endian
CPU(s): 12
On-line CPU(s) list: 0-11
Thread(s) per core: 1
Core(s) per socket: 1
Socket(s): 12
NUMA node(s): 1
Vendor ID: GenuineIntel
CPU family: 6
Model: 2
Stepping: 3
CPU MHz: 3200.185
BogoMIPS: 6400.53
Virtualization: VT-x
Hypervisor vendor: KVM
Virtualization type: full
L1d cache: 32K
L1i cache: 32K
L2 cache: 4096K
NUMA node0 CPU(s): 0-11
ebizzy benchmark(./ebizzy -S 10 -n 512)
Higher avg is better.
vanilla-jemalloc MADV_free-jemalloc
1 thread
records: 10 records: 10
avg: 2961.90 avg: 12069.70
std: 71.96(2.43%) std: 186.68(1.55%)
max: 3070.00 max: 12385.00
min: 2796.00 min: 11746.00
2 thread
records: 10 records: 10
avg: 5020.00 avg: 17827.00
std: 264.87(5.28%) std: 358.52(2.01%)
max: 5244.00 max: 18760.00
min: 4251.00 min: 17382.00
4 thread
records: 10 records: 10
avg: 8988.80 avg: 27930.80
std: 1175.33(13.08%) std: 3317.33(11.88%)
max: 9508.00 max: 30879.00
min: 5477.00 min: 21024.00
8 thread
records: 10 records: 10
avg: 13036.50 avg: 33739.40
std: 170.67(1.31%) std: 5146.22(15.25%)
max: 13371.00 max: 40572.00
min: 12785.00 min: 24088.00
16 thread
records: 10 records: 10
avg: 11092.40 avg: 31424.20
std: 710.60(6.41%) std: 3763.89(11.98%)
max: 12446.00 max: 36635.00
min: 9949.00 min: 25669.00
32 thread
records: 10 records: 10
avg: 11067.00 avg: 34495.80
std: 971.06(8.77%) std: 2721.36(7.89%)
max: 12010.00 max: 38598.00
min: 9002.00 min: 30636.00
In summary, MADV_FREE is about much faster than MADV_DONTNEED.
This patch (of 12):
Add core MADV_FREE implementation.
[akpm@linux-foundation.org: small cleanups]
Signed-off-by: Minchan Kim <minchan@kernel.org>
Acked-by: Michal Hocko <mhocko@suse.com>
Acked-by: Hugh Dickins <hughd@google.com>
Cc: Mika Penttil <mika.penttila@nextfour.com>
Cc: Michael Kerrisk <mtk.manpages@gmail.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Mel Gorman <mgorman@suse.de>
Cc: KOSAKI Motohiro <kosaki.motohiro@jp.fujitsu.com>
Cc: Jason Evans <je@fb.com>
Cc: Daniel Micay <danielmicay@gmail.com>
Cc: "Kirill A. Shutemov" <kirill@shutemov.name>
Cc: Shaohua Li <shli@kernel.org>
Cc: <yalin.wang2010@gmail.com>
Cc: Andy Lutomirski <luto@amacapital.net>
Cc: "James E.J. Bottomley" <jejb@parisc-linux.org>
Cc: "Kirill A. Shutemov" <kirill@shutemov.name>
Cc: "Shaohua Li" <shli@kernel.org>
Cc: Andrea Arcangeli <aarcange@redhat.com>
Cc: Arnd Bergmann <arnd@arndb.de>
Cc: Benjamin Herrenschmidt <benh@kernel.crashing.org>
Cc: Catalin Marinas <catalin.marinas@arm.com>
Cc: Chen Gang <gang.chen.5i5j@gmail.com>
Cc: Chris Zankel <chris@zankel.net>
Cc: Darrick J. Wong <darrick.wong@oracle.com>
Cc: David S. Miller <davem@davemloft.net>
Cc: Helge Deller <deller@gmx.de>
Cc: Ivan Kokshaysky <ink@jurassic.park.msu.ru>
Cc: Matt Turner <mattst88@gmail.com>
Cc: Max Filippov <jcmvbkbc@gmail.com>
Cc: Ralf Baechle <ralf@linux-mips.org>
Cc: Richard Henderson <rth@twiddle.net>
Cc: Roland Dreier <roland@kernel.org>
Cc: Russell King <rmk@arm.linux.org.uk>
Cc: Shaohua Li <shli@kernel.org>
Cc: Will Deacon <will.deacon@arm.com>
Cc: Wu Fengguang <fengguang.wu@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2016-01-16 03:54:53 +03:00
* Add it to the swap cache .
2009-09-22 04:02:52 +04:00
*/
err = add_to_swap_cache ( page , entry ,
2020-08-12 04:30:47 +03:00
__GFP_HIGH | __GFP_NOMEMALLOC | __GFP_NOWARN , NULL ) ;
mm, THP, swap: delay splitting THP during swap out
Patch series "THP swap: Delay splitting THP during swapping out", v11.
This patchset is to optimize the performance of Transparent Huge Page
(THP) swap.
Recently, the performance of the storage devices improved so fast that
we cannot saturate the disk bandwidth with single logical CPU when do
page swap out even on a high-end server machine. Because the
performance of the storage device improved faster than that of single
logical CPU. And it seems that the trend will not change in the near
future. On the other hand, the THP becomes more and more popular
because of increased memory size. So it becomes necessary to optimize
THP swap performance.
The advantages of the THP swap support include:
- Batch the swap operations for the THP to reduce lock
acquiring/releasing, including allocating/freeing the swap space,
adding/deleting to/from the swap cache, and writing/reading the swap
space, etc. This will help improve the performance of the THP swap.
- The THP swap space read/write will be 2M sequential IO. It is
particularly helpful for the swap read, which are usually 4k random
IO. This will improve the performance of the THP swap too.
- It will help the memory fragmentation, especially when the THP is
heavily used by the applications. The 2M continuous pages will be
free up after THP swapping out.
- It will improve the THP utilization on the system with the swap
turned on. Because the speed for khugepaged to collapse the normal
pages into the THP is quite slow. After the THP is split during the
swapping out, it will take quite long time for the normal pages to
collapse back into the THP after being swapped in. The high THP
utilization helps the efficiency of the page based memory management
too.
There are some concerns regarding THP swap in, mainly because possible
enlarged read/write IO size (for swap in/out) may put more overhead on
the storage device. To deal with that, the THP swap in should be turned
on only when necessary. For example, it can be selected via
"always/never/madvise" logic, to be turned on globally, turned off
globally, or turned on only for VMA with MADV_HUGEPAGE, etc.
This patchset is the first step for the THP swap support. The plan is
to delay splitting THP step by step, finally avoid splitting THP during
the THP swapping out and swap out/in the THP as a whole.
As the first step, in this patchset, the splitting huge page is delayed
from almost the first step of swapping out to after allocating the swap
space for the THP and adding the THP into the swap cache. This will
reduce lock acquiring/releasing for the locks used for the swap cache
management.
With the patchset, the swap out throughput improves 15.5% (from about
3.73GB/s to about 4.31GB/s) in the vm-scalability swap-w-seq test case
with 8 processes. The test is done on a Xeon E5 v3 system. The swap
device used is a RAM simulated PMEM (persistent memory) device. To test
the sequential swapping out, the test case creates 8 processes, which
sequentially allocate and write to the anonymous pages until the RAM and
part of the swap device is used up.
This patch (of 5):
In this patch, splitting huge page is delayed from almost the first step
of swapping out to after allocating the swap space for the THP
(Transparent Huge Page) and adding the THP into the swap cache. This
will batch the corresponding operation, thus improve THP swap out
throughput.
This is the first step for the THP swap optimization. The plan is to
delay splitting the THP step by step and avoid splitting the THP
finally.
In this patch, one swap cluster is used to hold the contents of each THP
swapped out. So, the size of the swap cluster is changed to that of the
THP (Transparent Huge Page) on x86_64 architecture (512). For other
architectures which want such THP swap optimization,
ARCH_USES_THP_SWAP_CLUSTER needs to be selected in the Kconfig file for
the architecture. In effect, this will enlarge swap cluster size by 2
times on x86_64. Which may make it harder to find a free cluster when
the swap space becomes fragmented. So that, this may reduce the
continuous swap space allocation and sequential write in theory. The
performance test in 0day shows no regressions caused by this.
In the future of THP swap optimization, some information of the swapped
out THP (such as compound map count) will be recorded in the
swap_cluster_info data structure.
The mem cgroup swap accounting functions are enhanced to support charge
or uncharge a swap cluster backing a THP as a whole.
The swap cluster allocate/free functions are added to allocate/free a
swap cluster for a THP. A fair simple algorithm is used for swap
cluster allocation, that is, only the first swap device in priority list
will be tried to allocate the swap cluster. The function will fail if
the trying is not successful, and the caller will fallback to allocate a
single swap slot instead. This works good enough for normal cases. If
the difference of the number of the free swap clusters among multiple
swap devices is significant, it is possible that some THPs are split
earlier than necessary. For example, this could be caused by big size
difference among multiple swap devices.
The swap cache functions is enhanced to support add/delete THP to/from
the swap cache as a set of (HPAGE_PMD_NR) sub-pages. This may be
enhanced in the future with multi-order radix tree. But because we will
split the THP soon during swapping out, that optimization doesn't make
much sense for this first step.
The THP splitting functions are enhanced to support to split THP in swap
cache during swapping out. The page lock will be held during allocating
the swap cluster, adding the THP into the swap cache and splitting the
THP. So in the code path other than swapping out, if the THP need to be
split, the PageSwapCache(THP) will be always false.
The swap cluster is only available for SSD, so the THP swap optimization
in this patchset has no effect for HDD.
[ying.huang@intel.com: fix two issues in THP optimize patch]
Link: http://lkml.kernel.org/r/87k25ed8zo.fsf@yhuang-dev.intel.com
[hannes@cmpxchg.org: extensive cleanups and simplifications, reduce code size]
Link: http://lkml.kernel.org/r/20170515112522.32457-2-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Signed-off-by: Johannes Weiner <hannes@cmpxchg.org>
Suggested-by: Andrew Morton <akpm@linux-foundation.org> [for config option]
Acked-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> [for changes in huge_memory.c and huge_mm.h]
Cc: Andrea Arcangeli <aarcange@redhat.com>
Cc: Ebru Akagunduz <ebru.akagunduz@gmail.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Michal Hocko <mhocko@kernel.org>
Cc: Tejun Heo <tj@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-07 01:37:18 +03:00
if ( err )
2005-05-01 19:58:37 +04:00
/*
2009-09-22 04:02:52 +04:00
* add_to_swap_cache ( ) doesn ' t return - EEXIST , so we can safely
* clear SWAP_HAS_CACHE flag .
2005-04-17 02:20:36 +04:00
*/
2017-07-07 01:37:24 +03:00
goto fail ;
2017-10-04 02:15:32 +03:00
/*
* Normally the page will be dirtied in unmap because its pte should be
2020-10-16 06:09:58 +03:00
* dirty . A special case is MADV_FREE page . The page ' s pte could have
2017-10-04 02:15:32 +03:00
* dirty bit cleared but the page ' s SwapBacked bit is still set because
* clearing the dirty bit and SwapBacked bit has no lock protected . For
* such page , unmap will not set dirty bit for it , so page reclaim will
* not write the page out . This can cause data corruption when the page
* is swap in later . Always setting the dirty bit for the page solves
* the problem .
*/
set_page_dirty ( page ) ;
mm, THP, swap: delay splitting THP during swap out
Patch series "THP swap: Delay splitting THP during swapping out", v11.
This patchset is to optimize the performance of Transparent Huge Page
(THP) swap.
Recently, the performance of the storage devices improved so fast that
we cannot saturate the disk bandwidth with single logical CPU when do
page swap out even on a high-end server machine. Because the
performance of the storage device improved faster than that of single
logical CPU. And it seems that the trend will not change in the near
future. On the other hand, the THP becomes more and more popular
because of increased memory size. So it becomes necessary to optimize
THP swap performance.
The advantages of the THP swap support include:
- Batch the swap operations for the THP to reduce lock
acquiring/releasing, including allocating/freeing the swap space,
adding/deleting to/from the swap cache, and writing/reading the swap
space, etc. This will help improve the performance of the THP swap.
- The THP swap space read/write will be 2M sequential IO. It is
particularly helpful for the swap read, which are usually 4k random
IO. This will improve the performance of the THP swap too.
- It will help the memory fragmentation, especially when the THP is
heavily used by the applications. The 2M continuous pages will be
free up after THP swapping out.
- It will improve the THP utilization on the system with the swap
turned on. Because the speed for khugepaged to collapse the normal
pages into the THP is quite slow. After the THP is split during the
swapping out, it will take quite long time for the normal pages to
collapse back into the THP after being swapped in. The high THP
utilization helps the efficiency of the page based memory management
too.
There are some concerns regarding THP swap in, mainly because possible
enlarged read/write IO size (for swap in/out) may put more overhead on
the storage device. To deal with that, the THP swap in should be turned
on only when necessary. For example, it can be selected via
"always/never/madvise" logic, to be turned on globally, turned off
globally, or turned on only for VMA with MADV_HUGEPAGE, etc.
This patchset is the first step for the THP swap support. The plan is
to delay splitting THP step by step, finally avoid splitting THP during
the THP swapping out and swap out/in the THP as a whole.
As the first step, in this patchset, the splitting huge page is delayed
from almost the first step of swapping out to after allocating the swap
space for the THP and adding the THP into the swap cache. This will
reduce lock acquiring/releasing for the locks used for the swap cache
management.
With the patchset, the swap out throughput improves 15.5% (from about
3.73GB/s to about 4.31GB/s) in the vm-scalability swap-w-seq test case
with 8 processes. The test is done on a Xeon E5 v3 system. The swap
device used is a RAM simulated PMEM (persistent memory) device. To test
the sequential swapping out, the test case creates 8 processes, which
sequentially allocate and write to the anonymous pages until the RAM and
part of the swap device is used up.
This patch (of 5):
In this patch, splitting huge page is delayed from almost the first step
of swapping out to after allocating the swap space for the THP
(Transparent Huge Page) and adding the THP into the swap cache. This
will batch the corresponding operation, thus improve THP swap out
throughput.
This is the first step for the THP swap optimization. The plan is to
delay splitting the THP step by step and avoid splitting the THP
finally.
In this patch, one swap cluster is used to hold the contents of each THP
swapped out. So, the size of the swap cluster is changed to that of the
THP (Transparent Huge Page) on x86_64 architecture (512). For other
architectures which want such THP swap optimization,
ARCH_USES_THP_SWAP_CLUSTER needs to be selected in the Kconfig file for
the architecture. In effect, this will enlarge swap cluster size by 2
times on x86_64. Which may make it harder to find a free cluster when
the swap space becomes fragmented. So that, this may reduce the
continuous swap space allocation and sequential write in theory. The
performance test in 0day shows no regressions caused by this.
In the future of THP swap optimization, some information of the swapped
out THP (such as compound map count) will be recorded in the
swap_cluster_info data structure.
The mem cgroup swap accounting functions are enhanced to support charge
or uncharge a swap cluster backing a THP as a whole.
The swap cluster allocate/free functions are added to allocate/free a
swap cluster for a THP. A fair simple algorithm is used for swap
cluster allocation, that is, only the first swap device in priority list
will be tried to allocate the swap cluster. The function will fail if
the trying is not successful, and the caller will fallback to allocate a
single swap slot instead. This works good enough for normal cases. If
the difference of the number of the free swap clusters among multiple
swap devices is significant, it is possible that some THPs are split
earlier than necessary. For example, this could be caused by big size
difference among multiple swap devices.
The swap cache functions is enhanced to support add/delete THP to/from
the swap cache as a set of (HPAGE_PMD_NR) sub-pages. This may be
enhanced in the future with multi-order radix tree. But because we will
split the THP soon during swapping out, that optimization doesn't make
much sense for this first step.
The THP splitting functions are enhanced to support to split THP in swap
cache during swapping out. The page lock will be held during allocating
the swap cluster, adding the THP into the swap cache and splitting the
THP. So in the code path other than swapping out, if the THP need to be
split, the PageSwapCache(THP) will be always false.
The swap cluster is only available for SSD, so the THP swap optimization
in this patchset has no effect for HDD.
[ying.huang@intel.com: fix two issues in THP optimize patch]
Link: http://lkml.kernel.org/r/87k25ed8zo.fsf@yhuang-dev.intel.com
[hannes@cmpxchg.org: extensive cleanups and simplifications, reduce code size]
Link: http://lkml.kernel.org/r/20170515112522.32457-2-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Signed-off-by: Johannes Weiner <hannes@cmpxchg.org>
Suggested-by: Andrew Morton <akpm@linux-foundation.org> [for config option]
Acked-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> [for changes in huge_memory.c and huge_mm.h]
Cc: Andrea Arcangeli <aarcange@redhat.com>
Cc: Ebru Akagunduz <ebru.akagunduz@gmail.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Michal Hocko <mhocko@kernel.org>
Cc: Tejun Heo <tj@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-07 01:37:18 +03:00
return 1 ;
fail :
2017-07-07 01:37:24 +03:00
put_swap_page ( page , entry ) ;
mm, THP, swap: delay splitting THP during swap out
Patch series "THP swap: Delay splitting THP during swapping out", v11.
This patchset is to optimize the performance of Transparent Huge Page
(THP) swap.
Recently, the performance of the storage devices improved so fast that
we cannot saturate the disk bandwidth with single logical CPU when do
page swap out even on a high-end server machine. Because the
performance of the storage device improved faster than that of single
logical CPU. And it seems that the trend will not change in the near
future. On the other hand, the THP becomes more and more popular
because of increased memory size. So it becomes necessary to optimize
THP swap performance.
The advantages of the THP swap support include:
- Batch the swap operations for the THP to reduce lock
acquiring/releasing, including allocating/freeing the swap space,
adding/deleting to/from the swap cache, and writing/reading the swap
space, etc. This will help improve the performance of the THP swap.
- The THP swap space read/write will be 2M sequential IO. It is
particularly helpful for the swap read, which are usually 4k random
IO. This will improve the performance of the THP swap too.
- It will help the memory fragmentation, especially when the THP is
heavily used by the applications. The 2M continuous pages will be
free up after THP swapping out.
- It will improve the THP utilization on the system with the swap
turned on. Because the speed for khugepaged to collapse the normal
pages into the THP is quite slow. After the THP is split during the
swapping out, it will take quite long time for the normal pages to
collapse back into the THP after being swapped in. The high THP
utilization helps the efficiency of the page based memory management
too.
There are some concerns regarding THP swap in, mainly because possible
enlarged read/write IO size (for swap in/out) may put more overhead on
the storage device. To deal with that, the THP swap in should be turned
on only when necessary. For example, it can be selected via
"always/never/madvise" logic, to be turned on globally, turned off
globally, or turned on only for VMA with MADV_HUGEPAGE, etc.
This patchset is the first step for the THP swap support. The plan is
to delay splitting THP step by step, finally avoid splitting THP during
the THP swapping out and swap out/in the THP as a whole.
As the first step, in this patchset, the splitting huge page is delayed
from almost the first step of swapping out to after allocating the swap
space for the THP and adding the THP into the swap cache. This will
reduce lock acquiring/releasing for the locks used for the swap cache
management.
With the patchset, the swap out throughput improves 15.5% (from about
3.73GB/s to about 4.31GB/s) in the vm-scalability swap-w-seq test case
with 8 processes. The test is done on a Xeon E5 v3 system. The swap
device used is a RAM simulated PMEM (persistent memory) device. To test
the sequential swapping out, the test case creates 8 processes, which
sequentially allocate and write to the anonymous pages until the RAM and
part of the swap device is used up.
This patch (of 5):
In this patch, splitting huge page is delayed from almost the first step
of swapping out to after allocating the swap space for the THP
(Transparent Huge Page) and adding the THP into the swap cache. This
will batch the corresponding operation, thus improve THP swap out
throughput.
This is the first step for the THP swap optimization. The plan is to
delay splitting the THP step by step and avoid splitting the THP
finally.
In this patch, one swap cluster is used to hold the contents of each THP
swapped out. So, the size of the swap cluster is changed to that of the
THP (Transparent Huge Page) on x86_64 architecture (512). For other
architectures which want such THP swap optimization,
ARCH_USES_THP_SWAP_CLUSTER needs to be selected in the Kconfig file for
the architecture. In effect, this will enlarge swap cluster size by 2
times on x86_64. Which may make it harder to find a free cluster when
the swap space becomes fragmented. So that, this may reduce the
continuous swap space allocation and sequential write in theory. The
performance test in 0day shows no regressions caused by this.
In the future of THP swap optimization, some information of the swapped
out THP (such as compound map count) will be recorded in the
swap_cluster_info data structure.
The mem cgroup swap accounting functions are enhanced to support charge
or uncharge a swap cluster backing a THP as a whole.
The swap cluster allocate/free functions are added to allocate/free a
swap cluster for a THP. A fair simple algorithm is used for swap
cluster allocation, that is, only the first swap device in priority list
will be tried to allocate the swap cluster. The function will fail if
the trying is not successful, and the caller will fallback to allocate a
single swap slot instead. This works good enough for normal cases. If
the difference of the number of the free swap clusters among multiple
swap devices is significant, it is possible that some THPs are split
earlier than necessary. For example, this could be caused by big size
difference among multiple swap devices.
The swap cache functions is enhanced to support add/delete THP to/from
the swap cache as a set of (HPAGE_PMD_NR) sub-pages. This may be
enhanced in the future with multi-order radix tree. But because we will
split the THP soon during swapping out, that optimization doesn't make
much sense for this first step.
The THP splitting functions are enhanced to support to split THP in swap
cache during swapping out. The page lock will be held during allocating
the swap cluster, adding the THP into the swap cache and splitting the
THP. So in the code path other than swapping out, if the THP need to be
split, the PageSwapCache(THP) will be always false.
The swap cluster is only available for SSD, so the THP swap optimization
in this patchset has no effect for HDD.
[ying.huang@intel.com: fix two issues in THP optimize patch]
Link: http://lkml.kernel.org/r/87k25ed8zo.fsf@yhuang-dev.intel.com
[hannes@cmpxchg.org: extensive cleanups and simplifications, reduce code size]
Link: http://lkml.kernel.org/r/20170515112522.32457-2-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Signed-off-by: Johannes Weiner <hannes@cmpxchg.org>
Suggested-by: Andrew Morton <akpm@linux-foundation.org> [for config option]
Acked-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> [for changes in huge_memory.c and huge_mm.h]
Cc: Andrea Arcangeli <aarcange@redhat.com>
Cc: Ebru Akagunduz <ebru.akagunduz@gmail.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Michal Hocko <mhocko@kernel.org>
Cc: Tejun Heo <tj@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-07 01:37:18 +03:00
return 0 ;
2005-04-17 02:20:36 +04:00
}
/*
* This must be called only on pages that have
* been verified to be in the swap cache and locked .
* It will never put the page into the free list ,
* the caller has a reference on the page .
*/
void delete_from_swap_cache ( struct page * page )
{
2017-11-29 16:32:39 +03:00
swp_entry_t entry = { . val = page_private ( page ) } ;
struct address_space * address_space = swap_address_space ( entry ) ;
2005-04-17 02:20:36 +04:00
2018-04-11 02:36:56 +03:00
xa_lock_irq ( & address_space - > i_pages ) ;
2020-08-12 04:30:47 +03:00
__delete_from_swap_cache ( page , entry , NULL ) ;
2018-04-11 02:36:56 +03:00
xa_unlock_irq ( & address_space - > i_pages ) ;
2005-04-17 02:20:36 +04:00
2017-07-07 01:37:21 +03:00
put_swap_page ( page , entry ) ;
2020-08-15 03:30:37 +03:00
page_ref_sub ( page , thp_nr_pages ( page ) ) ;
2005-04-17 02:20:36 +04:00
}
2020-08-12 04:30:47 +03:00
void clear_shadow_from_swap_cache ( int type , unsigned long begin ,
unsigned long end )
{
unsigned long curr = begin ;
void * old ;
for ( ; ; ) {
swp_entry_t entry = swp_entry ( type , curr ) ;
struct address_space * address_space = swap_address_space ( entry ) ;
XA_STATE ( xas , & address_space - > i_pages , curr ) ;
xa_lock_irq ( & address_space - > i_pages ) ;
xas_for_each ( & xas , old , end ) {
if ( ! xa_is_value ( old ) )
continue ;
xas_store ( & xas , NULL ) ;
}
xa_unlock_irq ( & address_space - > i_pages ) ;
/* search the next swapcache until we meet end */
curr > > = SWAP_ADDRESS_SPACE_SHIFT ;
curr + + ;
curr < < = SWAP_ADDRESS_SPACE_SHIFT ;
if ( curr > end )
break ;
}
}
2005-04-17 02:20:36 +04:00
/*
* If we are the only user , then try to free up the swap cache .
*
* Its ok to check for PageSwapCache without the page lock
2009-01-07 01:39:36 +03:00
* here because we are going to recheck again inside
* try_to_free_swap ( ) _with_ the lock .
2005-04-17 02:20:36 +04:00
* - Marcelo
*/
mm: free idle swap cache page after COW
With commit 09854ba94c6a ("mm: do_wp_page() simplification"), after COW,
the idle swap cache page (neither the page nor the corresponding swap
entry is mapped by any process) will be left in the LRU list, even if it's
in the active list or the head of the inactive list. So, the page
reclaimer may take quite some overhead to reclaim these actually unused
pages.
To help the page reclaiming, in this patch, after COW, the idle swap cache
page will be tried to be freed. To avoid to introduce much overhead to
the hot COW code path,
a) there's almost zero overhead for non-swap case via checking
PageSwapCache() firstly.
b) the page lock is acquired via trylock only.
To test the patch, we used pmbench memory accessing benchmark with
working-set larger than available memory on a 2-socket Intel server with a
NVMe SSD as swap device. Test results shows that the pmbench score
increases up to 23.8% with the decreased size of swap cache and swapin
throughput.
Link: https://lkml.kernel.org/r/20210601053143.1380078-1-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Suggested-by: Johannes Weiner <hannes@cmpxchg.org> [use free_swap_cache()]
Acked-by: Johannes Weiner <hannes@cmpxchg.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Matthew Wilcox <willy@infradead.org>
Cc: Peter Xu <peterx@redhat.com>
Cc: Mel Gorman <mgorman@suse.de>
Cc: Rik van Riel <riel@surriel.com>
Cc: Andrea Arcangeli <aarcange@redhat.com>
Cc: Michal Hocko <mhocko@kernel.org>
Cc: Dave Hansen <dave.hansen@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2021-06-29 05:37:12 +03:00
void free_swap_cache ( struct page * page )
2005-04-17 02:20:36 +04:00
{
2009-01-07 01:39:36 +03:00
if ( PageSwapCache ( page ) & & ! page_mapped ( page ) & & trylock_page ( page ) ) {
try_to_free_swap ( page ) ;
2005-04-17 02:20:36 +04:00
unlock_page ( page ) ;
}
}
/*
* Perform a free_page ( ) , also freeing any swap cache associated with
2005-10-30 04:16:41 +03:00
* this page if it is the last user of the page .
2005-04-17 02:20:36 +04:00
*/
void free_page_and_swap_cache ( struct page * page )
{
free_swap_cache ( page ) ;
2016-10-08 03:00:08 +03:00
if ( ! is_huge_zero_page ( page ) )
mm: thp: broken page count after commit aa88b68c3b1d
Christian Borntraeger reported a kernel panic after corrupt page counts,
and it turned out to be a regression introduced with commit aa88b68c3b1d
("thp: keep huge zero page pinned until tlb flush"), at least on s390.
put_huge_zero_page() was moved over from zap_huge_pmd() to
release_pages(), and it was replaced by tlb_remove_page(). However,
release_pages() might not always be triggered by (the arch-specific)
tlb_remove_page().
On s390 we call free_page_and_swap_cache() from tlb_remove_page(), and
not tlb_flush_mmu() -> free_pages_and_swap_cache() like the generic
version, because we don't use the MMU-gather logic. Although both
functions have very similar names, they are doing very unsimilar things,
in particular free_page_xxx is just doing a put_page(), while
free_pages_xxx calls release_pages().
This of course results in very harmful put_page()s on the huge zero
page, on architectures where tlb_remove_page() is implemented in this
way. It seems to affect only s390 and sh, but sh doesn't have THP
support, so the problem (currently) probably only exists on s390.
The following quick hack fixed the issue:
Link: http://lkml.kernel.org/r/20160602172141.75c006a9@thinkpad
Signed-off-by: Gerald Schaefer <gerald.schaefer@de.ibm.com>
Reported-by: Christian Borntraeger <borntraeger@de.ibm.com>
Tested-by: Christian Borntraeger <borntraeger@de.ibm.com>
Cc: "Kirill A. Shutemov" <kirill@shutemov.name>
Cc: Andrea Arcangeli <aarcange@redhat.com>
Cc: "Aneesh Kumar K.V" <aneesh.kumar@linux.vnet.ibm.com>
Cc: Mel Gorman <mgorman@techsingularity.net>
Cc: Hugh Dickins <hughd@google.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Dave Hansen <dave.hansen@intel.com>
Cc: Vlastimil Babka <vbabka@suse.cz>
Cc: Martin Schwidefsky <schwidefsky@de.ibm.com>
Cc: Heiko Carstens <heiko.carstens@de.ibm.com>
Cc: <stable@vger.kernel.org> [4.6.x]
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2016-06-09 01:33:50 +03:00
put_page ( page ) ;
2005-04-17 02:20:36 +04:00
}
/*
* Passed an array of pages , drop them all from swapcache and then release
* them . They are removed from the LRU and freed if this is their last use .
*/
void free_pages_and_swap_cache ( struct page * * pages , int nr )
{
struct page * * pagep = pages ;
2014-10-10 02:28:52 +04:00
int i ;
2005-04-17 02:20:36 +04:00
lru_add_drain ( ) ;
2014-10-10 02:28:52 +04:00
for ( i = 0 ; i < nr ; i + + )
free_swap_cache ( pagep [ i ] ) ;
2017-11-16 04:37:55 +03:00
release_pages ( pagep , nr ) ;
2005-04-17 02:20:36 +04:00
}
2018-04-06 02:23:42 +03:00
static inline bool swap_use_vma_readahead ( void )
{
return READ_ONCE ( enable_vma_readahead ) & & ! atomic_read ( & nr_rotate_swap ) ;
}
2005-04-17 02:20:36 +04:00
/*
* Lookup a swap entry in the swap cache . A found page will be returned
* unlocked and with its refcount incremented - we rely on the kernel
* lock getting page table operations atomic even if we drop the page
* lock before returning .
*/
mm, swap: VMA based swap readahead
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory. And the different tasks in the system may have different access
patterns, which makes the global space locality estimation incorrect.
In this patch, when page fault occurs, the virtual pages near the fault
address will be readahead instead of the swap slots near the fault swap
slot in swap device. This avoid to readahead the unrelated swap slots.
At the same time, the swap readahead is changed to work on per-VMA from
globally. So that the different access patterns of the different VMAs
could be distinguished, and the different readahead policy could be
applied accordingly. The original core readahead detection and scaling
algorithm is reused, because it is an effect algorithm to detect the
space locality.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device:
NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:36 +03:00
struct page * lookup_swap_cache ( swp_entry_t entry , struct vm_area_struct * vma ,
unsigned long addr )
2005-04-17 02:20:36 +04:00
{
struct page * page ;
mm, swap: fix race between swapoff and some swap operations
When swapin is performed, after getting the swap entry information from
the page table, system will swap in the swap entry, without any lock held
to prevent the swap device from being swapoff. This may cause the race
like below,
CPU 1 CPU 2
----- -----
do_swap_page
swapin_readahead
__read_swap_cache_async
swapoff swapcache_prepare
p->swap_map = NULL __swap_duplicate
p->swap_map[?] /* !!! NULL pointer access */
Because swapoff is usually done when system shutdown only, the race may
not hit many people in practice. But it is still a race need to be fixed.
To fix the race, get_swap_device() is added to check whether the specified
swap entry is valid in its swap device. If so, it will keep the swap
entry valid via preventing the swap device from being swapoff, until
put_swap_device() is called.
Because swapoff() is very rare code path, to make the normal path runs as
fast as possible, rcu_read_lock/unlock() and synchronize_rcu() instead of
reference count is used to implement get/put_swap_device(). >From
get_swap_device() to put_swap_device(), RCU reader side is locked, so
synchronize_rcu() in swapoff() will wait until put_swap_device() is
called.
In addition to swap_map, cluster_info, etc. data structure in the struct
swap_info_struct, the swap cache radix tree will be freed after swapoff,
so this patch fixes the race between swap cache looking up and swapoff
too.
Races between some other swap cache usages and swapoff are fixed too via
calling synchronize_rcu() between clearing PageSwapCache() and freeing
swap cache data structure.
Another possible method to fix this is to use preempt_off() +
stop_machine() to prevent the swap device from being swapoff when its data
structure is being accessed. The overhead in hot-path of both methods is
similar. The advantages of RCU based method are,
1. stop_machine() may disturb the normal execution code path on other
CPUs.
2. File cache uses RCU to protect its radix tree. If the similar
mechanism is used for swap cache too, it is easier to share code
between them.
3. RCU is used to protect swap cache in total_swapcache_pages() and
exit_swap_address_space() already. The two mechanisms can be
merged to simplify the logic.
Link: http://lkml.kernel.org/r/20190522015423.14418-1-ying.huang@intel.com
Fixes: 235b62176712 ("mm/swap: add cluster lock")
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Reviewed-by: Andrea Parri <andrea.parri@amarulasolutions.com>
Not-nacked-by: Hugh Dickins <hughd@google.com>
Cc: Andrea Arcangeli <aarcange@redhat.com>
Cc: Paul E. McKenney <paulmck@linux.vnet.ibm.com>
Cc: Daniel Jordan <daniel.m.jordan@oracle.com>
Cc: Michal Hocko <mhocko@suse.com>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Tim Chen <tim.c.chen@linux.intel.com>
Cc: Mel Gorman <mgorman@techsingularity.net>
Cc: Jérôme Glisse <jglisse@redhat.com>
Cc: Yang Shi <yang.shi@linux.alibaba.com>
Cc: David Rientjes <rientjes@google.com>
Cc: Rik van Riel <riel@redhat.com>
Cc: Jan Kara <jack@suse.cz>
Cc: Dave Jiang <dave.jiang@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-07-12 06:55:33 +03:00
struct swap_info_struct * si ;
2005-04-17 02:20:36 +04:00
mm, swap: fix race between swapoff and some swap operations
When swapin is performed, after getting the swap entry information from
the page table, system will swap in the swap entry, without any lock held
to prevent the swap device from being swapoff. This may cause the race
like below,
CPU 1 CPU 2
----- -----
do_swap_page
swapin_readahead
__read_swap_cache_async
swapoff swapcache_prepare
p->swap_map = NULL __swap_duplicate
p->swap_map[?] /* !!! NULL pointer access */
Because swapoff is usually done when system shutdown only, the race may
not hit many people in practice. But it is still a race need to be fixed.
To fix the race, get_swap_device() is added to check whether the specified
swap entry is valid in its swap device. If so, it will keep the swap
entry valid via preventing the swap device from being swapoff, until
put_swap_device() is called.
Because swapoff() is very rare code path, to make the normal path runs as
fast as possible, rcu_read_lock/unlock() and synchronize_rcu() instead of
reference count is used to implement get/put_swap_device(). >From
get_swap_device() to put_swap_device(), RCU reader side is locked, so
synchronize_rcu() in swapoff() will wait until put_swap_device() is
called.
In addition to swap_map, cluster_info, etc. data structure in the struct
swap_info_struct, the swap cache radix tree will be freed after swapoff,
so this patch fixes the race between swap cache looking up and swapoff
too.
Races between some other swap cache usages and swapoff are fixed too via
calling synchronize_rcu() between clearing PageSwapCache() and freeing
swap cache data structure.
Another possible method to fix this is to use preempt_off() +
stop_machine() to prevent the swap device from being swapoff when its data
structure is being accessed. The overhead in hot-path of both methods is
similar. The advantages of RCU based method are,
1. stop_machine() may disturb the normal execution code path on other
CPUs.
2. File cache uses RCU to protect its radix tree. If the similar
mechanism is used for swap cache too, it is easier to share code
between them.
3. RCU is used to protect swap cache in total_swapcache_pages() and
exit_swap_address_space() already. The two mechanisms can be
merged to simplify the logic.
Link: http://lkml.kernel.org/r/20190522015423.14418-1-ying.huang@intel.com
Fixes: 235b62176712 ("mm/swap: add cluster lock")
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Reviewed-by: Andrea Parri <andrea.parri@amarulasolutions.com>
Not-nacked-by: Hugh Dickins <hughd@google.com>
Cc: Andrea Arcangeli <aarcange@redhat.com>
Cc: Paul E. McKenney <paulmck@linux.vnet.ibm.com>
Cc: Daniel Jordan <daniel.m.jordan@oracle.com>
Cc: Michal Hocko <mhocko@suse.com>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Tim Chen <tim.c.chen@linux.intel.com>
Cc: Mel Gorman <mgorman@techsingularity.net>
Cc: Jérôme Glisse <jglisse@redhat.com>
Cc: Yang Shi <yang.shi@linux.alibaba.com>
Cc: David Rientjes <rientjes@google.com>
Cc: Rik van Riel <riel@redhat.com>
Cc: Jan Kara <jack@suse.cz>
Cc: Dave Jiang <dave.jiang@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-07-12 06:55:33 +03:00
si = get_swap_device ( entry ) ;
if ( ! si )
return NULL ;
mm, swap: use offset of swap entry as key of swap cache
This patch is to improve the performance of swap cache operations when
the type of the swap device is not 0. Originally, the whole swap entry
value is used as the key of the swap cache, even though there is one
radix tree for each swap device. If the type of the swap device is not
0, the height of the radix tree of the swap cache will be increased
unnecessary, especially on 64bit architecture. For example, for a 1GB
swap device on the x86_64 architecture, the height of the radix tree of
the swap cache is 11. But if the offset of the swap entry is used as
the key of the swap cache, the height of the radix tree of the swap
cache is 4. The increased height causes unnecessary radix tree
descending and increased cache footprint.
This patch reduces the height of the radix tree of the swap cache via
using the offset of the swap entry instead of the whole swap entry value
as the key of the swap cache. In 32 processes sequential swap out test
case on a Xeon E5 v3 system with RAM disk as swap, the lock contention
for the spinlock of the swap cache is reduced from 20.15% to 12.19%,
when the type of the swap device is 1.
Use the whole swap entry as key,
perf-profile.calltrace.cycles-pp._raw_spin_lock_irq.__add_to_swap_cache.add_to_swap_cache.add_to_swap.shrink_page_list: 10.37,
perf-profile.calltrace.cycles-pp._raw_spin_lock_irqsave.__remove_mapping.shrink_page_list.shrink_inactive_list.shrink_node_memcg: 9.78,
Use the swap offset as key,
perf-profile.calltrace.cycles-pp._raw_spin_lock_irq.__add_to_swap_cache.add_to_swap_cache.add_to_swap.shrink_page_list: 6.25,
perf-profile.calltrace.cycles-pp._raw_spin_lock_irqsave.__remove_mapping.shrink_page_list.shrink_inactive_list.shrink_node_memcg: 5.94,
Link: http://lkml.kernel.org/r/1473270649-27229-1-git-send-email-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Michal Hocko <mhocko@kernel.org>
Cc: Vladimir Davydov <vdavydov.dev@gmail.com>
Cc: "Kirill A. Shutemov" <kirill.shutemov@linux.intel.com>
Cc: Dave Hansen <dave.hansen@linux.intel.com>
Cc: Dan Williams <dan.j.williams@intel.com>
Cc: Joonsoo Kim <iamjoonsoo.kim@lge.com>
Cc: Hugh Dickins <hughd@google.com>
Cc: Mel Gorman <mgorman@techsingularity.net>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Aaron Lu <aaron.lu@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2016-10-08 03:00:21 +03:00
page = find_get_page ( swap_address_space ( entry ) , swp_offset ( entry ) ) ;
mm, swap: fix race between swapoff and some swap operations
When swapin is performed, after getting the swap entry information from
the page table, system will swap in the swap entry, without any lock held
to prevent the swap device from being swapoff. This may cause the race
like below,
CPU 1 CPU 2
----- -----
do_swap_page
swapin_readahead
__read_swap_cache_async
swapoff swapcache_prepare
p->swap_map = NULL __swap_duplicate
p->swap_map[?] /* !!! NULL pointer access */
Because swapoff is usually done when system shutdown only, the race may
not hit many people in practice. But it is still a race need to be fixed.
To fix the race, get_swap_device() is added to check whether the specified
swap entry is valid in its swap device. If so, it will keep the swap
entry valid via preventing the swap device from being swapoff, until
put_swap_device() is called.
Because swapoff() is very rare code path, to make the normal path runs as
fast as possible, rcu_read_lock/unlock() and synchronize_rcu() instead of
reference count is used to implement get/put_swap_device(). >From
get_swap_device() to put_swap_device(), RCU reader side is locked, so
synchronize_rcu() in swapoff() will wait until put_swap_device() is
called.
In addition to swap_map, cluster_info, etc. data structure in the struct
swap_info_struct, the swap cache radix tree will be freed after swapoff,
so this patch fixes the race between swap cache looking up and swapoff
too.
Races between some other swap cache usages and swapoff are fixed too via
calling synchronize_rcu() between clearing PageSwapCache() and freeing
swap cache data structure.
Another possible method to fix this is to use preempt_off() +
stop_machine() to prevent the swap device from being swapoff when its data
structure is being accessed. The overhead in hot-path of both methods is
similar. The advantages of RCU based method are,
1. stop_machine() may disturb the normal execution code path on other
CPUs.
2. File cache uses RCU to protect its radix tree. If the similar
mechanism is used for swap cache too, it is easier to share code
between them.
3. RCU is used to protect swap cache in total_swapcache_pages() and
exit_swap_address_space() already. The two mechanisms can be
merged to simplify the logic.
Link: http://lkml.kernel.org/r/20190522015423.14418-1-ying.huang@intel.com
Fixes: 235b62176712 ("mm/swap: add cluster lock")
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Reviewed-by: Andrea Parri <andrea.parri@amarulasolutions.com>
Not-nacked-by: Hugh Dickins <hughd@google.com>
Cc: Andrea Arcangeli <aarcange@redhat.com>
Cc: Paul E. McKenney <paulmck@linux.vnet.ibm.com>
Cc: Daniel Jordan <daniel.m.jordan@oracle.com>
Cc: Michal Hocko <mhocko@suse.com>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Tim Chen <tim.c.chen@linux.intel.com>
Cc: Mel Gorman <mgorman@techsingularity.net>
Cc: Jérôme Glisse <jglisse@redhat.com>
Cc: Yang Shi <yang.shi@linux.alibaba.com>
Cc: David Rientjes <rientjes@google.com>
Cc: Rik van Riel <riel@redhat.com>
Cc: Jan Kara <jack@suse.cz>
Cc: Dave Jiang <dave.jiang@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-07-12 06:55:33 +03:00
put_swap_device ( si ) ;
2005-04-17 02:20:36 +04:00
mm, swap: VMA based swap readahead
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory. And the different tasks in the system may have different access
patterns, which makes the global space locality estimation incorrect.
In this patch, when page fault occurs, the virtual pages near the fault
address will be readahead instead of the swap slots near the fault swap
slot in swap device. This avoid to readahead the unrelated swap slots.
At the same time, the swap readahead is changed to work on per-VMA from
globally. So that the different access patterns of the different VMAs
could be distinguished, and the different readahead policy could be
applied accordingly. The original core readahead detection and scaling
algorithm is reused, because it is an effect algorithm to detect the
space locality.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device:
NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:36 +03:00
INC_CACHE_INFO ( find_total ) ;
if ( page ) {
2018-04-06 02:23:39 +03:00
bool vma_ra = swap_use_vma_readahead ( ) ;
bool readahead ;
2005-04-17 02:20:36 +04:00
INC_CACHE_INFO ( find_success ) ;
2018-04-06 02:23:39 +03:00
/*
* At the moment , we don ' t support PG_readahead for anon THP
* so let ' s bail out rather than confusing the readahead stat .
*/
mm, swap: VMA based swap readahead
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory. And the different tasks in the system may have different access
patterns, which makes the global space locality estimation incorrect.
In this patch, when page fault occurs, the virtual pages near the fault
address will be readahead instead of the swap slots near the fault swap
slot in swap device. This avoid to readahead the unrelated swap slots.
At the same time, the swap readahead is changed to work on per-VMA from
globally. So that the different access patterns of the different VMAs
could be distinguished, and the different readahead policy could be
applied accordingly. The original core readahead detection and scaling
algorithm is reused, because it is an effect algorithm to detect the
space locality.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device:
NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:36 +03:00
if ( unlikely ( PageTransCompound ( page ) ) )
return page ;
2018-04-06 02:23:39 +03:00
mm, swap: VMA based swap readahead
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory. And the different tasks in the system may have different access
patterns, which makes the global space locality estimation incorrect.
In this patch, when page fault occurs, the virtual pages near the fault
address will be readahead instead of the swap slots near the fault swap
slot in swap device. This avoid to readahead the unrelated swap slots.
At the same time, the swap readahead is changed to work on per-VMA from
globally. So that the different access patterns of the different VMAs
could be distinguished, and the different readahead policy could be
applied accordingly. The original core readahead detection and scaling
algorithm is reused, because it is an effect algorithm to detect the
space locality.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device:
NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:36 +03:00
readahead = TestClearPageReadahead ( page ) ;
2018-04-06 02:23:39 +03:00
if ( vma & & vma_ra ) {
unsigned long ra_val ;
int win , hits ;
ra_val = GET_SWAP_RA_VAL ( vma ) ;
win = SWAP_RA_WIN ( ra_val ) ;
hits = SWAP_RA_HITS ( ra_val ) ;
mm, swap: VMA based swap readahead
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory. And the different tasks in the system may have different access
patterns, which makes the global space locality estimation incorrect.
In this patch, when page fault occurs, the virtual pages near the fault
address will be readahead instead of the swap slots near the fault swap
slot in swap device. This avoid to readahead the unrelated swap slots.
At the same time, the swap readahead is changed to work on per-VMA from
globally. So that the different access patterns of the different VMAs
could be distinguished, and the different readahead policy could be
applied accordingly. The original core readahead detection and scaling
algorithm is reused, because it is an effect algorithm to detect the
space locality.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device:
NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:36 +03:00
if ( readahead )
hits = min_t ( int , hits + 1 , SWAP_RA_HITS_MAX ) ;
atomic_long_set ( & vma - > swap_readahead_info ,
SWAP_RA_VAL ( addr , win , hits ) ) ;
}
2018-04-06 02:23:39 +03:00
mm, swap: VMA based swap readahead
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory. And the different tasks in the system may have different access
patterns, which makes the global space locality estimation incorrect.
In this patch, when page fault occurs, the virtual pages near the fault
address will be readahead instead of the swap slots near the fault swap
slot in swap device. This avoid to readahead the unrelated swap slots.
At the same time, the swap readahead is changed to work on per-VMA from
globally. So that the different access patterns of the different VMAs
could be distinguished, and the different readahead policy could be
applied accordingly. The original core readahead detection and scaling
algorithm is reused, because it is an effect algorithm to detect the
space locality.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device:
NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:36 +03:00
if ( readahead ) {
mm, swap: add swap readahead hit statistics
Patch series "mm, swap: VMA based swap readahead", v4.
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory space. And the different tasks in the system may have different
access patterns, which makes the global space locality estimation
incorrect.
In this patchset, when page fault occurs, the virtual pages near the
fault address will be readahead instead of the swap slots near the fault
swap slot in swap device. This avoid to readahead the unrelated swap
slots. At the same time, the swap readahead is changed to work on
per-VMA from globally. So that the different access patterns of the
different VMAs could be distinguished, and the different readahead
policy could be applied accordingly. The original core readahead
detection and scaling algorithm is reused, because it is an effect
algorithm to detect the space locality.
In addition to the swap readahead changes, some new sysfs interface is
added to show the efficiency of the readahead algorithm and some other
swap statistics.
This new implementation will incur more small random read, on SSD, the
improved correctness of estimation and readahead target should beat the
potential increased overhead, this is also illustrated in the test
results below. But on HDD, the overhead may beat the benefit, so the
original implementation will be used by default.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM)
Swap device: NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
This patch (of 5):
The statistics for total readahead pages and total readahead hits are
recorded and exported via the following sysfs interface.
/sys/kernel/mm/swap/ra_hits
/sys/kernel/mm/swap/ra_total
With them, the efficiency of the swap readahead could be measured, so
that the swap readahead algorithm and parameters could be tuned
accordingly.
[akpm@linux-foundation.org: don't display swap stats if CONFIG_SWAP=n]
Link: http://lkml.kernel.org/r/20170807054038.1843-2-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:29 +03:00
count_vm_event ( SWAP_RA_HIT ) ;
2018-04-06 02:23:39 +03:00
if ( ! vma | | ! vma_ra )
mm, swap: VMA based swap readahead
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory. And the different tasks in the system may have different access
patterns, which makes the global space locality estimation incorrect.
In this patch, when page fault occurs, the virtual pages near the fault
address will be readahead instead of the swap slots near the fault swap
slot in swap device. This avoid to readahead the unrelated swap slots.
At the same time, the swap readahead is changed to work on per-VMA from
globally. So that the different access patterns of the different VMAs
could be distinguished, and the different readahead policy could be
applied accordingly. The original core readahead detection and scaling
algorithm is reused, because it is an effect algorithm to detect the
space locality.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device:
NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:36 +03:00
atomic_inc ( & swapin_readahead_hits ) ;
mm, swap: add swap readahead hit statistics
Patch series "mm, swap: VMA based swap readahead", v4.
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory space. And the different tasks in the system may have different
access patterns, which makes the global space locality estimation
incorrect.
In this patchset, when page fault occurs, the virtual pages near the
fault address will be readahead instead of the swap slots near the fault
swap slot in swap device. This avoid to readahead the unrelated swap
slots. At the same time, the swap readahead is changed to work on
per-VMA from globally. So that the different access patterns of the
different VMAs could be distinguished, and the different readahead
policy could be applied accordingly. The original core readahead
detection and scaling algorithm is reused, because it is an effect
algorithm to detect the space locality.
In addition to the swap readahead changes, some new sysfs interface is
added to show the efficiency of the readahead algorithm and some other
swap statistics.
This new implementation will incur more small random read, on SSD, the
improved correctness of estimation and readahead target should beat the
potential increased overhead, this is also illustrated in the test
results below. But on HDD, the overhead may beat the benefit, so the
original implementation will be used by default.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM)
Swap device: NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
This patch (of 5):
The statistics for total readahead pages and total readahead hits are
recorded and exported via the following sysfs interface.
/sys/kernel/mm/swap/ra_hits
/sys/kernel/mm/swap/ra_total
With them, the efficiency of the swap readahead could be measured, so
that the swap readahead algorithm and parameters could be tuned
accordingly.
[akpm@linux-foundation.org: don't display swap stats if CONFIG_SWAP=n]
Link: http://lkml.kernel.org/r/20170807054038.1843-2-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:29 +03:00
}
swap: add a simple detector for inappropriate swapin readahead
This is a patch to improve swap readahead algorithm. It's from Hugh and
I slightly changed it.
Hugh's original changelog:
swapin readahead does a blind readahead, whether or not the swapin is
sequential. This may be ok on harddisk, because large reads have
relatively small costs, and if the readahead pages are unneeded they can
be reclaimed easily - though, what if their allocation forced reclaim of
useful pages? But on SSD devices large reads are more expensive than
small ones: if the readahead pages are unneeded, reading them in caused
significant overhead.
This patch adds very simplistic random read detection. Stealing the
PageReadahead technique from Konstantin Khlebnikov's patch, avoiding the
vma/anon_vma sophistications of Shaohua Li's patch, swapin_nr_pages()
simply looks at readahead's current success rate, and narrows or widens
its readahead window accordingly. There is little science to its
heuristic: it's about as stupid as can be whilst remaining effective.
The table below shows elapsed times (in centiseconds) when running a
single repetitive swapping load across a 1000MB mapping in 900MB ram
with 1GB swap (the harddisk tests had taken painfully too long when I
used mem=500M, but SSD shows similar results for that).
Vanilla is the 3.6-rc7 kernel on which I started; Shaohua denotes his
Sep 3 patch in mmotm and linux-next; HughOld denotes my Oct 1 patch
which Shaohua showed to be defective; HughNew this Nov 14 patch, with
page_cluster as usual at default of 3 (8-page reads); HughPC4 this same
patch with page_cluster 4 (16-page reads); HughPC0 with page_cluster 0
(1-page reads: no readahead).
HDD for swapping to harddisk, SSD for swapping to VertexII SSD. Seq for
sequential access to the mapping, cycling five times around; Rand for
the same number of random touches. Anon for a MAP_PRIVATE anon mapping;
Shmem for a MAP_SHARED anon mapping, equivalent to tmpfs.
One weakness of Shaohua's vma/anon_vma approach was that it did not
optimize Shmem: seen below. Konstantin's approach was perhaps mistuned,
50% slower on Seq: did not compete and is not shown below.
HDD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0
Seq Anon 73921 76210 75611 76904 78191 121542
Seq Shmem 73601 73176 73855 72947 74543 118322
Rand Anon 895392 831243 871569 845197 846496 841680
Rand Shmem 1058375 1053486 827935 764955 764376 756489
SSD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0
Seq Anon 24634 24198 24673 25107 21614 70018
Seq Shmem 24959 24932 25052 25703 22030 69678
Rand Anon 43014 26146 28075 25989 26935 25901
Rand Shmem 45349 45215 28249 24268 24138 24332
These tests are, of course, two extremes of a very simple case: under
heavier mixed loads I've not yet observed any consistent improvement or
degradation, and wider testing would be welcome.
Shaohua Li:
Test shows Vanilla is slightly better in sequential workload than Hugh's
patch. I observed with Hugh's patch sometimes the readahead size is
shrinked too fast (from 8 to 1 immediately) in sequential workload if
there is no hit. And in such case, continuing doing readahead is good
actually.
I don't prepare a sophisticated algorithm for the sequential workload
because so far we can't guarantee sequential accessed pages are swap out
sequentially. So I slightly change Hugh's heuristic - don't shrink
readahead size too fast.
Here is my test result (unit second, 3 runs average):
Vanilla Hugh New
Seq 356 370 360
Random 4525 2447 2444
Attached graph is the swapin/swapout throughput I collected with 'vmstat
2'. The first part is running a random workload (till around 1200 of
the x-axis) and the second part is running a sequential workload.
swapin and swapout throughput are almost identical in steady state in
both workloads. These are expected behavior. while in Vanilla, swapin
is much bigger than swapout especially in random workload (because wrong
readahead).
Original patches by: Shaohua Li and Konstantin Khlebnikov.
[fengguang.wu@intel.com: swapin_nr_pages() can be static]
Signed-off-by: Hugh Dickins <hughd@google.com>
Signed-off-by: Shaohua Li <shli@fusionio.com>
Signed-off-by: Fengguang Wu <fengguang.wu@intel.com>
Cc: Rik van Riel <riel@redhat.com>
Cc: Wu Fengguang <fengguang.wu@intel.com>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Konstantin Khlebnikov <khlebnikov@openvz.org>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2014-02-07 00:04:21 +04:00
}
2018-04-06 02:23:39 +03:00
2005-04-17 02:20:36 +04:00
return page ;
}
2020-10-14 02:51:17 +03:00
/**
* find_get_incore_page - Find and get a page from the page or swap caches .
* @ mapping : The address_space to search .
* @ index : The page cache index .
*
* This differs from find_get_page ( ) in that it will also look for the
* page in the swap cache .
*
* Return : The found page or % NULL .
*/
struct page * find_get_incore_page ( struct address_space * mapping , pgoff_t index )
{
swp_entry_t swp ;
struct swap_info_struct * si ;
2021-02-26 04:15:36 +03:00
struct page * page = pagecache_get_page ( mapping , index ,
FGP_ENTRY | FGP_HEAD , 0 ) ;
2020-10-14 02:51:17 +03:00
2020-10-14 02:51:34 +03:00
if ( ! page )
2020-10-14 02:51:17 +03:00
return page ;
2020-10-14 02:51:34 +03:00
if ( ! xa_is_value ( page ) )
return find_subpage ( page , index ) ;
2020-10-14 02:51:17 +03:00
if ( ! shmem_mapping ( mapping ) )
return NULL ;
swp = radix_to_swp_entry ( page ) ;
/* Prevent swapoff from happening to us */
si = get_swap_device ( swp ) ;
if ( ! si )
return NULL ;
page = find_get_page ( swap_address_space ( swp ) , swp_offset ( swp ) ) ;
put_swap_device ( si ) ;
return page ;
}
2015-09-09 01:05:00 +03:00
struct page * __read_swap_cache_async ( swp_entry_t entry , gfp_t gfp_mask ,
struct vm_area_struct * vma , unsigned long addr ,
bool * new_page_allocated )
2005-04-17 02:20:36 +04:00
{
mm, swap: fix race between swapoff and some swap operations
When swapin is performed, after getting the swap entry information from
the page table, system will swap in the swap entry, without any lock held
to prevent the swap device from being swapoff. This may cause the race
like below,
CPU 1 CPU 2
----- -----
do_swap_page
swapin_readahead
__read_swap_cache_async
swapoff swapcache_prepare
p->swap_map = NULL __swap_duplicate
p->swap_map[?] /* !!! NULL pointer access */
Because swapoff is usually done when system shutdown only, the race may
not hit many people in practice. But it is still a race need to be fixed.
To fix the race, get_swap_device() is added to check whether the specified
swap entry is valid in its swap device. If so, it will keep the swap
entry valid via preventing the swap device from being swapoff, until
put_swap_device() is called.
Because swapoff() is very rare code path, to make the normal path runs as
fast as possible, rcu_read_lock/unlock() and synchronize_rcu() instead of
reference count is used to implement get/put_swap_device(). >From
get_swap_device() to put_swap_device(), RCU reader side is locked, so
synchronize_rcu() in swapoff() will wait until put_swap_device() is
called.
In addition to swap_map, cluster_info, etc. data structure in the struct
swap_info_struct, the swap cache radix tree will be freed after swapoff,
so this patch fixes the race between swap cache looking up and swapoff
too.
Races between some other swap cache usages and swapoff are fixed too via
calling synchronize_rcu() between clearing PageSwapCache() and freeing
swap cache data structure.
Another possible method to fix this is to use preempt_off() +
stop_machine() to prevent the swap device from being swapoff when its data
structure is being accessed. The overhead in hot-path of both methods is
similar. The advantages of RCU based method are,
1. stop_machine() may disturb the normal execution code path on other
CPUs.
2. File cache uses RCU to protect its radix tree. If the similar
mechanism is used for swap cache too, it is easier to share code
between them.
3. RCU is used to protect swap cache in total_swapcache_pages() and
exit_swap_address_space() already. The two mechanisms can be
merged to simplify the logic.
Link: http://lkml.kernel.org/r/20190522015423.14418-1-ying.huang@intel.com
Fixes: 235b62176712 ("mm/swap: add cluster lock")
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Reviewed-by: Andrea Parri <andrea.parri@amarulasolutions.com>
Not-nacked-by: Hugh Dickins <hughd@google.com>
Cc: Andrea Arcangeli <aarcange@redhat.com>
Cc: Paul E. McKenney <paulmck@linux.vnet.ibm.com>
Cc: Daniel Jordan <daniel.m.jordan@oracle.com>
Cc: Michal Hocko <mhocko@suse.com>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Tim Chen <tim.c.chen@linux.intel.com>
Cc: Mel Gorman <mgorman@techsingularity.net>
Cc: Jérôme Glisse <jglisse@redhat.com>
Cc: Yang Shi <yang.shi@linux.alibaba.com>
Cc: David Rientjes <rientjes@google.com>
Cc: Rik van Riel <riel@redhat.com>
Cc: Jan Kara <jack@suse.cz>
Cc: Dave Jiang <dave.jiang@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-07-12 06:55:33 +03:00
struct swap_info_struct * si ;
2020-06-04 02:02:17 +03:00
struct page * page ;
2020-08-12 04:30:50 +03:00
void * shadow = NULL ;
2020-06-04 02:02:17 +03:00
2015-09-09 01:05:00 +03:00
* new_page_allocated = false ;
2005-04-17 02:20:36 +04:00
2020-06-04 02:02:17 +03:00
for ( ; ; ) {
int err ;
2005-04-17 02:20:36 +04:00
/*
* First check the swap cache . Since this is normally
* called after lookup_swap_cache ( ) failed , re - calling
* that would confuse statistics .
*/
mm, swap: fix race between swapoff and some swap operations
When swapin is performed, after getting the swap entry information from
the page table, system will swap in the swap entry, without any lock held
to prevent the swap device from being swapoff. This may cause the race
like below,
CPU 1 CPU 2
----- -----
do_swap_page
swapin_readahead
__read_swap_cache_async
swapoff swapcache_prepare
p->swap_map = NULL __swap_duplicate
p->swap_map[?] /* !!! NULL pointer access */
Because swapoff is usually done when system shutdown only, the race may
not hit many people in practice. But it is still a race need to be fixed.
To fix the race, get_swap_device() is added to check whether the specified
swap entry is valid in its swap device. If so, it will keep the swap
entry valid via preventing the swap device from being swapoff, until
put_swap_device() is called.
Because swapoff() is very rare code path, to make the normal path runs as
fast as possible, rcu_read_lock/unlock() and synchronize_rcu() instead of
reference count is used to implement get/put_swap_device(). >From
get_swap_device() to put_swap_device(), RCU reader side is locked, so
synchronize_rcu() in swapoff() will wait until put_swap_device() is
called.
In addition to swap_map, cluster_info, etc. data structure in the struct
swap_info_struct, the swap cache radix tree will be freed after swapoff,
so this patch fixes the race between swap cache looking up and swapoff
too.
Races between some other swap cache usages and swapoff are fixed too via
calling synchronize_rcu() between clearing PageSwapCache() and freeing
swap cache data structure.
Another possible method to fix this is to use preempt_off() +
stop_machine() to prevent the swap device from being swapoff when its data
structure is being accessed. The overhead in hot-path of both methods is
similar. The advantages of RCU based method are,
1. stop_machine() may disturb the normal execution code path on other
CPUs.
2. File cache uses RCU to protect its radix tree. If the similar
mechanism is used for swap cache too, it is easier to share code
between them.
3. RCU is used to protect swap cache in total_swapcache_pages() and
exit_swap_address_space() already. The two mechanisms can be
merged to simplify the logic.
Link: http://lkml.kernel.org/r/20190522015423.14418-1-ying.huang@intel.com
Fixes: 235b62176712 ("mm/swap: add cluster lock")
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Reviewed-by: Andrea Parri <andrea.parri@amarulasolutions.com>
Not-nacked-by: Hugh Dickins <hughd@google.com>
Cc: Andrea Arcangeli <aarcange@redhat.com>
Cc: Paul E. McKenney <paulmck@linux.vnet.ibm.com>
Cc: Daniel Jordan <daniel.m.jordan@oracle.com>
Cc: Michal Hocko <mhocko@suse.com>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Tim Chen <tim.c.chen@linux.intel.com>
Cc: Mel Gorman <mgorman@techsingularity.net>
Cc: Jérôme Glisse <jglisse@redhat.com>
Cc: Yang Shi <yang.shi@linux.alibaba.com>
Cc: David Rientjes <rientjes@google.com>
Cc: Rik van Riel <riel@redhat.com>
Cc: Jan Kara <jack@suse.cz>
Cc: Dave Jiang <dave.jiang@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-07-12 06:55:33 +03:00
si = get_swap_device ( entry ) ;
if ( ! si )
2020-06-04 02:02:17 +03:00
return NULL ;
page = find_get_page ( swap_address_space ( entry ) ,
swp_offset ( entry ) ) ;
mm, swap: fix race between swapoff and some swap operations
When swapin is performed, after getting the swap entry information from
the page table, system will swap in the swap entry, without any lock held
to prevent the swap device from being swapoff. This may cause the race
like below,
CPU 1 CPU 2
----- -----
do_swap_page
swapin_readahead
__read_swap_cache_async
swapoff swapcache_prepare
p->swap_map = NULL __swap_duplicate
p->swap_map[?] /* !!! NULL pointer access */
Because swapoff is usually done when system shutdown only, the race may
not hit many people in practice. But it is still a race need to be fixed.
To fix the race, get_swap_device() is added to check whether the specified
swap entry is valid in its swap device. If so, it will keep the swap
entry valid via preventing the swap device from being swapoff, until
put_swap_device() is called.
Because swapoff() is very rare code path, to make the normal path runs as
fast as possible, rcu_read_lock/unlock() and synchronize_rcu() instead of
reference count is used to implement get/put_swap_device(). >From
get_swap_device() to put_swap_device(), RCU reader side is locked, so
synchronize_rcu() in swapoff() will wait until put_swap_device() is
called.
In addition to swap_map, cluster_info, etc. data structure in the struct
swap_info_struct, the swap cache radix tree will be freed after swapoff,
so this patch fixes the race between swap cache looking up and swapoff
too.
Races between some other swap cache usages and swapoff are fixed too via
calling synchronize_rcu() between clearing PageSwapCache() and freeing
swap cache data structure.
Another possible method to fix this is to use preempt_off() +
stop_machine() to prevent the swap device from being swapoff when its data
structure is being accessed. The overhead in hot-path of both methods is
similar. The advantages of RCU based method are,
1. stop_machine() may disturb the normal execution code path on other
CPUs.
2. File cache uses RCU to protect its radix tree. If the similar
mechanism is used for swap cache too, it is easier to share code
between them.
3. RCU is used to protect swap cache in total_swapcache_pages() and
exit_swap_address_space() already. The two mechanisms can be
merged to simplify the logic.
Link: http://lkml.kernel.org/r/20190522015423.14418-1-ying.huang@intel.com
Fixes: 235b62176712 ("mm/swap: add cluster lock")
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Reviewed-by: Andrea Parri <andrea.parri@amarulasolutions.com>
Not-nacked-by: Hugh Dickins <hughd@google.com>
Cc: Andrea Arcangeli <aarcange@redhat.com>
Cc: Paul E. McKenney <paulmck@linux.vnet.ibm.com>
Cc: Daniel Jordan <daniel.m.jordan@oracle.com>
Cc: Michal Hocko <mhocko@suse.com>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Tim Chen <tim.c.chen@linux.intel.com>
Cc: Mel Gorman <mgorman@techsingularity.net>
Cc: Jérôme Glisse <jglisse@redhat.com>
Cc: Yang Shi <yang.shi@linux.alibaba.com>
Cc: David Rientjes <rientjes@google.com>
Cc: Rik van Riel <riel@redhat.com>
Cc: Jan Kara <jack@suse.cz>
Cc: Dave Jiang <dave.jiang@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-07-12 06:55:33 +03:00
put_swap_device ( si ) ;
2020-06-04 02:02:17 +03:00
if ( page )
return page ;
2005-04-17 02:20:36 +04:00
2017-02-23 02:45:46 +03:00
/*
* Just skip read ahead for unused swap slot .
* During swap_off when swap_slot_cache is disabled ,
* we have to handle the race between putting
* swap entry in swap cache and marking swap slot
* as SWAP_HAS_CACHE . That ' s done in later part of code or
* else swap_off will be aborted if we return NULL .
*/
if ( ! __swp_swapcount ( entry ) & & swap_slot_cache_enabled )
2020-06-04 02:02:17 +03:00
return NULL ;
2017-02-23 02:45:29 +03:00
2005-04-17 02:20:36 +04:00
/*
2020-06-04 02:02:17 +03:00
* Get a new page to read into from swap . Allocate it now ,
* before marking swap_map SWAP_HAS_CACHE , when - EEXIST will
* cause any racers to loop around until we add it to cache .
2005-04-17 02:20:36 +04:00
*/
2020-06-04 02:02:17 +03:00
page = alloc_page_vma ( gfp_mask , vma , addr ) ;
if ( ! page )
return NULL ;
2005-04-17 02:20:36 +04:00
2008-02-05 09:28:49 +03:00
/*
* Swap entry may have been freed since our caller observed it .
*/
2009-06-17 02:32:53 +04:00
err = swapcache_prepare ( entry ) ;
2020-06-04 02:02:17 +03:00
if ( ! err )
2008-02-05 09:28:49 +03:00
break ;
2020-06-04 02:02:17 +03:00
put_page ( page ) ;
if ( err ! = - EEXIST )
return NULL ;
2009-09-22 04:02:52 +04:00
/*
2020-06-04 02:02:17 +03:00
* We might race against __delete_from_swap_cache ( ) , and
* stumble across a swap_map entry whose SWAP_HAS_CACHE
* has not yet been cleared . Or race against another
* __read_swap_cache_async ( ) , which has set SWAP_HAS_CACHE
* in swap_map , but not yet added its page to swap cache .
2009-09-22 04:02:52 +04:00
*/
mm: swap: get rid of livelock in swapin readahead
In our testing, a livelock task was found. Through sysrq printing, same
stack was found every time, as follows:
__swap_duplicate+0x58/0x1a0
swapcache_prepare+0x24/0x30
__read_swap_cache_async+0xac/0x220
read_swap_cache_async+0x58/0xa0
swapin_readahead+0x24c/0x628
do_swap_page+0x374/0x8a0
__handle_mm_fault+0x598/0xd60
handle_mm_fault+0x114/0x200
do_page_fault+0x148/0x4d0
do_translation_fault+0xb0/0xd4
do_mem_abort+0x50/0xb0
The reason for the livelock is that swapcache_prepare() always returns
EEXIST, indicating that SWAP_HAS_CACHE has not been cleared, so that it
cannot jump out of the loop. We suspect that the task that clears the
SWAP_HAS_CACHE flag never gets a chance to run. We try to lower the
priority of the task stuck in a livelock so that the task that clears
the SWAP_HAS_CACHE flag will run. The results show that the system
returns to normal after the priority is lowered.
In our testing, multiple real-time tasks are bound to the same core, and
the task in the livelock is the highest priority task of the core, so
the livelocked task cannot be preempted.
Although cond_resched() is used by __read_swap_cache_async, it is an
empty function in the preemptive system and cannot achieve the purpose
of releasing the CPU. A high-priority task cannot release the CPU
unless preempted by a higher-priority task. But when this task is
already the highest priority task on this core, other tasks will not be
able to be scheduled. So we think we should replace cond_resched() with
schedule_timeout_uninterruptible(1), schedule_timeout_interruptible will
call set_current_state first to set the task state, so the task will be
removed from the running queue, so as to achieve the purpose of giving
up the CPU and prevent it from running in kernel mode for too long.
(akpm: ugly hack becomes uglier. But it fixes the issue in a
backportable-to-stable fashion while we hopefully work on something
better)
Link: https://lkml.kernel.org/r/20220221111749.1928222-1-cgel.zte@gmail.com
Signed-off-by: Guo Ziliang <guo.ziliang@zte.com.cn>
Reported-by: Zeal Robot <zealci@zte.com.cn>
Reviewed-by: Ran Xiaokai <ran.xiaokai@zte.com.cn>
Reviewed-by: Jiang Xuexin <jiang.xuexin@zte.com.cn>
Reviewed-by: Yang Yang <yang.yang29@zte.com.cn>
Acked-by: Hugh Dickins <hughd@google.com>
Cc: Naoya Horiguchi <naoya.horiguchi@nec.com>
Cc: Michal Hocko <mhocko@kernel.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Roger Quadros <rogerq@kernel.org>
Cc: Ziliang Guo <guo.ziliang@zte.com.cn>
Cc: <stable@vger.kernel.org>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2022-03-17 02:15:03 +03:00
schedule_timeout_uninterruptible ( 1 ) ;
2020-06-04 02:02:17 +03:00
}
/*
* The swap entry is ours to swap in . Prepare the new page .
*/
__SetPageLocked ( page ) ;
__SetPageSwapBacked ( page ) ;
2021-04-30 08:56:36 +03:00
if ( mem_cgroup_swapin_charge_page ( page , NULL , gfp_mask , entry ) )
2020-06-04 02:02:17 +03:00
goto fail_unlock ;
2021-04-30 08:56:36 +03:00
/* May fail (-ENOMEM) if XArray node allocation failed. */
if ( add_to_swap_cache ( page , entry , gfp_mask & GFP_RECLAIM_MASK , & shadow ) )
2020-06-04 02:02:17 +03:00
goto fail_unlock ;
2021-04-30 08:56:36 +03:00
mem_cgroup_swapin_uncharge_swap ( entry ) ;
2020-06-04 02:02:17 +03:00
2020-08-12 04:30:50 +03:00
if ( shadow )
2021-04-29 17:27:16 +03:00
workingset_refault ( page_folio ( page ) , shadow ) ;
mm: balance LRU lists based on relative thrashing
Since the LRUs were split into anon and file lists, the VM has been
balancing between page cache and anonymous pages based on per-list ratios
of scanned vs. rotated pages. In most cases that tips page reclaim
towards the list that is easier to reclaim and has the fewest actively
used pages, but there are a few problems with it:
1. Refaults and LRU rotations are weighted the same way, even though
one costs IO and the other costs a bit of CPU.
2. The less we scan an LRU list based on already observed rotations,
the more we increase the sampling interval for new references, and
rotations become even more likely on that list. This can enter a
death spiral in which we stop looking at one list completely until
the other one is all but annihilated by page reclaim.
Since commit a528910e12ec ("mm: thrash detection-based file cache sizing")
we have refault detection for the page cache. Along with swapin events,
they are good indicators of when the file or anon list, respectively, is
too small for its workingset and needs to grow.
For example, if the page cache is thrashing, the cache pages need more
time in memory, while there may be colder pages on the anonymous list.
Likewise, if swapped pages are faulting back in, it indicates that we
reclaim anonymous pages too aggressively and should back off.
Replace LRU rotations with refaults and swapins as the basis for relative
reclaim cost of the two LRUs. This will have the VM target list balances
that incur the least amount of IO on aggregate.
Signed-off-by: Johannes Weiner <hannes@cmpxchg.org>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Cc: Joonsoo Kim <iamjoonsoo.kim@lge.com>
Cc: Michal Hocko <mhocko@suse.com>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@surriel.com>
Link: http://lkml.kernel.org/r/20200520232525.798933-12-hannes@cmpxchg.org
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2020-06-04 02:03:03 +03:00
2020-06-04 02:02:17 +03:00
/* Caller will initiate read into locked page */
2020-06-04 02:02:40 +03:00
lru_cache_add ( page ) ;
2020-06-04 02:02:17 +03:00
* new_page_allocated = true ;
return page ;
2005-04-17 02:20:36 +04:00
2020-06-04 02:02:17 +03:00
fail_unlock :
2021-04-30 08:56:36 +03:00
put_swap_page ( page , entry ) ;
2020-06-04 02:02:17 +03:00
unlock_page ( page ) ;
put_page ( page ) ;
return NULL ;
2005-04-17 02:20:36 +04:00
}
2008-02-05 09:28:41 +03:00
2015-09-09 01:05:00 +03:00
/*
* Locate a page of swap in physical memory , reserving swap cache space
* and reading the disk if it is not already cached .
* A failure return means that either the page allocation failed or that
* the swap entry is no longer in use .
*/
struct page * read_swap_cache_async ( swp_entry_t entry , gfp_t gfp_mask ,
swap: add block io poll in swapin path
For fast flash disk, async IO could introduce overhead because of
context switch. block-mq now supports IO poll, which improves
performance and latency a lot. swapin is a good place to use this
technique, because the task is waiting for the swapin page to continue
execution.
In my virtual machine, directly read 4k data from a NVMe with iopoll is
about 60% better than that without poll. With iopoll support in swapin
patch, my microbenchmark (a task does random memory write) is about
10%~25% faster. CPU utilization increases a lot though, 2x and even 3x
CPU utilization. This will depend on disk speed.
While iopoll in swapin isn't intended for all usage cases, it's a win
for latency sensistive workloads with high speed swap disk. block layer
has knob to control poll in runtime. If poll isn't enabled in block
layer, there should be no noticeable change in swapin.
I got a chance to run the same test in a NVMe with DRAM as the media.
In simple fio IO test, blkpoll boosts 50% performance in single thread
test and ~20% in 8 threads test. So this is the base line. In above
swap test, blkpoll boosts ~27% performance in single thread test.
blkpoll uses 2x CPU time though.
If we enable hybid polling, the performance gain has very slight drop
but CPU time is only 50% worse than that without blkpoll. Also we can
adjust parameter of hybid poll, with it, the CPU time penality is
reduced further. In 8 threads test, blkpoll doesn't help though. The
performance is similar to that without blkpoll, but cpu utilization is
similar too. There is lock contention in swap path. The cpu time
spending on blkpoll isn't high. So overall, blkpoll swapin isn't worse
than that without it.
The swapin readahead might read several pages in in the same time and
form a big IO request. Since the IO will take longer time, it doesn't
make sense to do poll, so the patch only does iopoll for single page
swapin.
[akpm@linux-foundation.org: coding-style fixes]
Link: http://lkml.kernel.org/r/070c3c3e40b711e7b1390002c991e86a-b5408f0@7511894063d3764ff01ea8111f5a004d7dd700ed078797c204a24e620ddb965c
Signed-off-by: Shaohua Li <shli@fb.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Huang Ying <ying.huang@intel.com>
Cc: Jens Axboe <axboe@fb.com>
Cc: Hugh Dickins <hughd@google.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-11 01:47:11 +03:00
struct vm_area_struct * vma , unsigned long addr , bool do_poll )
2015-09-09 01:05:00 +03:00
{
bool page_was_allocated ;
struct page * retpage = __read_swap_cache_async ( entry , gfp_mask ,
vma , addr , & page_was_allocated ) ;
if ( page_was_allocated )
swap: add block io poll in swapin path
For fast flash disk, async IO could introduce overhead because of
context switch. block-mq now supports IO poll, which improves
performance and latency a lot. swapin is a good place to use this
technique, because the task is waiting for the swapin page to continue
execution.
In my virtual machine, directly read 4k data from a NVMe with iopoll is
about 60% better than that without poll. With iopoll support in swapin
patch, my microbenchmark (a task does random memory write) is about
10%~25% faster. CPU utilization increases a lot though, 2x and even 3x
CPU utilization. This will depend on disk speed.
While iopoll in swapin isn't intended for all usage cases, it's a win
for latency sensistive workloads with high speed swap disk. block layer
has knob to control poll in runtime. If poll isn't enabled in block
layer, there should be no noticeable change in swapin.
I got a chance to run the same test in a NVMe with DRAM as the media.
In simple fio IO test, blkpoll boosts 50% performance in single thread
test and ~20% in 8 threads test. So this is the base line. In above
swap test, blkpoll boosts ~27% performance in single thread test.
blkpoll uses 2x CPU time though.
If we enable hybid polling, the performance gain has very slight drop
but CPU time is only 50% worse than that without blkpoll. Also we can
adjust parameter of hybid poll, with it, the CPU time penality is
reduced further. In 8 threads test, blkpoll doesn't help though. The
performance is similar to that without blkpoll, but cpu utilization is
similar too. There is lock contention in swap path. The cpu time
spending on blkpoll isn't high. So overall, blkpoll swapin isn't worse
than that without it.
The swapin readahead might read several pages in in the same time and
form a big IO request. Since the IO will take longer time, it doesn't
make sense to do poll, so the patch only does iopoll for single page
swapin.
[akpm@linux-foundation.org: coding-style fixes]
Link: http://lkml.kernel.org/r/070c3c3e40b711e7b1390002c991e86a-b5408f0@7511894063d3764ff01ea8111f5a004d7dd700ed078797c204a24e620ddb965c
Signed-off-by: Shaohua Li <shli@fb.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Huang Ying <ying.huang@intel.com>
Cc: Jens Axboe <axboe@fb.com>
Cc: Hugh Dickins <hughd@google.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-11 01:47:11 +03:00
swap_readpage ( retpage , do_poll ) ;
2015-09-09 01:05:00 +03:00
return retpage ;
}
mm, swap: VMA based swap readahead
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory. And the different tasks in the system may have different access
patterns, which makes the global space locality estimation incorrect.
In this patch, when page fault occurs, the virtual pages near the fault
address will be readahead instead of the swap slots near the fault swap
slot in swap device. This avoid to readahead the unrelated swap slots.
At the same time, the swap readahead is changed to work on per-VMA from
globally. So that the different access patterns of the different VMAs
could be distinguished, and the different readahead policy could be
applied accordingly. The original core readahead detection and scaling
algorithm is reused, because it is an effect algorithm to detect the
space locality.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device:
NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:36 +03:00
static unsigned int __swapin_nr_pages ( unsigned long prev_offset ,
unsigned long offset ,
int hits ,
int max_pages ,
int prev_win )
swap: add a simple detector for inappropriate swapin readahead
This is a patch to improve swap readahead algorithm. It's from Hugh and
I slightly changed it.
Hugh's original changelog:
swapin readahead does a blind readahead, whether or not the swapin is
sequential. This may be ok on harddisk, because large reads have
relatively small costs, and if the readahead pages are unneeded they can
be reclaimed easily - though, what if their allocation forced reclaim of
useful pages? But on SSD devices large reads are more expensive than
small ones: if the readahead pages are unneeded, reading them in caused
significant overhead.
This patch adds very simplistic random read detection. Stealing the
PageReadahead technique from Konstantin Khlebnikov's patch, avoiding the
vma/anon_vma sophistications of Shaohua Li's patch, swapin_nr_pages()
simply looks at readahead's current success rate, and narrows or widens
its readahead window accordingly. There is little science to its
heuristic: it's about as stupid as can be whilst remaining effective.
The table below shows elapsed times (in centiseconds) when running a
single repetitive swapping load across a 1000MB mapping in 900MB ram
with 1GB swap (the harddisk tests had taken painfully too long when I
used mem=500M, but SSD shows similar results for that).
Vanilla is the 3.6-rc7 kernel on which I started; Shaohua denotes his
Sep 3 patch in mmotm and linux-next; HughOld denotes my Oct 1 patch
which Shaohua showed to be defective; HughNew this Nov 14 patch, with
page_cluster as usual at default of 3 (8-page reads); HughPC4 this same
patch with page_cluster 4 (16-page reads); HughPC0 with page_cluster 0
(1-page reads: no readahead).
HDD for swapping to harddisk, SSD for swapping to VertexII SSD. Seq for
sequential access to the mapping, cycling five times around; Rand for
the same number of random touches. Anon for a MAP_PRIVATE anon mapping;
Shmem for a MAP_SHARED anon mapping, equivalent to tmpfs.
One weakness of Shaohua's vma/anon_vma approach was that it did not
optimize Shmem: seen below. Konstantin's approach was perhaps mistuned,
50% slower on Seq: did not compete and is not shown below.
HDD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0
Seq Anon 73921 76210 75611 76904 78191 121542
Seq Shmem 73601 73176 73855 72947 74543 118322
Rand Anon 895392 831243 871569 845197 846496 841680
Rand Shmem 1058375 1053486 827935 764955 764376 756489
SSD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0
Seq Anon 24634 24198 24673 25107 21614 70018
Seq Shmem 24959 24932 25052 25703 22030 69678
Rand Anon 43014 26146 28075 25989 26935 25901
Rand Shmem 45349 45215 28249 24268 24138 24332
These tests are, of course, two extremes of a very simple case: under
heavier mixed loads I've not yet observed any consistent improvement or
degradation, and wider testing would be welcome.
Shaohua Li:
Test shows Vanilla is slightly better in sequential workload than Hugh's
patch. I observed with Hugh's patch sometimes the readahead size is
shrinked too fast (from 8 to 1 immediately) in sequential workload if
there is no hit. And in such case, continuing doing readahead is good
actually.
I don't prepare a sophisticated algorithm for the sequential workload
because so far we can't guarantee sequential accessed pages are swap out
sequentially. So I slightly change Hugh's heuristic - don't shrink
readahead size too fast.
Here is my test result (unit second, 3 runs average):
Vanilla Hugh New
Seq 356 370 360
Random 4525 2447 2444
Attached graph is the swapin/swapout throughput I collected with 'vmstat
2'. The first part is running a random workload (till around 1200 of
the x-axis) and the second part is running a sequential workload.
swapin and swapout throughput are almost identical in steady state in
both workloads. These are expected behavior. while in Vanilla, swapin
is much bigger than swapout especially in random workload (because wrong
readahead).
Original patches by: Shaohua Li and Konstantin Khlebnikov.
[fengguang.wu@intel.com: swapin_nr_pages() can be static]
Signed-off-by: Hugh Dickins <hughd@google.com>
Signed-off-by: Shaohua Li <shli@fusionio.com>
Signed-off-by: Fengguang Wu <fengguang.wu@intel.com>
Cc: Rik van Riel <riel@redhat.com>
Cc: Wu Fengguang <fengguang.wu@intel.com>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Konstantin Khlebnikov <khlebnikov@openvz.org>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2014-02-07 00:04:21 +04:00
{
mm, swap: VMA based swap readahead
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory. And the different tasks in the system may have different access
patterns, which makes the global space locality estimation incorrect.
In this patch, when page fault occurs, the virtual pages near the fault
address will be readahead instead of the swap slots near the fault swap
slot in swap device. This avoid to readahead the unrelated swap slots.
At the same time, the swap readahead is changed to work on per-VMA from
globally. So that the different access patterns of the different VMAs
could be distinguished, and the different readahead policy could be
applied accordingly. The original core readahead detection and scaling
algorithm is reused, because it is an effect algorithm to detect the
space locality.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device:
NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:36 +03:00
unsigned int pages , last_ra ;
swap: add a simple detector for inappropriate swapin readahead
This is a patch to improve swap readahead algorithm. It's from Hugh and
I slightly changed it.
Hugh's original changelog:
swapin readahead does a blind readahead, whether or not the swapin is
sequential. This may be ok on harddisk, because large reads have
relatively small costs, and if the readahead pages are unneeded they can
be reclaimed easily - though, what if their allocation forced reclaim of
useful pages? But on SSD devices large reads are more expensive than
small ones: if the readahead pages are unneeded, reading them in caused
significant overhead.
This patch adds very simplistic random read detection. Stealing the
PageReadahead technique from Konstantin Khlebnikov's patch, avoiding the
vma/anon_vma sophistications of Shaohua Li's patch, swapin_nr_pages()
simply looks at readahead's current success rate, and narrows or widens
its readahead window accordingly. There is little science to its
heuristic: it's about as stupid as can be whilst remaining effective.
The table below shows elapsed times (in centiseconds) when running a
single repetitive swapping load across a 1000MB mapping in 900MB ram
with 1GB swap (the harddisk tests had taken painfully too long when I
used mem=500M, but SSD shows similar results for that).
Vanilla is the 3.6-rc7 kernel on which I started; Shaohua denotes his
Sep 3 patch in mmotm and linux-next; HughOld denotes my Oct 1 patch
which Shaohua showed to be defective; HughNew this Nov 14 patch, with
page_cluster as usual at default of 3 (8-page reads); HughPC4 this same
patch with page_cluster 4 (16-page reads); HughPC0 with page_cluster 0
(1-page reads: no readahead).
HDD for swapping to harddisk, SSD for swapping to VertexII SSD. Seq for
sequential access to the mapping, cycling five times around; Rand for
the same number of random touches. Anon for a MAP_PRIVATE anon mapping;
Shmem for a MAP_SHARED anon mapping, equivalent to tmpfs.
One weakness of Shaohua's vma/anon_vma approach was that it did not
optimize Shmem: seen below. Konstantin's approach was perhaps mistuned,
50% slower on Seq: did not compete and is not shown below.
HDD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0
Seq Anon 73921 76210 75611 76904 78191 121542
Seq Shmem 73601 73176 73855 72947 74543 118322
Rand Anon 895392 831243 871569 845197 846496 841680
Rand Shmem 1058375 1053486 827935 764955 764376 756489
SSD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0
Seq Anon 24634 24198 24673 25107 21614 70018
Seq Shmem 24959 24932 25052 25703 22030 69678
Rand Anon 43014 26146 28075 25989 26935 25901
Rand Shmem 45349 45215 28249 24268 24138 24332
These tests are, of course, two extremes of a very simple case: under
heavier mixed loads I've not yet observed any consistent improvement or
degradation, and wider testing would be welcome.
Shaohua Li:
Test shows Vanilla is slightly better in sequential workload than Hugh's
patch. I observed with Hugh's patch sometimes the readahead size is
shrinked too fast (from 8 to 1 immediately) in sequential workload if
there is no hit. And in such case, continuing doing readahead is good
actually.
I don't prepare a sophisticated algorithm for the sequential workload
because so far we can't guarantee sequential accessed pages are swap out
sequentially. So I slightly change Hugh's heuristic - don't shrink
readahead size too fast.
Here is my test result (unit second, 3 runs average):
Vanilla Hugh New
Seq 356 370 360
Random 4525 2447 2444
Attached graph is the swapin/swapout throughput I collected with 'vmstat
2'. The first part is running a random workload (till around 1200 of
the x-axis) and the second part is running a sequential workload.
swapin and swapout throughput are almost identical in steady state in
both workloads. These are expected behavior. while in Vanilla, swapin
is much bigger than swapout especially in random workload (because wrong
readahead).
Original patches by: Shaohua Li and Konstantin Khlebnikov.
[fengguang.wu@intel.com: swapin_nr_pages() can be static]
Signed-off-by: Hugh Dickins <hughd@google.com>
Signed-off-by: Shaohua Li <shli@fusionio.com>
Signed-off-by: Fengguang Wu <fengguang.wu@intel.com>
Cc: Rik van Riel <riel@redhat.com>
Cc: Wu Fengguang <fengguang.wu@intel.com>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Konstantin Khlebnikov <khlebnikov@openvz.org>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2014-02-07 00:04:21 +04:00
/*
* This heuristic has been found to work well on both sequential and
* random loads , swapping to hard disk or to SSD : please don ' t ask
* what the " + 2 " means , it just happens to work well , that ' s all .
*/
mm, swap: VMA based swap readahead
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory. And the different tasks in the system may have different access
patterns, which makes the global space locality estimation incorrect.
In this patch, when page fault occurs, the virtual pages near the fault
address will be readahead instead of the swap slots near the fault swap
slot in swap device. This avoid to readahead the unrelated swap slots.
At the same time, the swap readahead is changed to work on per-VMA from
globally. So that the different access patterns of the different VMAs
could be distinguished, and the different readahead policy could be
applied accordingly. The original core readahead detection and scaling
algorithm is reused, because it is an effect algorithm to detect the
space locality.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device:
NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:36 +03:00
pages = hits + 2 ;
swap: add a simple detector for inappropriate swapin readahead
This is a patch to improve swap readahead algorithm. It's from Hugh and
I slightly changed it.
Hugh's original changelog:
swapin readahead does a blind readahead, whether or not the swapin is
sequential. This may be ok on harddisk, because large reads have
relatively small costs, and if the readahead pages are unneeded they can
be reclaimed easily - though, what if their allocation forced reclaim of
useful pages? But on SSD devices large reads are more expensive than
small ones: if the readahead pages are unneeded, reading them in caused
significant overhead.
This patch adds very simplistic random read detection. Stealing the
PageReadahead technique from Konstantin Khlebnikov's patch, avoiding the
vma/anon_vma sophistications of Shaohua Li's patch, swapin_nr_pages()
simply looks at readahead's current success rate, and narrows or widens
its readahead window accordingly. There is little science to its
heuristic: it's about as stupid as can be whilst remaining effective.
The table below shows elapsed times (in centiseconds) when running a
single repetitive swapping load across a 1000MB mapping in 900MB ram
with 1GB swap (the harddisk tests had taken painfully too long when I
used mem=500M, but SSD shows similar results for that).
Vanilla is the 3.6-rc7 kernel on which I started; Shaohua denotes his
Sep 3 patch in mmotm and linux-next; HughOld denotes my Oct 1 patch
which Shaohua showed to be defective; HughNew this Nov 14 patch, with
page_cluster as usual at default of 3 (8-page reads); HughPC4 this same
patch with page_cluster 4 (16-page reads); HughPC0 with page_cluster 0
(1-page reads: no readahead).
HDD for swapping to harddisk, SSD for swapping to VertexII SSD. Seq for
sequential access to the mapping, cycling five times around; Rand for
the same number of random touches. Anon for a MAP_PRIVATE anon mapping;
Shmem for a MAP_SHARED anon mapping, equivalent to tmpfs.
One weakness of Shaohua's vma/anon_vma approach was that it did not
optimize Shmem: seen below. Konstantin's approach was perhaps mistuned,
50% slower on Seq: did not compete and is not shown below.
HDD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0
Seq Anon 73921 76210 75611 76904 78191 121542
Seq Shmem 73601 73176 73855 72947 74543 118322
Rand Anon 895392 831243 871569 845197 846496 841680
Rand Shmem 1058375 1053486 827935 764955 764376 756489
SSD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0
Seq Anon 24634 24198 24673 25107 21614 70018
Seq Shmem 24959 24932 25052 25703 22030 69678
Rand Anon 43014 26146 28075 25989 26935 25901
Rand Shmem 45349 45215 28249 24268 24138 24332
These tests are, of course, two extremes of a very simple case: under
heavier mixed loads I've not yet observed any consistent improvement or
degradation, and wider testing would be welcome.
Shaohua Li:
Test shows Vanilla is slightly better in sequential workload than Hugh's
patch. I observed with Hugh's patch sometimes the readahead size is
shrinked too fast (from 8 to 1 immediately) in sequential workload if
there is no hit. And in such case, continuing doing readahead is good
actually.
I don't prepare a sophisticated algorithm for the sequential workload
because so far we can't guarantee sequential accessed pages are swap out
sequentially. So I slightly change Hugh's heuristic - don't shrink
readahead size too fast.
Here is my test result (unit second, 3 runs average):
Vanilla Hugh New
Seq 356 370 360
Random 4525 2447 2444
Attached graph is the swapin/swapout throughput I collected with 'vmstat
2'. The first part is running a random workload (till around 1200 of
the x-axis) and the second part is running a sequential workload.
swapin and swapout throughput are almost identical in steady state in
both workloads. These are expected behavior. while in Vanilla, swapin
is much bigger than swapout especially in random workload (because wrong
readahead).
Original patches by: Shaohua Li and Konstantin Khlebnikov.
[fengguang.wu@intel.com: swapin_nr_pages() can be static]
Signed-off-by: Hugh Dickins <hughd@google.com>
Signed-off-by: Shaohua Li <shli@fusionio.com>
Signed-off-by: Fengguang Wu <fengguang.wu@intel.com>
Cc: Rik van Riel <riel@redhat.com>
Cc: Wu Fengguang <fengguang.wu@intel.com>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Konstantin Khlebnikov <khlebnikov@openvz.org>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2014-02-07 00:04:21 +04:00
if ( pages = = 2 ) {
/*
* We can have no readahead hits to judge by : but must not get
* stuck here forever , so check for an adjacent offset instead
* ( and don ' t even bother to check whether swap type is same ) .
*/
if ( offset ! = prev_offset + 1 & & offset ! = prev_offset - 1 )
pages = 1 ;
} else {
unsigned int roundup = 4 ;
while ( roundup < pages )
roundup < < = 1 ;
pages = roundup ;
}
if ( pages > max_pages )
pages = max_pages ;
/* Don't shrink readahead too fast */
mm, swap: VMA based swap readahead
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory. And the different tasks in the system may have different access
patterns, which makes the global space locality estimation incorrect.
In this patch, when page fault occurs, the virtual pages near the fault
address will be readahead instead of the swap slots near the fault swap
slot in swap device. This avoid to readahead the unrelated swap slots.
At the same time, the swap readahead is changed to work on per-VMA from
globally. So that the different access patterns of the different VMAs
could be distinguished, and the different readahead policy could be
applied accordingly. The original core readahead detection and scaling
algorithm is reused, because it is an effect algorithm to detect the
space locality.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device:
NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:36 +03:00
last_ra = prev_win / 2 ;
swap: add a simple detector for inappropriate swapin readahead
This is a patch to improve swap readahead algorithm. It's from Hugh and
I slightly changed it.
Hugh's original changelog:
swapin readahead does a blind readahead, whether or not the swapin is
sequential. This may be ok on harddisk, because large reads have
relatively small costs, and if the readahead pages are unneeded they can
be reclaimed easily - though, what if their allocation forced reclaim of
useful pages? But on SSD devices large reads are more expensive than
small ones: if the readahead pages are unneeded, reading them in caused
significant overhead.
This patch adds very simplistic random read detection. Stealing the
PageReadahead technique from Konstantin Khlebnikov's patch, avoiding the
vma/anon_vma sophistications of Shaohua Li's patch, swapin_nr_pages()
simply looks at readahead's current success rate, and narrows or widens
its readahead window accordingly. There is little science to its
heuristic: it's about as stupid as can be whilst remaining effective.
The table below shows elapsed times (in centiseconds) when running a
single repetitive swapping load across a 1000MB mapping in 900MB ram
with 1GB swap (the harddisk tests had taken painfully too long when I
used mem=500M, but SSD shows similar results for that).
Vanilla is the 3.6-rc7 kernel on which I started; Shaohua denotes his
Sep 3 patch in mmotm and linux-next; HughOld denotes my Oct 1 patch
which Shaohua showed to be defective; HughNew this Nov 14 patch, with
page_cluster as usual at default of 3 (8-page reads); HughPC4 this same
patch with page_cluster 4 (16-page reads); HughPC0 with page_cluster 0
(1-page reads: no readahead).
HDD for swapping to harddisk, SSD for swapping to VertexII SSD. Seq for
sequential access to the mapping, cycling five times around; Rand for
the same number of random touches. Anon for a MAP_PRIVATE anon mapping;
Shmem for a MAP_SHARED anon mapping, equivalent to tmpfs.
One weakness of Shaohua's vma/anon_vma approach was that it did not
optimize Shmem: seen below. Konstantin's approach was perhaps mistuned,
50% slower on Seq: did not compete and is not shown below.
HDD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0
Seq Anon 73921 76210 75611 76904 78191 121542
Seq Shmem 73601 73176 73855 72947 74543 118322
Rand Anon 895392 831243 871569 845197 846496 841680
Rand Shmem 1058375 1053486 827935 764955 764376 756489
SSD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0
Seq Anon 24634 24198 24673 25107 21614 70018
Seq Shmem 24959 24932 25052 25703 22030 69678
Rand Anon 43014 26146 28075 25989 26935 25901
Rand Shmem 45349 45215 28249 24268 24138 24332
These tests are, of course, two extremes of a very simple case: under
heavier mixed loads I've not yet observed any consistent improvement or
degradation, and wider testing would be welcome.
Shaohua Li:
Test shows Vanilla is slightly better in sequential workload than Hugh's
patch. I observed with Hugh's patch sometimes the readahead size is
shrinked too fast (from 8 to 1 immediately) in sequential workload if
there is no hit. And in such case, continuing doing readahead is good
actually.
I don't prepare a sophisticated algorithm for the sequential workload
because so far we can't guarantee sequential accessed pages are swap out
sequentially. So I slightly change Hugh's heuristic - don't shrink
readahead size too fast.
Here is my test result (unit second, 3 runs average):
Vanilla Hugh New
Seq 356 370 360
Random 4525 2447 2444
Attached graph is the swapin/swapout throughput I collected with 'vmstat
2'. The first part is running a random workload (till around 1200 of
the x-axis) and the second part is running a sequential workload.
swapin and swapout throughput are almost identical in steady state in
both workloads. These are expected behavior. while in Vanilla, swapin
is much bigger than swapout especially in random workload (because wrong
readahead).
Original patches by: Shaohua Li and Konstantin Khlebnikov.
[fengguang.wu@intel.com: swapin_nr_pages() can be static]
Signed-off-by: Hugh Dickins <hughd@google.com>
Signed-off-by: Shaohua Li <shli@fusionio.com>
Signed-off-by: Fengguang Wu <fengguang.wu@intel.com>
Cc: Rik van Riel <riel@redhat.com>
Cc: Wu Fengguang <fengguang.wu@intel.com>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Konstantin Khlebnikov <khlebnikov@openvz.org>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2014-02-07 00:04:21 +04:00
if ( pages < last_ra )
pages = last_ra ;
mm, swap: VMA based swap readahead
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory. And the different tasks in the system may have different access
patterns, which makes the global space locality estimation incorrect.
In this patch, when page fault occurs, the virtual pages near the fault
address will be readahead instead of the swap slots near the fault swap
slot in swap device. This avoid to readahead the unrelated swap slots.
At the same time, the swap readahead is changed to work on per-VMA from
globally. So that the different access patterns of the different VMAs
could be distinguished, and the different readahead policy could be
applied accordingly. The original core readahead detection and scaling
algorithm is reused, because it is an effect algorithm to detect the
space locality.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device:
NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:36 +03:00
return pages ;
}
static unsigned long swapin_nr_pages ( unsigned long offset )
{
static unsigned long prev_offset ;
unsigned int hits , pages , max_pages ;
static atomic_t last_readahead_pages ;
max_pages = 1 < < READ_ONCE ( page_cluster ) ;
if ( max_pages < = 1 )
return 1 ;
hits = atomic_xchg ( & swapin_readahead_hits , 0 ) ;
2020-06-02 07:48:40 +03:00
pages = __swapin_nr_pages ( READ_ONCE ( prev_offset ) , offset , hits ,
max_pages ,
mm, swap: VMA based swap readahead
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory. And the different tasks in the system may have different access
patterns, which makes the global space locality estimation incorrect.
In this patch, when page fault occurs, the virtual pages near the fault
address will be readahead instead of the swap slots near the fault swap
slot in swap device. This avoid to readahead the unrelated swap slots.
At the same time, the swap readahead is changed to work on per-VMA from
globally. So that the different access patterns of the different VMAs
could be distinguished, and the different readahead policy could be
applied accordingly. The original core readahead detection and scaling
algorithm is reused, because it is an effect algorithm to detect the
space locality.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device:
NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:36 +03:00
atomic_read ( & last_readahead_pages ) ) ;
if ( ! hits )
2020-06-02 07:48:40 +03:00
WRITE_ONCE ( prev_offset , offset ) ;
swap: add a simple detector for inappropriate swapin readahead
This is a patch to improve swap readahead algorithm. It's from Hugh and
I slightly changed it.
Hugh's original changelog:
swapin readahead does a blind readahead, whether or not the swapin is
sequential. This may be ok on harddisk, because large reads have
relatively small costs, and if the readahead pages are unneeded they can
be reclaimed easily - though, what if their allocation forced reclaim of
useful pages? But on SSD devices large reads are more expensive than
small ones: if the readahead pages are unneeded, reading them in caused
significant overhead.
This patch adds very simplistic random read detection. Stealing the
PageReadahead technique from Konstantin Khlebnikov's patch, avoiding the
vma/anon_vma sophistications of Shaohua Li's patch, swapin_nr_pages()
simply looks at readahead's current success rate, and narrows or widens
its readahead window accordingly. There is little science to its
heuristic: it's about as stupid as can be whilst remaining effective.
The table below shows elapsed times (in centiseconds) when running a
single repetitive swapping load across a 1000MB mapping in 900MB ram
with 1GB swap (the harddisk tests had taken painfully too long when I
used mem=500M, but SSD shows similar results for that).
Vanilla is the 3.6-rc7 kernel on which I started; Shaohua denotes his
Sep 3 patch in mmotm and linux-next; HughOld denotes my Oct 1 patch
which Shaohua showed to be defective; HughNew this Nov 14 patch, with
page_cluster as usual at default of 3 (8-page reads); HughPC4 this same
patch with page_cluster 4 (16-page reads); HughPC0 with page_cluster 0
(1-page reads: no readahead).
HDD for swapping to harddisk, SSD for swapping to VertexII SSD. Seq for
sequential access to the mapping, cycling five times around; Rand for
the same number of random touches. Anon for a MAP_PRIVATE anon mapping;
Shmem for a MAP_SHARED anon mapping, equivalent to tmpfs.
One weakness of Shaohua's vma/anon_vma approach was that it did not
optimize Shmem: seen below. Konstantin's approach was perhaps mistuned,
50% slower on Seq: did not compete and is not shown below.
HDD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0
Seq Anon 73921 76210 75611 76904 78191 121542
Seq Shmem 73601 73176 73855 72947 74543 118322
Rand Anon 895392 831243 871569 845197 846496 841680
Rand Shmem 1058375 1053486 827935 764955 764376 756489
SSD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0
Seq Anon 24634 24198 24673 25107 21614 70018
Seq Shmem 24959 24932 25052 25703 22030 69678
Rand Anon 43014 26146 28075 25989 26935 25901
Rand Shmem 45349 45215 28249 24268 24138 24332
These tests are, of course, two extremes of a very simple case: under
heavier mixed loads I've not yet observed any consistent improvement or
degradation, and wider testing would be welcome.
Shaohua Li:
Test shows Vanilla is slightly better in sequential workload than Hugh's
patch. I observed with Hugh's patch sometimes the readahead size is
shrinked too fast (from 8 to 1 immediately) in sequential workload if
there is no hit. And in such case, continuing doing readahead is good
actually.
I don't prepare a sophisticated algorithm for the sequential workload
because so far we can't guarantee sequential accessed pages are swap out
sequentially. So I slightly change Hugh's heuristic - don't shrink
readahead size too fast.
Here is my test result (unit second, 3 runs average):
Vanilla Hugh New
Seq 356 370 360
Random 4525 2447 2444
Attached graph is the swapin/swapout throughput I collected with 'vmstat
2'. The first part is running a random workload (till around 1200 of
the x-axis) and the second part is running a sequential workload.
swapin and swapout throughput are almost identical in steady state in
both workloads. These are expected behavior. while in Vanilla, swapin
is much bigger than swapout especially in random workload (because wrong
readahead).
Original patches by: Shaohua Li and Konstantin Khlebnikov.
[fengguang.wu@intel.com: swapin_nr_pages() can be static]
Signed-off-by: Hugh Dickins <hughd@google.com>
Signed-off-by: Shaohua Li <shli@fusionio.com>
Signed-off-by: Fengguang Wu <fengguang.wu@intel.com>
Cc: Rik van Riel <riel@redhat.com>
Cc: Wu Fengguang <fengguang.wu@intel.com>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Konstantin Khlebnikov <khlebnikov@openvz.org>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2014-02-07 00:04:21 +04:00
atomic_set ( & last_readahead_pages , pages ) ;
return pages ;
}
2008-02-05 09:28:41 +03:00
/**
2018-04-06 02:23:42 +03:00
* swap_cluster_readahead - swap in pages in hope we need them soon
2008-02-05 09:28:41 +03:00
* @ entry : swap entry of this memory
2008-03-20 03:00:40 +03:00
* @ gfp_mask : memory allocation flags
2018-04-06 02:23:42 +03:00
* @ vmf : fault information
2008-02-05 09:28:41 +03:00
*
* Returns the struct page for entry and addr , after queueing swapin .
*
* Primitive swap readahead code . We simply read an aligned block of
* ( 1 < < page_cluster ) entries in the swap area . This method is chosen
* because it doesn ' t cost us any seek time . We also make sure to queue
* the ' original ' request together with the readahead ones . . .
*
* This has been extended to use the NUMA policies from the mm triggering
* the readahead .
*
2020-06-09 07:33:54 +03:00
* Caller must hold read mmap_lock if vmf - > vma is not NULL .
2008-02-05 09:28:41 +03:00
*/
2018-04-06 02:23:42 +03:00
struct page * swap_cluster_readahead ( swp_entry_t entry , gfp_t gfp_mask ,
struct vm_fault * vmf )
2008-02-05 09:28:41 +03:00
{
struct page * page ;
swap: add a simple detector for inappropriate swapin readahead
This is a patch to improve swap readahead algorithm. It's from Hugh and
I slightly changed it.
Hugh's original changelog:
swapin readahead does a blind readahead, whether or not the swapin is
sequential. This may be ok on harddisk, because large reads have
relatively small costs, and if the readahead pages are unneeded they can
be reclaimed easily - though, what if their allocation forced reclaim of
useful pages? But on SSD devices large reads are more expensive than
small ones: if the readahead pages are unneeded, reading them in caused
significant overhead.
This patch adds very simplistic random read detection. Stealing the
PageReadahead technique from Konstantin Khlebnikov's patch, avoiding the
vma/anon_vma sophistications of Shaohua Li's patch, swapin_nr_pages()
simply looks at readahead's current success rate, and narrows or widens
its readahead window accordingly. There is little science to its
heuristic: it's about as stupid as can be whilst remaining effective.
The table below shows elapsed times (in centiseconds) when running a
single repetitive swapping load across a 1000MB mapping in 900MB ram
with 1GB swap (the harddisk tests had taken painfully too long when I
used mem=500M, but SSD shows similar results for that).
Vanilla is the 3.6-rc7 kernel on which I started; Shaohua denotes his
Sep 3 patch in mmotm and linux-next; HughOld denotes my Oct 1 patch
which Shaohua showed to be defective; HughNew this Nov 14 patch, with
page_cluster as usual at default of 3 (8-page reads); HughPC4 this same
patch with page_cluster 4 (16-page reads); HughPC0 with page_cluster 0
(1-page reads: no readahead).
HDD for swapping to harddisk, SSD for swapping to VertexII SSD. Seq for
sequential access to the mapping, cycling five times around; Rand for
the same number of random touches. Anon for a MAP_PRIVATE anon mapping;
Shmem for a MAP_SHARED anon mapping, equivalent to tmpfs.
One weakness of Shaohua's vma/anon_vma approach was that it did not
optimize Shmem: seen below. Konstantin's approach was perhaps mistuned,
50% slower on Seq: did not compete and is not shown below.
HDD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0
Seq Anon 73921 76210 75611 76904 78191 121542
Seq Shmem 73601 73176 73855 72947 74543 118322
Rand Anon 895392 831243 871569 845197 846496 841680
Rand Shmem 1058375 1053486 827935 764955 764376 756489
SSD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0
Seq Anon 24634 24198 24673 25107 21614 70018
Seq Shmem 24959 24932 25052 25703 22030 69678
Rand Anon 43014 26146 28075 25989 26935 25901
Rand Shmem 45349 45215 28249 24268 24138 24332
These tests are, of course, two extremes of a very simple case: under
heavier mixed loads I've not yet observed any consistent improvement or
degradation, and wider testing would be welcome.
Shaohua Li:
Test shows Vanilla is slightly better in sequential workload than Hugh's
patch. I observed with Hugh's patch sometimes the readahead size is
shrinked too fast (from 8 to 1 immediately) in sequential workload if
there is no hit. And in such case, continuing doing readahead is good
actually.
I don't prepare a sophisticated algorithm for the sequential workload
because so far we can't guarantee sequential accessed pages are swap out
sequentially. So I slightly change Hugh's heuristic - don't shrink
readahead size too fast.
Here is my test result (unit second, 3 runs average):
Vanilla Hugh New
Seq 356 370 360
Random 4525 2447 2444
Attached graph is the swapin/swapout throughput I collected with 'vmstat
2'. The first part is running a random workload (till around 1200 of
the x-axis) and the second part is running a sequential workload.
swapin and swapout throughput are almost identical in steady state in
both workloads. These are expected behavior. while in Vanilla, swapin
is much bigger than swapout especially in random workload (because wrong
readahead).
Original patches by: Shaohua Li and Konstantin Khlebnikov.
[fengguang.wu@intel.com: swapin_nr_pages() can be static]
Signed-off-by: Hugh Dickins <hughd@google.com>
Signed-off-by: Shaohua Li <shli@fusionio.com>
Signed-off-by: Fengguang Wu <fengguang.wu@intel.com>
Cc: Rik van Riel <riel@redhat.com>
Cc: Wu Fengguang <fengguang.wu@intel.com>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Konstantin Khlebnikov <khlebnikov@openvz.org>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2014-02-07 00:04:21 +04:00
unsigned long entry_offset = swp_offset ( entry ) ;
unsigned long offset = entry_offset ;
2012-03-22 03:33:50 +04:00
unsigned long start_offset , end_offset ;
swap: add a simple detector for inappropriate swapin readahead
This is a patch to improve swap readahead algorithm. It's from Hugh and
I slightly changed it.
Hugh's original changelog:
swapin readahead does a blind readahead, whether or not the swapin is
sequential. This may be ok on harddisk, because large reads have
relatively small costs, and if the readahead pages are unneeded they can
be reclaimed easily - though, what if their allocation forced reclaim of
useful pages? But on SSD devices large reads are more expensive than
small ones: if the readahead pages are unneeded, reading them in caused
significant overhead.
This patch adds very simplistic random read detection. Stealing the
PageReadahead technique from Konstantin Khlebnikov's patch, avoiding the
vma/anon_vma sophistications of Shaohua Li's patch, swapin_nr_pages()
simply looks at readahead's current success rate, and narrows or widens
its readahead window accordingly. There is little science to its
heuristic: it's about as stupid as can be whilst remaining effective.
The table below shows elapsed times (in centiseconds) when running a
single repetitive swapping load across a 1000MB mapping in 900MB ram
with 1GB swap (the harddisk tests had taken painfully too long when I
used mem=500M, but SSD shows similar results for that).
Vanilla is the 3.6-rc7 kernel on which I started; Shaohua denotes his
Sep 3 patch in mmotm and linux-next; HughOld denotes my Oct 1 patch
which Shaohua showed to be defective; HughNew this Nov 14 patch, with
page_cluster as usual at default of 3 (8-page reads); HughPC4 this same
patch with page_cluster 4 (16-page reads); HughPC0 with page_cluster 0
(1-page reads: no readahead).
HDD for swapping to harddisk, SSD for swapping to VertexII SSD. Seq for
sequential access to the mapping, cycling five times around; Rand for
the same number of random touches. Anon for a MAP_PRIVATE anon mapping;
Shmem for a MAP_SHARED anon mapping, equivalent to tmpfs.
One weakness of Shaohua's vma/anon_vma approach was that it did not
optimize Shmem: seen below. Konstantin's approach was perhaps mistuned,
50% slower on Seq: did not compete and is not shown below.
HDD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0
Seq Anon 73921 76210 75611 76904 78191 121542
Seq Shmem 73601 73176 73855 72947 74543 118322
Rand Anon 895392 831243 871569 845197 846496 841680
Rand Shmem 1058375 1053486 827935 764955 764376 756489
SSD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0
Seq Anon 24634 24198 24673 25107 21614 70018
Seq Shmem 24959 24932 25052 25703 22030 69678
Rand Anon 43014 26146 28075 25989 26935 25901
Rand Shmem 45349 45215 28249 24268 24138 24332
These tests are, of course, two extremes of a very simple case: under
heavier mixed loads I've not yet observed any consistent improvement or
degradation, and wider testing would be welcome.
Shaohua Li:
Test shows Vanilla is slightly better in sequential workload than Hugh's
patch. I observed with Hugh's patch sometimes the readahead size is
shrinked too fast (from 8 to 1 immediately) in sequential workload if
there is no hit. And in such case, continuing doing readahead is good
actually.
I don't prepare a sophisticated algorithm for the sequential workload
because so far we can't guarantee sequential accessed pages are swap out
sequentially. So I slightly change Hugh's heuristic - don't shrink
readahead size too fast.
Here is my test result (unit second, 3 runs average):
Vanilla Hugh New
Seq 356 370 360
Random 4525 2447 2444
Attached graph is the swapin/swapout throughput I collected with 'vmstat
2'. The first part is running a random workload (till around 1200 of
the x-axis) and the second part is running a sequential workload.
swapin and swapout throughput are almost identical in steady state in
both workloads. These are expected behavior. while in Vanilla, swapin
is much bigger than swapout especially in random workload (because wrong
readahead).
Original patches by: Shaohua Li and Konstantin Khlebnikov.
[fengguang.wu@intel.com: swapin_nr_pages() can be static]
Signed-off-by: Hugh Dickins <hughd@google.com>
Signed-off-by: Shaohua Li <shli@fusionio.com>
Signed-off-by: Fengguang Wu <fengguang.wu@intel.com>
Cc: Rik van Riel <riel@redhat.com>
Cc: Wu Fengguang <fengguang.wu@intel.com>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Konstantin Khlebnikov <khlebnikov@openvz.org>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2014-02-07 00:04:21 +04:00
unsigned long mask ;
2017-11-16 04:33:15 +03:00
struct swap_info_struct * si = swp_swap_info ( entry ) ;
swap: allow swap readahead to be merged
Swap readahead works fine, but the I/O to disk is almost always done in
page size requests, despite the fact that readahead submits
1<<page-cluster pages at a time.
On older kernels the old per device plugging behavior might have captured
this and merged the requests, but currently all comes down to much more
I/Os than required.
On a single device this might not be an issue, but as soon as a server
runs on shared san resources savin I/Os not only improves swapin
throughput but also provides a lower resource utilization.
With a load running KVM in a lot of memory overcommitment (the hot memory
is 1.5 times the host memory) swapping throughput improves significantly
and the lead feels more responsive as well as achieves more throughput.
In a test setup with 16 swap disks running blocktrace on one of those disks
shows the improved merging:
Prior:
Reads Queued: 560,888, 2,243MiB Writes Queued: 226,242, 904,968KiB
Read Dispatches: 544,701, 2,243MiB Write Dispatches: 159,318, 904,968KiB
Reads Requeued: 0 Writes Requeued: 0
Reads Completed: 544,716, 2,243MiB Writes Completed: 159,321, 904,980KiB
Read Merges: 16,187, 64,748KiB Write Merges: 61,744, 246,976KiB
IO unplugs: 149,614 Timer unplugs: 2,940
With the patch:
Reads Queued: 734,315, 2,937MiB Writes Queued: 300,188, 1,200MiB
Read Dispatches: 214,972, 2,937MiB Write Dispatches: 215,176, 1,200MiB
Reads Requeued: 0 Writes Requeued: 0
Reads Completed: 214,971, 2,937MiB Writes Completed: 215,177, 1,200MiB
Read Merges: 519,343, 2,077MiB Write Merges: 73,325, 293,300KiB
IO unplugs: 337,130 Timer unplugs: 11,184
I got ~10% to ~40% more throughput in my cases and at the same time much
lower cpu consumption when broken down per transferred kilobyte (the
majority of that due to saved interrupts and better cache handling). In a
shared SAN others might get an additional benefit as well, because this
now causes less protocol overhead.
Signed-off-by: Christian Ehrhardt <ehrhardt@linux.vnet.ibm.com>
Acked-by: Rik van Riel <riel@redhat.com>
Acked-by: Jens Axboe <axboe@kernel.dk>
Reviewed-by: Minchan Kim <minchan@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2012-08-01 03:41:44 +04:00
struct blk_plug plug ;
2017-09-07 02:24:33 +03:00
bool do_poll = true , page_allocated ;
2018-04-06 02:23:42 +03:00
struct vm_area_struct * vma = vmf - > vma ;
unsigned long addr = vmf - > address ;
2008-02-05 09:28:41 +03:00
swap: add a simple detector for inappropriate swapin readahead
This is a patch to improve swap readahead algorithm. It's from Hugh and
I slightly changed it.
Hugh's original changelog:
swapin readahead does a blind readahead, whether or not the swapin is
sequential. This may be ok on harddisk, because large reads have
relatively small costs, and if the readahead pages are unneeded they can
be reclaimed easily - though, what if their allocation forced reclaim of
useful pages? But on SSD devices large reads are more expensive than
small ones: if the readahead pages are unneeded, reading them in caused
significant overhead.
This patch adds very simplistic random read detection. Stealing the
PageReadahead technique from Konstantin Khlebnikov's patch, avoiding the
vma/anon_vma sophistications of Shaohua Li's patch, swapin_nr_pages()
simply looks at readahead's current success rate, and narrows or widens
its readahead window accordingly. There is little science to its
heuristic: it's about as stupid as can be whilst remaining effective.
The table below shows elapsed times (in centiseconds) when running a
single repetitive swapping load across a 1000MB mapping in 900MB ram
with 1GB swap (the harddisk tests had taken painfully too long when I
used mem=500M, but SSD shows similar results for that).
Vanilla is the 3.6-rc7 kernel on which I started; Shaohua denotes his
Sep 3 patch in mmotm and linux-next; HughOld denotes my Oct 1 patch
which Shaohua showed to be defective; HughNew this Nov 14 patch, with
page_cluster as usual at default of 3 (8-page reads); HughPC4 this same
patch with page_cluster 4 (16-page reads); HughPC0 with page_cluster 0
(1-page reads: no readahead).
HDD for swapping to harddisk, SSD for swapping to VertexII SSD. Seq for
sequential access to the mapping, cycling five times around; Rand for
the same number of random touches. Anon for a MAP_PRIVATE anon mapping;
Shmem for a MAP_SHARED anon mapping, equivalent to tmpfs.
One weakness of Shaohua's vma/anon_vma approach was that it did not
optimize Shmem: seen below. Konstantin's approach was perhaps mistuned,
50% slower on Seq: did not compete and is not shown below.
HDD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0
Seq Anon 73921 76210 75611 76904 78191 121542
Seq Shmem 73601 73176 73855 72947 74543 118322
Rand Anon 895392 831243 871569 845197 846496 841680
Rand Shmem 1058375 1053486 827935 764955 764376 756489
SSD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0
Seq Anon 24634 24198 24673 25107 21614 70018
Seq Shmem 24959 24932 25052 25703 22030 69678
Rand Anon 43014 26146 28075 25989 26935 25901
Rand Shmem 45349 45215 28249 24268 24138 24332
These tests are, of course, two extremes of a very simple case: under
heavier mixed loads I've not yet observed any consistent improvement or
degradation, and wider testing would be welcome.
Shaohua Li:
Test shows Vanilla is slightly better in sequential workload than Hugh's
patch. I observed with Hugh's patch sometimes the readahead size is
shrinked too fast (from 8 to 1 immediately) in sequential workload if
there is no hit. And in such case, continuing doing readahead is good
actually.
I don't prepare a sophisticated algorithm for the sequential workload
because so far we can't guarantee sequential accessed pages are swap out
sequentially. So I slightly change Hugh's heuristic - don't shrink
readahead size too fast.
Here is my test result (unit second, 3 runs average):
Vanilla Hugh New
Seq 356 370 360
Random 4525 2447 2444
Attached graph is the swapin/swapout throughput I collected with 'vmstat
2'. The first part is running a random workload (till around 1200 of
the x-axis) and the second part is running a sequential workload.
swapin and swapout throughput are almost identical in steady state in
both workloads. These are expected behavior. while in Vanilla, swapin
is much bigger than swapout especially in random workload (because wrong
readahead).
Original patches by: Shaohua Li and Konstantin Khlebnikov.
[fengguang.wu@intel.com: swapin_nr_pages() can be static]
Signed-off-by: Hugh Dickins <hughd@google.com>
Signed-off-by: Shaohua Li <shli@fusionio.com>
Signed-off-by: Fengguang Wu <fengguang.wu@intel.com>
Cc: Rik van Riel <riel@redhat.com>
Cc: Wu Fengguang <fengguang.wu@intel.com>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Konstantin Khlebnikov <khlebnikov@openvz.org>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2014-02-07 00:04:21 +04:00
mask = swapin_nr_pages ( offset ) - 1 ;
if ( ! mask )
goto skip ;
swap: add block io poll in swapin path
For fast flash disk, async IO could introduce overhead because of
context switch. block-mq now supports IO poll, which improves
performance and latency a lot. swapin is a good place to use this
technique, because the task is waiting for the swapin page to continue
execution.
In my virtual machine, directly read 4k data from a NVMe with iopoll is
about 60% better than that without poll. With iopoll support in swapin
patch, my microbenchmark (a task does random memory write) is about
10%~25% faster. CPU utilization increases a lot though, 2x and even 3x
CPU utilization. This will depend on disk speed.
While iopoll in swapin isn't intended for all usage cases, it's a win
for latency sensistive workloads with high speed swap disk. block layer
has knob to control poll in runtime. If poll isn't enabled in block
layer, there should be no noticeable change in swapin.
I got a chance to run the same test in a NVMe with DRAM as the media.
In simple fio IO test, blkpoll boosts 50% performance in single thread
test and ~20% in 8 threads test. So this is the base line. In above
swap test, blkpoll boosts ~27% performance in single thread test.
blkpoll uses 2x CPU time though.
If we enable hybid polling, the performance gain has very slight drop
but CPU time is only 50% worse than that without blkpoll. Also we can
adjust parameter of hybid poll, with it, the CPU time penality is
reduced further. In 8 threads test, blkpoll doesn't help though. The
performance is similar to that without blkpoll, but cpu utilization is
similar too. There is lock contention in swap path. The cpu time
spending on blkpoll isn't high. So overall, blkpoll swapin isn't worse
than that without it.
The swapin readahead might read several pages in in the same time and
form a big IO request. Since the IO will take longer time, it doesn't
make sense to do poll, so the patch only does iopoll for single page
swapin.
[akpm@linux-foundation.org: coding-style fixes]
Link: http://lkml.kernel.org/r/070c3c3e40b711e7b1390002c991e86a-b5408f0@7511894063d3764ff01ea8111f5a004d7dd700ed078797c204a24e620ddb965c
Signed-off-by: Shaohua Li <shli@fb.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Huang Ying <ying.huang@intel.com>
Cc: Jens Axboe <axboe@fb.com>
Cc: Hugh Dickins <hughd@google.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-11 01:47:11 +03:00
do_poll = false ;
2012-03-22 03:33:50 +04:00
/* Read a page_cluster sized and aligned cluster around offset. */
start_offset = offset & ~ mask ;
end_offset = offset | mask ;
if ( ! start_offset ) /* First page is swap header. */
start_offset + + ;
2017-11-16 04:33:15 +03:00
if ( end_offset > = si - > max )
end_offset = si - > max - 1 ;
2012-03-22 03:33:50 +04:00
swap: allow swap readahead to be merged
Swap readahead works fine, but the I/O to disk is almost always done in
page size requests, despite the fact that readahead submits
1<<page-cluster pages at a time.
On older kernels the old per device plugging behavior might have captured
this and merged the requests, but currently all comes down to much more
I/Os than required.
On a single device this might not be an issue, but as soon as a server
runs on shared san resources savin I/Os not only improves swapin
throughput but also provides a lower resource utilization.
With a load running KVM in a lot of memory overcommitment (the hot memory
is 1.5 times the host memory) swapping throughput improves significantly
and the lead feels more responsive as well as achieves more throughput.
In a test setup with 16 swap disks running blocktrace on one of those disks
shows the improved merging:
Prior:
Reads Queued: 560,888, 2,243MiB Writes Queued: 226,242, 904,968KiB
Read Dispatches: 544,701, 2,243MiB Write Dispatches: 159,318, 904,968KiB
Reads Requeued: 0 Writes Requeued: 0
Reads Completed: 544,716, 2,243MiB Writes Completed: 159,321, 904,980KiB
Read Merges: 16,187, 64,748KiB Write Merges: 61,744, 246,976KiB
IO unplugs: 149,614 Timer unplugs: 2,940
With the patch:
Reads Queued: 734,315, 2,937MiB Writes Queued: 300,188, 1,200MiB
Read Dispatches: 214,972, 2,937MiB Write Dispatches: 215,176, 1,200MiB
Reads Requeued: 0 Writes Requeued: 0
Reads Completed: 214,971, 2,937MiB Writes Completed: 215,177, 1,200MiB
Read Merges: 519,343, 2,077MiB Write Merges: 73,325, 293,300KiB
IO unplugs: 337,130 Timer unplugs: 11,184
I got ~10% to ~40% more throughput in my cases and at the same time much
lower cpu consumption when broken down per transferred kilobyte (the
majority of that due to saved interrupts and better cache handling). In a
shared SAN others might get an additional benefit as well, because this
now causes less protocol overhead.
Signed-off-by: Christian Ehrhardt <ehrhardt@linux.vnet.ibm.com>
Acked-by: Rik van Riel <riel@redhat.com>
Acked-by: Jens Axboe <axboe@kernel.dk>
Reviewed-by: Minchan Kim <minchan@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2012-08-01 03:41:44 +04:00
blk_start_plug ( & plug ) ;
2012-03-22 03:33:50 +04:00
for ( offset = start_offset ; offset < = end_offset ; offset + + ) {
2008-02-05 09:28:41 +03:00
/* Ok, do the async read-ahead now */
2017-09-07 02:24:33 +03:00
page = __read_swap_cache_async (
swp_entry ( swp_type ( entry ) , offset ) ,
gfp_mask , vma , addr , & page_allocated ) ;
2008-02-05 09:28:41 +03:00
if ( ! page )
2012-03-22 03:33:50 +04:00
continue ;
2017-09-07 02:24:33 +03:00
if ( page_allocated ) {
swap_readpage ( page , false ) ;
2018-04-06 02:23:39 +03:00
if ( offset ! = entry_offset ) {
2017-09-07 02:24:33 +03:00
SetPageReadahead ( page ) ;
count_vm_event ( SWAP_RA ) ;
}
mm, swap: add swap readahead hit statistics
Patch series "mm, swap: VMA based swap readahead", v4.
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory space. And the different tasks in the system may have different
access patterns, which makes the global space locality estimation
incorrect.
In this patchset, when page fault occurs, the virtual pages near the
fault address will be readahead instead of the swap slots near the fault
swap slot in swap device. This avoid to readahead the unrelated swap
slots. At the same time, the swap readahead is changed to work on
per-VMA from globally. So that the different access patterns of the
different VMAs could be distinguished, and the different readahead
policy could be applied accordingly. The original core readahead
detection and scaling algorithm is reused, because it is an effect
algorithm to detect the space locality.
In addition to the swap readahead changes, some new sysfs interface is
added to show the efficiency of the readahead algorithm and some other
swap statistics.
This new implementation will incur more small random read, on SSD, the
improved correctness of estimation and readahead target should beat the
potential increased overhead, this is also illustrated in the test
results below. But on HDD, the overhead may beat the benefit, so the
original implementation will be used by default.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM)
Swap device: NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
This patch (of 5):
The statistics for total readahead pages and total readahead hits are
recorded and exported via the following sysfs interface.
/sys/kernel/mm/swap/ra_hits
/sys/kernel/mm/swap/ra_total
With them, the efficiency of the swap readahead could be measured, so
that the swap readahead algorithm and parameters could be tuned
accordingly.
[akpm@linux-foundation.org: don't display swap stats if CONFIG_SWAP=n]
Link: http://lkml.kernel.org/r/20170807054038.1843-2-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:29 +03:00
}
mm, fs: get rid of PAGE_CACHE_* and page_cache_{get,release} macros
PAGE_CACHE_{SIZE,SHIFT,MASK,ALIGN} macros were introduced *long* time
ago with promise that one day it will be possible to implement page
cache with bigger chunks than PAGE_SIZE.
This promise never materialized. And unlikely will.
We have many places where PAGE_CACHE_SIZE assumed to be equal to
PAGE_SIZE. And it's constant source of confusion on whether
PAGE_CACHE_* or PAGE_* constant should be used in a particular case,
especially on the border between fs and mm.
Global switching to PAGE_CACHE_SIZE != PAGE_SIZE would cause to much
breakage to be doable.
Let's stop pretending that pages in page cache are special. They are
not.
The changes are pretty straight-forward:
- <foo> << (PAGE_CACHE_SHIFT - PAGE_SHIFT) -> <foo>;
- <foo> >> (PAGE_CACHE_SHIFT - PAGE_SHIFT) -> <foo>;
- PAGE_CACHE_{SIZE,SHIFT,MASK,ALIGN} -> PAGE_{SIZE,SHIFT,MASK,ALIGN};
- page_cache_get() -> get_page();
- page_cache_release() -> put_page();
This patch contains automated changes generated with coccinelle using
script below. For some reason, coccinelle doesn't patch header files.
I've called spatch for them manually.
The only adjustment after coccinelle is revert of changes to
PAGE_CAHCE_ALIGN definition: we are going to drop it later.
There are few places in the code where coccinelle didn't reach. I'll
fix them manually in a separate patch. Comments and documentation also
will be addressed with the separate patch.
virtual patch
@@
expression E;
@@
- E << (PAGE_CACHE_SHIFT - PAGE_SHIFT)
+ E
@@
expression E;
@@
- E >> (PAGE_CACHE_SHIFT - PAGE_SHIFT)
+ E
@@
@@
- PAGE_CACHE_SHIFT
+ PAGE_SHIFT
@@
@@
- PAGE_CACHE_SIZE
+ PAGE_SIZE
@@
@@
- PAGE_CACHE_MASK
+ PAGE_MASK
@@
expression E;
@@
- PAGE_CACHE_ALIGN(E)
+ PAGE_ALIGN(E)
@@
expression E;
@@
- page_cache_get(E)
+ get_page(E)
@@
expression E;
@@
- page_cache_release(E)
+ put_page(E)
Signed-off-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com>
Acked-by: Michal Hocko <mhocko@suse.com>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2016-04-01 15:29:47 +03:00
put_page ( page ) ;
2008-02-05 09:28:41 +03:00
}
swap: allow swap readahead to be merged
Swap readahead works fine, but the I/O to disk is almost always done in
page size requests, despite the fact that readahead submits
1<<page-cluster pages at a time.
On older kernels the old per device plugging behavior might have captured
this and merged the requests, but currently all comes down to much more
I/Os than required.
On a single device this might not be an issue, but as soon as a server
runs on shared san resources savin I/Os not only improves swapin
throughput but also provides a lower resource utilization.
With a load running KVM in a lot of memory overcommitment (the hot memory
is 1.5 times the host memory) swapping throughput improves significantly
and the lead feels more responsive as well as achieves more throughput.
In a test setup with 16 swap disks running blocktrace on one of those disks
shows the improved merging:
Prior:
Reads Queued: 560,888, 2,243MiB Writes Queued: 226,242, 904,968KiB
Read Dispatches: 544,701, 2,243MiB Write Dispatches: 159,318, 904,968KiB
Reads Requeued: 0 Writes Requeued: 0
Reads Completed: 544,716, 2,243MiB Writes Completed: 159,321, 904,980KiB
Read Merges: 16,187, 64,748KiB Write Merges: 61,744, 246,976KiB
IO unplugs: 149,614 Timer unplugs: 2,940
With the patch:
Reads Queued: 734,315, 2,937MiB Writes Queued: 300,188, 1,200MiB
Read Dispatches: 214,972, 2,937MiB Write Dispatches: 215,176, 1,200MiB
Reads Requeued: 0 Writes Requeued: 0
Reads Completed: 214,971, 2,937MiB Writes Completed: 215,177, 1,200MiB
Read Merges: 519,343, 2,077MiB Write Merges: 73,325, 293,300KiB
IO unplugs: 337,130 Timer unplugs: 11,184
I got ~10% to ~40% more throughput in my cases and at the same time much
lower cpu consumption when broken down per transferred kilobyte (the
majority of that due to saved interrupts and better cache handling). In a
shared SAN others might get an additional benefit as well, because this
now causes less protocol overhead.
Signed-off-by: Christian Ehrhardt <ehrhardt@linux.vnet.ibm.com>
Acked-by: Rik van Riel <riel@redhat.com>
Acked-by: Jens Axboe <axboe@kernel.dk>
Reviewed-by: Minchan Kim <minchan@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2012-08-01 03:41:44 +04:00
blk_finish_plug ( & plug ) ;
2008-02-05 09:28:41 +03:00
lru_add_drain ( ) ; /* Push any new pages onto the LRU now */
swap: add a simple detector for inappropriate swapin readahead
This is a patch to improve swap readahead algorithm. It's from Hugh and
I slightly changed it.
Hugh's original changelog:
swapin readahead does a blind readahead, whether or not the swapin is
sequential. This may be ok on harddisk, because large reads have
relatively small costs, and if the readahead pages are unneeded they can
be reclaimed easily - though, what if their allocation forced reclaim of
useful pages? But on SSD devices large reads are more expensive than
small ones: if the readahead pages are unneeded, reading them in caused
significant overhead.
This patch adds very simplistic random read detection. Stealing the
PageReadahead technique from Konstantin Khlebnikov's patch, avoiding the
vma/anon_vma sophistications of Shaohua Li's patch, swapin_nr_pages()
simply looks at readahead's current success rate, and narrows or widens
its readahead window accordingly. There is little science to its
heuristic: it's about as stupid as can be whilst remaining effective.
The table below shows elapsed times (in centiseconds) when running a
single repetitive swapping load across a 1000MB mapping in 900MB ram
with 1GB swap (the harddisk tests had taken painfully too long when I
used mem=500M, but SSD shows similar results for that).
Vanilla is the 3.6-rc7 kernel on which I started; Shaohua denotes his
Sep 3 patch in mmotm and linux-next; HughOld denotes my Oct 1 patch
which Shaohua showed to be defective; HughNew this Nov 14 patch, with
page_cluster as usual at default of 3 (8-page reads); HughPC4 this same
patch with page_cluster 4 (16-page reads); HughPC0 with page_cluster 0
(1-page reads: no readahead).
HDD for swapping to harddisk, SSD for swapping to VertexII SSD. Seq for
sequential access to the mapping, cycling five times around; Rand for
the same number of random touches. Anon for a MAP_PRIVATE anon mapping;
Shmem for a MAP_SHARED anon mapping, equivalent to tmpfs.
One weakness of Shaohua's vma/anon_vma approach was that it did not
optimize Shmem: seen below. Konstantin's approach was perhaps mistuned,
50% slower on Seq: did not compete and is not shown below.
HDD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0
Seq Anon 73921 76210 75611 76904 78191 121542
Seq Shmem 73601 73176 73855 72947 74543 118322
Rand Anon 895392 831243 871569 845197 846496 841680
Rand Shmem 1058375 1053486 827935 764955 764376 756489
SSD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0
Seq Anon 24634 24198 24673 25107 21614 70018
Seq Shmem 24959 24932 25052 25703 22030 69678
Rand Anon 43014 26146 28075 25989 26935 25901
Rand Shmem 45349 45215 28249 24268 24138 24332
These tests are, of course, two extremes of a very simple case: under
heavier mixed loads I've not yet observed any consistent improvement or
degradation, and wider testing would be welcome.
Shaohua Li:
Test shows Vanilla is slightly better in sequential workload than Hugh's
patch. I observed with Hugh's patch sometimes the readahead size is
shrinked too fast (from 8 to 1 immediately) in sequential workload if
there is no hit. And in such case, continuing doing readahead is good
actually.
I don't prepare a sophisticated algorithm for the sequential workload
because so far we can't guarantee sequential accessed pages are swap out
sequentially. So I slightly change Hugh's heuristic - don't shrink
readahead size too fast.
Here is my test result (unit second, 3 runs average):
Vanilla Hugh New
Seq 356 370 360
Random 4525 2447 2444
Attached graph is the swapin/swapout throughput I collected with 'vmstat
2'. The first part is running a random workload (till around 1200 of
the x-axis) and the second part is running a sequential workload.
swapin and swapout throughput are almost identical in steady state in
both workloads. These are expected behavior. while in Vanilla, swapin
is much bigger than swapout especially in random workload (because wrong
readahead).
Original patches by: Shaohua Li and Konstantin Khlebnikov.
[fengguang.wu@intel.com: swapin_nr_pages() can be static]
Signed-off-by: Hugh Dickins <hughd@google.com>
Signed-off-by: Shaohua Li <shli@fusionio.com>
Signed-off-by: Fengguang Wu <fengguang.wu@intel.com>
Cc: Rik van Riel <riel@redhat.com>
Cc: Wu Fengguang <fengguang.wu@intel.com>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Konstantin Khlebnikov <khlebnikov@openvz.org>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2014-02-07 00:04:21 +04:00
skip :
swap: add block io poll in swapin path
For fast flash disk, async IO could introduce overhead because of
context switch. block-mq now supports IO poll, which improves
performance and latency a lot. swapin is a good place to use this
technique, because the task is waiting for the swapin page to continue
execution.
In my virtual machine, directly read 4k data from a NVMe with iopoll is
about 60% better than that without poll. With iopoll support in swapin
patch, my microbenchmark (a task does random memory write) is about
10%~25% faster. CPU utilization increases a lot though, 2x and even 3x
CPU utilization. This will depend on disk speed.
While iopoll in swapin isn't intended for all usage cases, it's a win
for latency sensistive workloads with high speed swap disk. block layer
has knob to control poll in runtime. If poll isn't enabled in block
layer, there should be no noticeable change in swapin.
I got a chance to run the same test in a NVMe with DRAM as the media.
In simple fio IO test, blkpoll boosts 50% performance in single thread
test and ~20% in 8 threads test. So this is the base line. In above
swap test, blkpoll boosts ~27% performance in single thread test.
blkpoll uses 2x CPU time though.
If we enable hybid polling, the performance gain has very slight drop
but CPU time is only 50% worse than that without blkpoll. Also we can
adjust parameter of hybid poll, with it, the CPU time penality is
reduced further. In 8 threads test, blkpoll doesn't help though. The
performance is similar to that without blkpoll, but cpu utilization is
similar too. There is lock contention in swap path. The cpu time
spending on blkpoll isn't high. So overall, blkpoll swapin isn't worse
than that without it.
The swapin readahead might read several pages in in the same time and
form a big IO request. Since the IO will take longer time, it doesn't
make sense to do poll, so the patch only does iopoll for single page
swapin.
[akpm@linux-foundation.org: coding-style fixes]
Link: http://lkml.kernel.org/r/070c3c3e40b711e7b1390002c991e86a-b5408f0@7511894063d3764ff01ea8111f5a004d7dd700ed078797c204a24e620ddb965c
Signed-off-by: Shaohua Li <shli@fb.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Huang Ying <ying.huang@intel.com>
Cc: Jens Axboe <axboe@fb.com>
Cc: Hugh Dickins <hughd@google.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-11 01:47:11 +03:00
return read_swap_cache_async ( entry , gfp_mask , vma , addr , do_poll ) ;
2008-02-05 09:28:41 +03:00
}
mm/swap: split swap cache into 64MB trunks
The patch is to improve the scalability of the swap out/in via using
fine grained locks for the swap cache. In current kernel, one address
space will be used for each swap device. And in the common
configuration, the number of the swap device is very small (one is
typical). This causes the heavy lock contention on the radix tree of
the address space if multiple tasks swap out/in concurrently.
But in fact, there is no dependency between pages in the swap cache. So
that, we can split the one shared address space for each swap device
into several address spaces to reduce the lock contention. In the
patch, the shared address space is split into 64MB trunks. 64MB is
chosen to balance the memory space usage and effect of lock contention
reduction.
The size of struct address_space on x86_64 architecture is 408B, so with
the patch, 6528B more memory will be used for every 1GB swap space on
x86_64 architecture.
One address space is still shared for the swap entries in the same 64M
trunks. To avoid lock contention for the first round of swap space
allocation, the order of the swap clusters in the initial free clusters
list is changed. The swap space distance between the consecutive swap
clusters in the free cluster list is at least 64M. After the first
round of allocation, the swap clusters are expected to be freed
randomly, so the lock contention should be reduced effectively.
Link: http://lkml.kernel.org/r/735bab895e64c930581ffb0a05b661e01da82bc5.1484082593.git.tim.c.chen@linux.intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Signed-off-by: Tim Chen <tim.c.chen@linux.intel.com>
Cc: Aaron Lu <aaron.lu@intel.com>
Cc: Andi Kleen <ak@linux.intel.com>
Cc: Andrea Arcangeli <aarcange@redhat.com>
Cc: Christian Borntraeger <borntraeger@de.ibm.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Cc: Hillf Danton <hillf.zj@alibaba-inc.com>
Cc: Huang Ying <ying.huang@intel.com>
Cc: Hugh Dickins <hughd@google.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Jonathan Corbet <corbet@lwn.net> escreveu:
Cc: Kirill A. Shutemov <kirill.shutemov@linux.intel.com>
Cc: Michal Hocko <mhocko@kernel.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Vladimir Davydov <vdavydov.dev@gmail.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-02-23 02:45:26 +03:00
int init_swap_address_space ( unsigned int type , unsigned long nr_pages )
{
struct address_space * spaces , * space ;
unsigned int i , nr ;
nr = DIV_ROUND_UP ( nr_pages , SWAP_ADDRESS_SPACE_PAGES ) ;
treewide: kvzalloc() -> kvcalloc()
The kvzalloc() function has a 2-factor argument form, kvcalloc(). This
patch replaces cases of:
kvzalloc(a * b, gfp)
with:
kvcalloc(a * b, gfp)
as well as handling cases of:
kvzalloc(a * b * c, gfp)
with:
kvzalloc(array3_size(a, b, c), gfp)
as it's slightly less ugly than:
kvcalloc(array_size(a, b), c, gfp)
This does, however, attempt to ignore constant size factors like:
kvzalloc(4 * 1024, gfp)
though any constants defined via macros get caught up in the conversion.
Any factors with a sizeof() of "unsigned char", "char", and "u8" were
dropped, since they're redundant.
The Coccinelle script used for this was:
// Fix redundant parens around sizeof().
@@
type TYPE;
expression THING, E;
@@
(
kvzalloc(
- (sizeof(TYPE)) * E
+ sizeof(TYPE) * E
, ...)
|
kvzalloc(
- (sizeof(THING)) * E
+ sizeof(THING) * E
, ...)
)
// Drop single-byte sizes and redundant parens.
@@
expression COUNT;
typedef u8;
typedef __u8;
@@
(
kvzalloc(
- sizeof(u8) * (COUNT)
+ COUNT
, ...)
|
kvzalloc(
- sizeof(__u8) * (COUNT)
+ COUNT
, ...)
|
kvzalloc(
- sizeof(char) * (COUNT)
+ COUNT
, ...)
|
kvzalloc(
- sizeof(unsigned char) * (COUNT)
+ COUNT
, ...)
|
kvzalloc(
- sizeof(u8) * COUNT
+ COUNT
, ...)
|
kvzalloc(
- sizeof(__u8) * COUNT
+ COUNT
, ...)
|
kvzalloc(
- sizeof(char) * COUNT
+ COUNT
, ...)
|
kvzalloc(
- sizeof(unsigned char) * COUNT
+ COUNT
, ...)
)
// 2-factor product with sizeof(type/expression) and identifier or constant.
@@
type TYPE;
expression THING;
identifier COUNT_ID;
constant COUNT_CONST;
@@
(
- kvzalloc
+ kvcalloc
(
- sizeof(TYPE) * (COUNT_ID)
+ COUNT_ID, sizeof(TYPE)
, ...)
|
- kvzalloc
+ kvcalloc
(
- sizeof(TYPE) * COUNT_ID
+ COUNT_ID, sizeof(TYPE)
, ...)
|
- kvzalloc
+ kvcalloc
(
- sizeof(TYPE) * (COUNT_CONST)
+ COUNT_CONST, sizeof(TYPE)
, ...)
|
- kvzalloc
+ kvcalloc
(
- sizeof(TYPE) * COUNT_CONST
+ COUNT_CONST, sizeof(TYPE)
, ...)
|
- kvzalloc
+ kvcalloc
(
- sizeof(THING) * (COUNT_ID)
+ COUNT_ID, sizeof(THING)
, ...)
|
- kvzalloc
+ kvcalloc
(
- sizeof(THING) * COUNT_ID
+ COUNT_ID, sizeof(THING)
, ...)
|
- kvzalloc
+ kvcalloc
(
- sizeof(THING) * (COUNT_CONST)
+ COUNT_CONST, sizeof(THING)
, ...)
|
- kvzalloc
+ kvcalloc
(
- sizeof(THING) * COUNT_CONST
+ COUNT_CONST, sizeof(THING)
, ...)
)
// 2-factor product, only identifiers.
@@
identifier SIZE, COUNT;
@@
- kvzalloc
+ kvcalloc
(
- SIZE * COUNT
+ COUNT, SIZE
, ...)
// 3-factor product with 1 sizeof(type) or sizeof(expression), with
// redundant parens removed.
@@
expression THING;
identifier STRIDE, COUNT;
type TYPE;
@@
(
kvzalloc(
- sizeof(TYPE) * (COUNT) * (STRIDE)
+ array3_size(COUNT, STRIDE, sizeof(TYPE))
, ...)
|
kvzalloc(
- sizeof(TYPE) * (COUNT) * STRIDE
+ array3_size(COUNT, STRIDE, sizeof(TYPE))
, ...)
|
kvzalloc(
- sizeof(TYPE) * COUNT * (STRIDE)
+ array3_size(COUNT, STRIDE, sizeof(TYPE))
, ...)
|
kvzalloc(
- sizeof(TYPE) * COUNT * STRIDE
+ array3_size(COUNT, STRIDE, sizeof(TYPE))
, ...)
|
kvzalloc(
- sizeof(THING) * (COUNT) * (STRIDE)
+ array3_size(COUNT, STRIDE, sizeof(THING))
, ...)
|
kvzalloc(
- sizeof(THING) * (COUNT) * STRIDE
+ array3_size(COUNT, STRIDE, sizeof(THING))
, ...)
|
kvzalloc(
- sizeof(THING) * COUNT * (STRIDE)
+ array3_size(COUNT, STRIDE, sizeof(THING))
, ...)
|
kvzalloc(
- sizeof(THING) * COUNT * STRIDE
+ array3_size(COUNT, STRIDE, sizeof(THING))
, ...)
)
// 3-factor product with 2 sizeof(variable), with redundant parens removed.
@@
expression THING1, THING2;
identifier COUNT;
type TYPE1, TYPE2;
@@
(
kvzalloc(
- sizeof(TYPE1) * sizeof(TYPE2) * COUNT
+ array3_size(COUNT, sizeof(TYPE1), sizeof(TYPE2))
, ...)
|
kvzalloc(
- sizeof(TYPE1) * sizeof(THING2) * (COUNT)
+ array3_size(COUNT, sizeof(TYPE1), sizeof(TYPE2))
, ...)
|
kvzalloc(
- sizeof(THING1) * sizeof(THING2) * COUNT
+ array3_size(COUNT, sizeof(THING1), sizeof(THING2))
, ...)
|
kvzalloc(
- sizeof(THING1) * sizeof(THING2) * (COUNT)
+ array3_size(COUNT, sizeof(THING1), sizeof(THING2))
, ...)
|
kvzalloc(
- sizeof(TYPE1) * sizeof(THING2) * COUNT
+ array3_size(COUNT, sizeof(TYPE1), sizeof(THING2))
, ...)
|
kvzalloc(
- sizeof(TYPE1) * sizeof(THING2) * (COUNT)
+ array3_size(COUNT, sizeof(TYPE1), sizeof(THING2))
, ...)
)
// 3-factor product, only identifiers, with redundant parens removed.
@@
identifier STRIDE, SIZE, COUNT;
@@
(
kvzalloc(
- (COUNT) * STRIDE * SIZE
+ array3_size(COUNT, STRIDE, SIZE)
, ...)
|
kvzalloc(
- COUNT * (STRIDE) * SIZE
+ array3_size(COUNT, STRIDE, SIZE)
, ...)
|
kvzalloc(
- COUNT * STRIDE * (SIZE)
+ array3_size(COUNT, STRIDE, SIZE)
, ...)
|
kvzalloc(
- (COUNT) * (STRIDE) * SIZE
+ array3_size(COUNT, STRIDE, SIZE)
, ...)
|
kvzalloc(
- COUNT * (STRIDE) * (SIZE)
+ array3_size(COUNT, STRIDE, SIZE)
, ...)
|
kvzalloc(
- (COUNT) * STRIDE * (SIZE)
+ array3_size(COUNT, STRIDE, SIZE)
, ...)
|
kvzalloc(
- (COUNT) * (STRIDE) * (SIZE)
+ array3_size(COUNT, STRIDE, SIZE)
, ...)
|
kvzalloc(
- COUNT * STRIDE * SIZE
+ array3_size(COUNT, STRIDE, SIZE)
, ...)
)
// Any remaining multi-factor products, first at least 3-factor products,
// when they're not all constants...
@@
expression E1, E2, E3;
constant C1, C2, C3;
@@
(
kvzalloc(C1 * C2 * C3, ...)
|
kvzalloc(
- (E1) * E2 * E3
+ array3_size(E1, E2, E3)
, ...)
|
kvzalloc(
- (E1) * (E2) * E3
+ array3_size(E1, E2, E3)
, ...)
|
kvzalloc(
- (E1) * (E2) * (E3)
+ array3_size(E1, E2, E3)
, ...)
|
kvzalloc(
- E1 * E2 * E3
+ array3_size(E1, E2, E3)
, ...)
)
// And then all remaining 2 factors products when they're not all constants,
// keeping sizeof() as the second factor argument.
@@
expression THING, E1, E2;
type TYPE;
constant C1, C2, C3;
@@
(
kvzalloc(sizeof(THING) * C2, ...)
|
kvzalloc(sizeof(TYPE) * C2, ...)
|
kvzalloc(C1 * C2 * C3, ...)
|
kvzalloc(C1 * C2, ...)
|
- kvzalloc
+ kvcalloc
(
- sizeof(TYPE) * (E2)
+ E2, sizeof(TYPE)
, ...)
|
- kvzalloc
+ kvcalloc
(
- sizeof(TYPE) * E2
+ E2, sizeof(TYPE)
, ...)
|
- kvzalloc
+ kvcalloc
(
- sizeof(THING) * (E2)
+ E2, sizeof(THING)
, ...)
|
- kvzalloc
+ kvcalloc
(
- sizeof(THING) * E2
+ E2, sizeof(THING)
, ...)
|
- kvzalloc
+ kvcalloc
(
- (E1) * E2
+ E1, E2
, ...)
|
- kvzalloc
+ kvcalloc
(
- (E1) * (E2)
+ E1, E2
, ...)
|
- kvzalloc
+ kvcalloc
(
- E1 * E2
+ E1, E2
, ...)
)
Signed-off-by: Kees Cook <keescook@chromium.org>
2018-06-13 00:04:48 +03:00
spaces = kvcalloc ( nr , sizeof ( struct address_space ) , GFP_KERNEL ) ;
mm/swap: split swap cache into 64MB trunks
The patch is to improve the scalability of the swap out/in via using
fine grained locks for the swap cache. In current kernel, one address
space will be used for each swap device. And in the common
configuration, the number of the swap device is very small (one is
typical). This causes the heavy lock contention on the radix tree of
the address space if multiple tasks swap out/in concurrently.
But in fact, there is no dependency between pages in the swap cache. So
that, we can split the one shared address space for each swap device
into several address spaces to reduce the lock contention. In the
patch, the shared address space is split into 64MB trunks. 64MB is
chosen to balance the memory space usage and effect of lock contention
reduction.
The size of struct address_space on x86_64 architecture is 408B, so with
the patch, 6528B more memory will be used for every 1GB swap space on
x86_64 architecture.
One address space is still shared for the swap entries in the same 64M
trunks. To avoid lock contention for the first round of swap space
allocation, the order of the swap clusters in the initial free clusters
list is changed. The swap space distance between the consecutive swap
clusters in the free cluster list is at least 64M. After the first
round of allocation, the swap clusters are expected to be freed
randomly, so the lock contention should be reduced effectively.
Link: http://lkml.kernel.org/r/735bab895e64c930581ffb0a05b661e01da82bc5.1484082593.git.tim.c.chen@linux.intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Signed-off-by: Tim Chen <tim.c.chen@linux.intel.com>
Cc: Aaron Lu <aaron.lu@intel.com>
Cc: Andi Kleen <ak@linux.intel.com>
Cc: Andrea Arcangeli <aarcange@redhat.com>
Cc: Christian Borntraeger <borntraeger@de.ibm.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Cc: Hillf Danton <hillf.zj@alibaba-inc.com>
Cc: Huang Ying <ying.huang@intel.com>
Cc: Hugh Dickins <hughd@google.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Jonathan Corbet <corbet@lwn.net> escreveu:
Cc: Kirill A. Shutemov <kirill.shutemov@linux.intel.com>
Cc: Michal Hocko <mhocko@kernel.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Vladimir Davydov <vdavydov.dev@gmail.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-02-23 02:45:26 +03:00
if ( ! spaces )
return - ENOMEM ;
for ( i = 0 ; i < nr ; i + + ) {
space = spaces + i ;
2017-12-06 03:04:20 +03:00
xa_init_flags ( & space - > i_pages , XA_FLAGS_LOCK_IRQ ) ;
mm/swap: split swap cache into 64MB trunks
The patch is to improve the scalability of the swap out/in via using
fine grained locks for the swap cache. In current kernel, one address
space will be used for each swap device. And in the common
configuration, the number of the swap device is very small (one is
typical). This causes the heavy lock contention on the radix tree of
the address space if multiple tasks swap out/in concurrently.
But in fact, there is no dependency between pages in the swap cache. So
that, we can split the one shared address space for each swap device
into several address spaces to reduce the lock contention. In the
patch, the shared address space is split into 64MB trunks. 64MB is
chosen to balance the memory space usage and effect of lock contention
reduction.
The size of struct address_space on x86_64 architecture is 408B, so with
the patch, 6528B more memory will be used for every 1GB swap space on
x86_64 architecture.
One address space is still shared for the swap entries in the same 64M
trunks. To avoid lock contention for the first round of swap space
allocation, the order of the swap clusters in the initial free clusters
list is changed. The swap space distance between the consecutive swap
clusters in the free cluster list is at least 64M. After the first
round of allocation, the swap clusters are expected to be freed
randomly, so the lock contention should be reduced effectively.
Link: http://lkml.kernel.org/r/735bab895e64c930581ffb0a05b661e01da82bc5.1484082593.git.tim.c.chen@linux.intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Signed-off-by: Tim Chen <tim.c.chen@linux.intel.com>
Cc: Aaron Lu <aaron.lu@intel.com>
Cc: Andi Kleen <ak@linux.intel.com>
Cc: Andrea Arcangeli <aarcange@redhat.com>
Cc: Christian Borntraeger <borntraeger@de.ibm.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Cc: Hillf Danton <hillf.zj@alibaba-inc.com>
Cc: Huang Ying <ying.huang@intel.com>
Cc: Hugh Dickins <hughd@google.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Jonathan Corbet <corbet@lwn.net> escreveu:
Cc: Kirill A. Shutemov <kirill.shutemov@linux.intel.com>
Cc: Michal Hocko <mhocko@kernel.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Vladimir Davydov <vdavydov.dev@gmail.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-02-23 02:45:26 +03:00
atomic_set ( & space - > i_mmap_writable , 0 ) ;
space - > a_ops = & swap_aops ;
/* swap cache doesn't use writeback related tags */
mapping_set_no_writeback_tags ( space ) ;
}
nr_swapper_spaces [ type ] = nr ;
2019-07-12 06:55:37 +03:00
swapper_spaces [ type ] = spaces ;
mm/swap: split swap cache into 64MB trunks
The patch is to improve the scalability of the swap out/in via using
fine grained locks for the swap cache. In current kernel, one address
space will be used for each swap device. And in the common
configuration, the number of the swap device is very small (one is
typical). This causes the heavy lock contention on the radix tree of
the address space if multiple tasks swap out/in concurrently.
But in fact, there is no dependency between pages in the swap cache. So
that, we can split the one shared address space for each swap device
into several address spaces to reduce the lock contention. In the
patch, the shared address space is split into 64MB trunks. 64MB is
chosen to balance the memory space usage and effect of lock contention
reduction.
The size of struct address_space on x86_64 architecture is 408B, so with
the patch, 6528B more memory will be used for every 1GB swap space on
x86_64 architecture.
One address space is still shared for the swap entries in the same 64M
trunks. To avoid lock contention for the first round of swap space
allocation, the order of the swap clusters in the initial free clusters
list is changed. The swap space distance between the consecutive swap
clusters in the free cluster list is at least 64M. After the first
round of allocation, the swap clusters are expected to be freed
randomly, so the lock contention should be reduced effectively.
Link: http://lkml.kernel.org/r/735bab895e64c930581ffb0a05b661e01da82bc5.1484082593.git.tim.c.chen@linux.intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Signed-off-by: Tim Chen <tim.c.chen@linux.intel.com>
Cc: Aaron Lu <aaron.lu@intel.com>
Cc: Andi Kleen <ak@linux.intel.com>
Cc: Andrea Arcangeli <aarcange@redhat.com>
Cc: Christian Borntraeger <borntraeger@de.ibm.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Cc: Hillf Danton <hillf.zj@alibaba-inc.com>
Cc: Huang Ying <ying.huang@intel.com>
Cc: Hugh Dickins <hughd@google.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Jonathan Corbet <corbet@lwn.net> escreveu:
Cc: Kirill A. Shutemov <kirill.shutemov@linux.intel.com>
Cc: Michal Hocko <mhocko@kernel.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Vladimir Davydov <vdavydov.dev@gmail.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-02-23 02:45:26 +03:00
return 0 ;
}
void exit_swap_address_space ( unsigned int type )
{
2021-06-29 05:37:16 +03:00
int i ;
struct address_space * spaces = swapper_spaces [ type ] ;
for ( i = 0 ; i < nr_swapper_spaces [ type ] ; i + + )
VM_WARN_ON_ONCE ( ! mapping_empty ( & spaces [ i ] ) ) ;
kvfree ( spaces ) ;
mm/swap: split swap cache into 64MB trunks
The patch is to improve the scalability of the swap out/in via using
fine grained locks for the swap cache. In current kernel, one address
space will be used for each swap device. And in the common
configuration, the number of the swap device is very small (one is
typical). This causes the heavy lock contention on the radix tree of
the address space if multiple tasks swap out/in concurrently.
But in fact, there is no dependency between pages in the swap cache. So
that, we can split the one shared address space for each swap device
into several address spaces to reduce the lock contention. In the
patch, the shared address space is split into 64MB trunks. 64MB is
chosen to balance the memory space usage and effect of lock contention
reduction.
The size of struct address_space on x86_64 architecture is 408B, so with
the patch, 6528B more memory will be used for every 1GB swap space on
x86_64 architecture.
One address space is still shared for the swap entries in the same 64M
trunks. To avoid lock contention for the first round of swap space
allocation, the order of the swap clusters in the initial free clusters
list is changed. The swap space distance between the consecutive swap
clusters in the free cluster list is at least 64M. After the first
round of allocation, the swap clusters are expected to be freed
randomly, so the lock contention should be reduced effectively.
Link: http://lkml.kernel.org/r/735bab895e64c930581ffb0a05b661e01da82bc5.1484082593.git.tim.c.chen@linux.intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Signed-off-by: Tim Chen <tim.c.chen@linux.intel.com>
Cc: Aaron Lu <aaron.lu@intel.com>
Cc: Andi Kleen <ak@linux.intel.com>
Cc: Andrea Arcangeli <aarcange@redhat.com>
Cc: Christian Borntraeger <borntraeger@de.ibm.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Cc: Hillf Danton <hillf.zj@alibaba-inc.com>
Cc: Huang Ying <ying.huang@intel.com>
Cc: Hugh Dickins <hughd@google.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Jonathan Corbet <corbet@lwn.net> escreveu:
Cc: Kirill A. Shutemov <kirill.shutemov@linux.intel.com>
Cc: Michal Hocko <mhocko@kernel.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Vladimir Davydov <vdavydov.dev@gmail.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-02-23 02:45:26 +03:00
nr_swapper_spaces [ type ] = 0 ;
2019-07-12 06:55:37 +03:00
swapper_spaces [ type ] = NULL ;
mm/swap: split swap cache into 64MB trunks
The patch is to improve the scalability of the swap out/in via using
fine grained locks for the swap cache. In current kernel, one address
space will be used for each swap device. And in the common
configuration, the number of the swap device is very small (one is
typical). This causes the heavy lock contention on the radix tree of
the address space if multiple tasks swap out/in concurrently.
But in fact, there is no dependency between pages in the swap cache. So
that, we can split the one shared address space for each swap device
into several address spaces to reduce the lock contention. In the
patch, the shared address space is split into 64MB trunks. 64MB is
chosen to balance the memory space usage and effect of lock contention
reduction.
The size of struct address_space on x86_64 architecture is 408B, so with
the patch, 6528B more memory will be used for every 1GB swap space on
x86_64 architecture.
One address space is still shared for the swap entries in the same 64M
trunks. To avoid lock contention for the first round of swap space
allocation, the order of the swap clusters in the initial free clusters
list is changed. The swap space distance between the consecutive swap
clusters in the free cluster list is at least 64M. After the first
round of allocation, the swap clusters are expected to be freed
randomly, so the lock contention should be reduced effectively.
Link: http://lkml.kernel.org/r/735bab895e64c930581ffb0a05b661e01da82bc5.1484082593.git.tim.c.chen@linux.intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Signed-off-by: Tim Chen <tim.c.chen@linux.intel.com>
Cc: Aaron Lu <aaron.lu@intel.com>
Cc: Andi Kleen <ak@linux.intel.com>
Cc: Andrea Arcangeli <aarcange@redhat.com>
Cc: Christian Borntraeger <borntraeger@de.ibm.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Cc: Hillf Danton <hillf.zj@alibaba-inc.com>
Cc: Huang Ying <ying.huang@intel.com>
Cc: Hugh Dickins <hughd@google.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Jonathan Corbet <corbet@lwn.net> escreveu:
Cc: Kirill A. Shutemov <kirill.shutemov@linux.intel.com>
Cc: Michal Hocko <mhocko@kernel.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Vladimir Davydov <vdavydov.dev@gmail.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-02-23 02:45:26 +03:00
}
mm, swap: VMA based swap readahead
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory. And the different tasks in the system may have different access
patterns, which makes the global space locality estimation incorrect.
In this patch, when page fault occurs, the virtual pages near the fault
address will be readahead instead of the swap slots near the fault swap
slot in swap device. This avoid to readahead the unrelated swap slots.
At the same time, the swap readahead is changed to work on per-VMA from
globally. So that the different access patterns of the different VMAs
could be distinguished, and the different readahead policy could be
applied accordingly. The original core readahead detection and scaling
algorithm is reused, because it is an effect algorithm to detect the
space locality.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device:
NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:36 +03:00
static inline void swap_ra_clamp_pfn ( struct vm_area_struct * vma ,
unsigned long faddr ,
unsigned long lpfn ,
unsigned long rpfn ,
unsigned long * start ,
unsigned long * end )
{
* start = max3 ( lpfn , PFN_DOWN ( vma - > vm_start ) ,
PFN_DOWN ( faddr & PMD_MASK ) ) ;
* end = min3 ( rpfn , PFN_DOWN ( vma - > vm_end ) ,
PFN_DOWN ( ( faddr & PMD_MASK ) + PMD_SIZE ) ) ;
}
2018-04-06 02:23:39 +03:00
static void swap_ra_info ( struct vm_fault * vmf ,
struct vma_swap_readahead * ra_info )
mm, swap: VMA based swap readahead
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory. And the different tasks in the system may have different access
patterns, which makes the global space locality estimation incorrect.
In this patch, when page fault occurs, the virtual pages near the fault
address will be readahead instead of the swap slots near the fault swap
slot in swap device. This avoid to readahead the unrelated swap slots.
At the same time, the swap readahead is changed to work on per-VMA from
globally. So that the different access patterns of the different VMAs
could be distinguished, and the different readahead policy could be
applied accordingly. The original core readahead detection and scaling
algorithm is reused, because it is an effect algorithm to detect the
space locality.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device:
NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:36 +03:00
{
struct vm_area_struct * vma = vmf - > vma ;
2018-04-06 02:23:39 +03:00
unsigned long ra_val ;
mm, swap: VMA based swap readahead
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory. And the different tasks in the system may have different access
patterns, which makes the global space locality estimation incorrect.
In this patch, when page fault occurs, the virtual pages near the fault
address will be readahead instead of the swap slots near the fault swap
slot in swap device. This avoid to readahead the unrelated swap slots.
At the same time, the swap readahead is changed to work on per-VMA from
globally. So that the different access patterns of the different VMAs
could be distinguished, and the different readahead policy could be
applied accordingly. The original core readahead detection and scaling
algorithm is reused, because it is an effect algorithm to detect the
space locality.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device:
NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:36 +03:00
unsigned long faddr , pfn , fpfn ;
unsigned long start , end ;
2018-04-06 02:23:39 +03:00
pte_t * pte , * orig_pte ;
mm, swap: VMA based swap readahead
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory. And the different tasks in the system may have different access
patterns, which makes the global space locality estimation incorrect.
In this patch, when page fault occurs, the virtual pages near the fault
address will be readahead instead of the swap slots near the fault swap
slot in swap device. This avoid to readahead the unrelated swap slots.
At the same time, the swap readahead is changed to work on per-VMA from
globally. So that the different access patterns of the different VMAs
could be distinguished, and the different readahead policy could be
applied accordingly. The original core readahead detection and scaling
algorithm is reused, because it is an effect algorithm to detect the
space locality.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device:
NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:36 +03:00
unsigned int max_win , hits , prev_win , win , left ;
# ifndef CONFIG_64BIT
pte_t * tpte ;
# endif
2017-10-14 01:58:29 +03:00
max_win = 1 < < min_t ( unsigned int , READ_ONCE ( page_cluster ) ,
SWAP_RA_ORDER_CEILING ) ;
if ( max_win = = 1 ) {
2018-04-06 02:23:39 +03:00
ra_info - > win = 1 ;
return ;
2017-10-14 01:58:29 +03:00
}
mm, swap: VMA based swap readahead
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory. And the different tasks in the system may have different access
patterns, which makes the global space locality estimation incorrect.
In this patch, when page fault occurs, the virtual pages near the fault
address will be readahead instead of the swap slots near the fault swap
slot in swap device. This avoid to readahead the unrelated swap slots.
At the same time, the swap readahead is changed to work on per-VMA from
globally. So that the different access patterns of the different VMAs
could be distinguished, and the different readahead policy could be
applied accordingly. The original core readahead detection and scaling
algorithm is reused, because it is an effect algorithm to detect the
space locality.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device:
NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:36 +03:00
faddr = vmf - > address ;
2018-04-06 02:23:39 +03:00
orig_pte = pte = pte_offset_map ( vmf - > pmd , faddr ) ;
mm, swap: VMA based swap readahead
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory. And the different tasks in the system may have different access
patterns, which makes the global space locality estimation incorrect.
In this patch, when page fault occurs, the virtual pages near the fault
address will be readahead instead of the swap slots near the fault swap
slot in swap device. This avoid to readahead the unrelated swap slots.
At the same time, the swap readahead is changed to work on per-VMA from
globally. So that the different access patterns of the different VMAs
could be distinguished, and the different readahead policy could be
applied accordingly. The original core readahead detection and scaling
algorithm is reused, because it is an effect algorithm to detect the
space locality.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device:
NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:36 +03:00
fpfn = PFN_DOWN ( faddr ) ;
2018-04-06 02:23:39 +03:00
ra_val = GET_SWAP_RA_VAL ( vma ) ;
pfn = PFN_DOWN ( SWAP_RA_ADDR ( ra_val ) ) ;
prev_win = SWAP_RA_WIN ( ra_val ) ;
hits = SWAP_RA_HITS ( ra_val ) ;
ra_info - > win = win = __swapin_nr_pages ( pfn , fpfn , hits ,
mm, swap: VMA based swap readahead
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory. And the different tasks in the system may have different access
patterns, which makes the global space locality estimation incorrect.
In this patch, when page fault occurs, the virtual pages near the fault
address will be readahead instead of the swap slots near the fault swap
slot in swap device. This avoid to readahead the unrelated swap slots.
At the same time, the swap readahead is changed to work on per-VMA from
globally. So that the different access patterns of the different VMAs
could be distinguished, and the different readahead policy could be
applied accordingly. The original core readahead detection and scaling
algorithm is reused, because it is an effect algorithm to detect the
space locality.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device:
NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:36 +03:00
max_win , prev_win ) ;
atomic_long_set ( & vma - > swap_readahead_info ,
SWAP_RA_VAL ( faddr , win , 0 ) ) ;
2018-04-06 02:23:39 +03:00
if ( win = = 1 ) {
pte_unmap ( orig_pte ) ;
return ;
}
mm, swap: VMA based swap readahead
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory. And the different tasks in the system may have different access
patterns, which makes the global space locality estimation incorrect.
In this patch, when page fault occurs, the virtual pages near the fault
address will be readahead instead of the swap slots near the fault swap
slot in swap device. This avoid to readahead the unrelated swap slots.
At the same time, the swap readahead is changed to work on per-VMA from
globally. So that the different access patterns of the different VMAs
could be distinguished, and the different readahead policy could be
applied accordingly. The original core readahead detection and scaling
algorithm is reused, because it is an effect algorithm to detect the
space locality.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device:
NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:36 +03:00
/* Copy the PTEs because the page table may be unmapped */
if ( fpfn = = pfn + 1 )
swap_ra_clamp_pfn ( vma , faddr , fpfn , fpfn + win , & start , & end ) ;
else if ( pfn = = fpfn + 1 )
swap_ra_clamp_pfn ( vma , faddr , fpfn - win + 1 , fpfn + 1 ,
& start , & end ) ;
else {
left = ( win - 1 ) / 2 ;
swap_ra_clamp_pfn ( vma , faddr , fpfn - left , fpfn + win - left ,
& start , & end ) ;
}
2018-04-06 02:23:39 +03:00
ra_info - > nr_pte = end - start ;
ra_info - > offset = fpfn - start ;
pte - = ra_info - > offset ;
mm, swap: VMA based swap readahead
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory. And the different tasks in the system may have different access
patterns, which makes the global space locality estimation incorrect.
In this patch, when page fault occurs, the virtual pages near the fault
address will be readahead instead of the swap slots near the fault swap
slot in swap device. This avoid to readahead the unrelated swap slots.
At the same time, the swap readahead is changed to work on per-VMA from
globally. So that the different access patterns of the different VMAs
could be distinguished, and the different readahead policy could be
applied accordingly. The original core readahead detection and scaling
algorithm is reused, because it is an effect algorithm to detect the
space locality.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device:
NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:36 +03:00
# ifdef CONFIG_64BIT
2018-04-06 02:23:39 +03:00
ra_info - > ptes = pte ;
mm, swap: VMA based swap readahead
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory. And the different tasks in the system may have different access
patterns, which makes the global space locality estimation incorrect.
In this patch, when page fault occurs, the virtual pages near the fault
address will be readahead instead of the swap slots near the fault swap
slot in swap device. This avoid to readahead the unrelated swap slots.
At the same time, the swap readahead is changed to work on per-VMA from
globally. So that the different access patterns of the different VMAs
could be distinguished, and the different readahead policy could be
applied accordingly. The original core readahead detection and scaling
algorithm is reused, because it is an effect algorithm to detect the
space locality.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device:
NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:36 +03:00
# else
2018-04-06 02:23:39 +03:00
tpte = ra_info - > ptes ;
mm, swap: VMA based swap readahead
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory. And the different tasks in the system may have different access
patterns, which makes the global space locality estimation incorrect.
In this patch, when page fault occurs, the virtual pages near the fault
address will be readahead instead of the swap slots near the fault swap
slot in swap device. This avoid to readahead the unrelated swap slots.
At the same time, the swap readahead is changed to work on per-VMA from
globally. So that the different access patterns of the different VMAs
could be distinguished, and the different readahead policy could be
applied accordingly. The original core readahead detection and scaling
algorithm is reused, because it is an effect algorithm to detect the
space locality.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device:
NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:36 +03:00
for ( pfn = start ; pfn ! = end ; pfn + + )
* tpte + + = * pte + + ;
# endif
2018-04-06 02:23:39 +03:00
pte_unmap ( orig_pte ) ;
mm, swap: VMA based swap readahead
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory. And the different tasks in the system may have different access
patterns, which makes the global space locality estimation incorrect.
In this patch, when page fault occurs, the virtual pages near the fault
address will be readahead instead of the swap slots near the fault swap
slot in swap device. This avoid to readahead the unrelated swap slots.
At the same time, the swap readahead is changed to work on per-VMA from
globally. So that the different access patterns of the different VMAs
could be distinguished, and the different readahead policy could be
applied accordingly. The original core readahead detection and scaling
algorithm is reused, because it is an effect algorithm to detect the
space locality.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device:
NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:36 +03:00
}
2019-03-06 02:44:15 +03:00
/**
* swap_vma_readahead - swap in pages in hope we need them soon
2020-08-07 09:20:14 +03:00
* @ fentry : swap entry of this memory
2019-03-06 02:44:15 +03:00
* @ gfp_mask : memory allocation flags
* @ vmf : fault information
*
* Returns the struct page for entry and addr , after queueing swapin .
*
2021-05-07 04:05:51 +03:00
* Primitive swap readahead code . We simply read in a few pages whose
2019-03-06 02:44:15 +03:00
* virtual addresses are around the fault address in the same vma .
*
2020-06-09 07:33:54 +03:00
* Caller must hold read mmap_lock if vmf - > vma is not NULL .
2019-03-06 02:44:15 +03:00
*
*/
2018-04-06 02:25:05 +03:00
static struct page * swap_vma_readahead ( swp_entry_t fentry , gfp_t gfp_mask ,
struct vm_fault * vmf )
mm, swap: VMA based swap readahead
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory. And the different tasks in the system may have different access
patterns, which makes the global space locality estimation incorrect.
In this patch, when page fault occurs, the virtual pages near the fault
address will be readahead instead of the swap slots near the fault swap
slot in swap device. This avoid to readahead the unrelated swap slots.
At the same time, the swap readahead is changed to work on per-VMA from
globally. So that the different access patterns of the different VMAs
could be distinguished, and the different readahead policy could be
applied accordingly. The original core readahead detection and scaling
algorithm is reused, because it is an effect algorithm to detect the
space locality.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device:
NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:36 +03:00
{
struct blk_plug plug ;
struct vm_area_struct * vma = vmf - > vma ;
struct page * page ;
pte_t * pte , pentry ;
swp_entry_t entry ;
unsigned int i ;
bool page_allocated ;
2020-12-15 06:06:01 +03:00
struct vma_swap_readahead ra_info = {
. win = 1 ,
} ;
mm, swap: VMA based swap readahead
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory. And the different tasks in the system may have different access
patterns, which makes the global space locality estimation incorrect.
In this patch, when page fault occurs, the virtual pages near the fault
address will be readahead instead of the swap slots near the fault swap
slot in swap device. This avoid to readahead the unrelated swap slots.
At the same time, the swap readahead is changed to work on per-VMA from
globally. So that the different access patterns of the different VMAs
could be distinguished, and the different readahead policy could be
applied accordingly. The original core readahead detection and scaling
algorithm is reused, because it is an effect algorithm to detect the
space locality.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device:
NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:36 +03:00
2018-04-06 02:23:39 +03:00
swap_ra_info ( vmf , & ra_info ) ;
if ( ra_info . win = = 1 )
mm, swap: VMA based swap readahead
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory. And the different tasks in the system may have different access
patterns, which makes the global space locality estimation incorrect.
In this patch, when page fault occurs, the virtual pages near the fault
address will be readahead instead of the swap slots near the fault swap
slot in swap device. This avoid to readahead the unrelated swap slots.
At the same time, the swap readahead is changed to work on per-VMA from
globally. So that the different access patterns of the different VMAs
could be distinguished, and the different readahead policy could be
applied accordingly. The original core readahead detection and scaling
algorithm is reused, because it is an effect algorithm to detect the
space locality.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device:
NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:36 +03:00
goto skip ;
blk_start_plug ( & plug ) ;
2018-04-06 02:23:39 +03:00
for ( i = 0 , pte = ra_info . ptes ; i < ra_info . nr_pte ;
mm, swap: VMA based swap readahead
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory. And the different tasks in the system may have different access
patterns, which makes the global space locality estimation incorrect.
In this patch, when page fault occurs, the virtual pages near the fault
address will be readahead instead of the swap slots near the fault swap
slot in swap device. This avoid to readahead the unrelated swap slots.
At the same time, the swap readahead is changed to work on per-VMA from
globally. So that the different access patterns of the different VMAs
could be distinguished, and the different readahead policy could be
applied accordingly. The original core readahead detection and scaling
algorithm is reused, because it is an effect algorithm to detect the
space locality.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device:
NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:36 +03:00
i + + , pte + + ) {
pentry = * pte ;
if ( pte_none ( pentry ) )
continue ;
if ( pte_present ( pentry ) )
continue ;
entry = pte_to_swp_entry ( pentry ) ;
if ( unlikely ( non_swap_entry ( entry ) ) )
continue ;
page = __read_swap_cache_async ( entry , gfp_mask , vma ,
vmf - > address , & page_allocated ) ;
if ( ! page )
continue ;
if ( page_allocated ) {
swap_readpage ( page , false ) ;
2018-04-06 02:23:39 +03:00
if ( i ! = ra_info . offset ) {
mm, swap: VMA based swap readahead
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory. And the different tasks in the system may have different access
patterns, which makes the global space locality estimation incorrect.
In this patch, when page fault occurs, the virtual pages near the fault
address will be readahead instead of the swap slots near the fault swap
slot in swap device. This avoid to readahead the unrelated swap slots.
At the same time, the swap readahead is changed to work on per-VMA from
globally. So that the different access patterns of the different VMAs
could be distinguished, and the different readahead policy could be
applied accordingly. The original core readahead detection and scaling
algorithm is reused, because it is an effect algorithm to detect the
space locality.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device:
NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:36 +03:00
SetPageReadahead ( page ) ;
count_vm_event ( SWAP_RA ) ;
}
}
put_page ( page ) ;
}
blk_finish_plug ( & plug ) ;
lru_add_drain ( ) ;
skip :
return read_swap_cache_async ( fentry , gfp_mask , vma , vmf - > address ,
2018-04-06 02:23:39 +03:00
ra_info . win = = 1 ) ;
mm, swap: VMA based swap readahead
The swap readahead is an important mechanism to reduce the swap in
latency. Although pure sequential memory access pattern isn't very
popular for anonymous memory, the space locality is still considered
valid.
In the original swap readahead implementation, the consecutive blocks in
swap device are readahead based on the global space locality estimation.
But the consecutive blocks in swap device just reflect the order of page
reclaiming, don't necessarily reflect the access pattern in virtual
memory. And the different tasks in the system may have different access
patterns, which makes the global space locality estimation incorrect.
In this patch, when page fault occurs, the virtual pages near the fault
address will be readahead instead of the swap slots near the fault swap
slot in swap device. This avoid to readahead the unrelated swap slots.
At the same time, the swap readahead is changed to work on per-VMA from
globally. So that the different access patterns of the different VMAs
could be distinguished, and the different readahead policy could be
applied accordingly. The original core readahead detection and scaling
algorithm is reused, because it is an effect algorithm to detect the
space locality.
The test and result is as follow,
Common test condition
=====================
Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device:
NVMe disk
Micro-benchmark with combined access pattern
============================================
vm-scalability, sequential swap test case, 4 processes to eat 50G
virtual memory space, repeat the sequential memory writing until 300
seconds. The first round writing will trigger swap out, the following
rounds will trigger sequential swap in and out.
At the same time, run vm-scalability random swap test case in
background, 8 processes to eat 30G virtual memory space, repeat the
random memory write until 300 seconds. This will trigger random swap-in
in the background.
This is a combined workload with sequential and random memory accessing
at the same time. The result (for sequential workload) is as follow,
Base Optimized
---- ---------
throughput 345413 KB/s 414029 KB/s (+19.9%)
latency.average 97.14 us 61.06 us (-37.1%)
latency.50th 2 us 1 us
latency.60th 2 us 1 us
latency.70th 98 us 2 us
latency.80th 160 us 2 us
latency.90th 260 us 217 us
latency.95th 346 us 369 us
latency.99th 1.34 ms 1.09 ms
ra_hit% 52.69% 99.98%
The original swap readahead algorithm is confused by the background
random access workload, so readahead hit rate is lower. The VMA-base
readahead algorithm works much better.
Linpack
=======
The test memory size is bigger than RAM to trigger swapping.
Base Optimized
---- ---------
elapsed_time 393.49 s 329.88 s (-16.2%)
ra_hit% 86.21% 98.82%
The score of base and optimized kernel hasn't visible changes. But the
elapsed time reduced and readahead hit rate improved, so the optimized
kernel runs better for startup and tear down stages. And the absolute
value of readahead hit rate is high, shows that the space locality is
still valid in some practical workloads.
Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com
Signed-off-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Minchan Kim <minchan@kernel.org>
Cc: Rik van Riel <riel@redhat.com>
Cc: Shaohua Li <shli@kernel.org>
Cc: Hugh Dickins <hughd@google.com>
Cc: Fengguang Wu <fengguang.wu@intel.com>
Cc: Tim Chen <tim.c.chen@intel.com>
Cc: Dave Hansen <dave.hansen@intel.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 02:24:36 +03:00
}
2017-09-07 02:24:40 +03:00
2018-04-06 02:23:42 +03:00
/**
* swapin_readahead - swap in pages in hope we need them soon
* @ entry : swap entry of this memory
* @ gfp_mask : memory allocation flags
* @ vmf : fault information
*
* Returns the struct page for entry and addr , after queueing swapin .
*
* It ' s a main entry function for swap readahead . By the configuration ,
* it will read ahead blocks by cluster - based ( ie , physical disk based )
* or vma - based ( ie , virtual address based on faulty address ) readahead .
*/
struct page * swapin_readahead ( swp_entry_t entry , gfp_t gfp_mask ,
struct vm_fault * vmf )
{
return swap_use_vma_readahead ( ) ?
swap_vma_readahead ( entry , gfp_mask , vmf ) :
swap_cluster_readahead ( entry , gfp_mask , vmf ) ;
}
2017-09-07 02:24:40 +03:00
# ifdef CONFIG_SYSFS
static ssize_t vma_ra_enabled_show ( struct kobject * kobj ,
struct kobj_attribute * attr , char * buf )
{
2020-12-15 06:14:42 +03:00
return sysfs_emit ( buf , " %s \n " ,
enable_vma_readahead ? " true " : " false " ) ;
2017-09-07 02:24:40 +03:00
}
static ssize_t vma_ra_enabled_store ( struct kobject * kobj ,
struct kobj_attribute * attr ,
const char * buf , size_t count )
{
if ( ! strncmp ( buf , " true " , 4 ) | | ! strncmp ( buf , " 1 " , 1 ) )
2018-04-06 02:23:42 +03:00
enable_vma_readahead = true ;
2017-09-07 02:24:40 +03:00
else if ( ! strncmp ( buf , " false " , 5 ) | | ! strncmp ( buf , " 0 " , 1 ) )
2018-04-06 02:23:42 +03:00
enable_vma_readahead = false ;
2017-09-07 02:24:40 +03:00
else
return - EINVAL ;
return count ;
}
static struct kobj_attribute vma_ra_enabled_attr =
__ATTR ( vma_ra_enabled , 0644 , vma_ra_enabled_show ,
vma_ra_enabled_store ) ;
static struct attribute * swap_attrs [ ] = {
& vma_ra_enabled_attr . attr ,
NULL ,
} ;
2021-02-24 23:03:05 +03:00
static const struct attribute_group swap_attr_group = {
2017-09-07 02:24:40 +03:00
. attrs = swap_attrs ,
} ;
static int __init swap_init_sysfs ( void )
{
int err ;
struct kobject * swap_kobj ;
swap_kobj = kobject_create_and_add ( " swap " , mm_kobj ) ;
if ( ! swap_kobj ) {
pr_err ( " failed to create swap kobject \n " ) ;
return - ENOMEM ;
}
err = sysfs_create_group ( swap_kobj , & swap_attr_group ) ;
if ( err ) {
pr_err ( " failed to register swap group \n " ) ;
goto delete_obj ;
}
return 0 ;
delete_obj :
kobject_put ( swap_kobj ) ;
return err ;
}
subsys_initcall ( swap_init_sysfs ) ;
# endif