selftests/damon: add a test for update_schemes_tried_regions sysfs command

Add a selftest for verifying the accuracy of DAMON's access monitoring
functionality.  The test starts a program of artificial access pattern,
monitor the access pattern using DAMON, and check if DAMON finds expected
amount of hot data region (working set size) with only acceptable error
rate.

Note that the acceptable error rate is set with only naive assumptions and
small number of tests.  Hence failures of the test may not always mean
DAMON is broken.  Rather than that, those could be a signal to better
understand the real accuracy level of DAMON in wider environments.  Based
on further finding, we could optimize DAMON or adjust the expectation of
the test.

Link: https://lkml.kernel.org/r/20231212194810.54457-5-sj@kernel.org
Signed-off-by: SeongJae Park <sj@kernel.org>
Cc: Shuah Khan <shuah@kernel.org>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>

tools/testing/selftests/damon/Makefile

@@ -2,6 +2,7 @@
 # Makefile for damon selftests
 
 TEST_GEN_FILES += huge_count_read_write
+TEST_GEN_FILES += access_memory
 
 TEST_FILES = _chk_dependency.sh _debugfs_common.sh
 TEST_PROGS = debugfs_attrs.sh debugfs_schemes.sh debugfs_target_ids.sh
@@ -9,6 +10,7 @@ TEST_PROGS += debugfs_empty_targets.sh debugfs_huge_count_read_write.sh
 TEST_PROGS += debugfs_duplicate_context_creation.sh
 TEST_PROGS += debugfs_rm_non_contexts.sh
 TEST_PROGS += sysfs.sh sysfs_update_removed_scheme_dir.sh
+TEST_PROGS += sysfs_update_schemes_tried_regions_wss_estimation.py
 TEST_PROGS += reclaim.sh lru_sort.sh
 
 include ../lib.mk

tools/testing/selftests/damon/access_memory.c

@@ -0,0 +1,41 @@
+// SPDX-License-Identifier: GPL-2.0
+/*
+ * Artificial memory access program for testing DAMON.
+ */
+
+#include <stdio.h>
+#include <stdlib.h>
+#include <string.h>
+#include <time.h>
+
+int main(int argc, char *argv[])
+{
+	char **regions;
+	clock_t start_clock;
+	int nr_regions;
+	int sz_region;
+	int access_time_ms;
+	int i;
+
+	if (argc != 4) {
+		printf("Usage: %s <number> <size (bytes)> <time (ms)>\n",
+				argv[0]);
+		return -1;
+	}
+
+	nr_regions = atoi(argv[1]);
+	sz_region = atoi(argv[2]);
+	access_time_ms = atoi(argv[3]);
+
+	regions = malloc(sizeof(*regions) * nr_regions);
+	for (i = 0; i < nr_regions; i++)
+		regions[i] = malloc(sz_region);
+
+	for (i = 0; i < nr_regions; i++) {
+		start_clock = clock();
+		while ((clock() - start_clock) * 1000 / CLOCKS_PER_SEC <
+				access_time_ms)
+			memset(regions[i], i, 1024 * 1024 * 10);
+	}
+	return 0;
+}

tools/testing/selftests/damon/sysfs_update_schemes_tried_regions_wss_estimation.py

@@ -0,0 +1,55 @@
+#!/usr/bin/env python3
+# SPDX-License-Identifier: GPL-2.0
+
+import subprocess
+import time
+
+import _damon_sysfs
+
+def main():
+    # access two 10 MiB memory regions, 2 second per each
+    sz_region = 10 * 1024 * 1024
+    proc = subprocess.Popen(['./access_memory', '2', '%d' % sz_region, '2000'])
+    kdamonds = _damon_sysfs.Kdamonds([_damon_sysfs.Kdamond(
+            contexts=[_damon_sysfs.DamonCtx(
+                ops='vaddr',
+                targets=[_damon_sysfs.DamonTarget(pid=proc.pid)],
+                schemes=[_damon_sysfs.Damos(
+                    access_pattern=_damon_sysfs.DamosAccessPattern(
+                        # >= 25% access rate, >= 200ms age
+                        nr_accesses=[5, 20], age=[2, 2**64 - 1]))] # schemes
+                )] # contexts
+            )]) # kdamonds
+
+    err = kdamonds.start()
+    if err != None:
+        print('kdmaond start failed: %s' % err)
+        exit(1)
+
+    wss_collected = []
+    while proc.poll() == None:
+        time.sleep(0.1)
+        err = kdamonds.kdamonds[0].update_schemes_tried_bytes()
+        if err != None:
+            print('tried bytes update failed: %s' % err)
+            exit(1)
+
+        wss_collected.append(
+                kdamonds.kdamonds[0].contexts[0].schemes[0].tried_bytes)
+
+    wss_collected.sort()
+    acceptable_error_rate = 0.2
+    for percentile in [50, 75]:
+        sample = wss_collected[int(len(wss_collected) * percentile / 100)]
+        error_rate = abs(sample - sz_region) / sz_region
+        print('%d-th percentile (%d) error %f' %
+                (percentile, sample, error_rate))
+        if error_rate > acceptable_error_rate:
+            print('the error rate is not acceptable (> %f)' %
+                    acceptable_error_rate)
+            print('samples are as below')
+            print('\n'.join(['%d' % wss for wss in wss_collected]))
+            exit(1)
+
+if __name__ == '__main__':
+    main()