selftests/damon: implement test for min/max_nr_regions

Implement a kselftest for DAMON's {min,max}_nr_regions' parameters.  The
test ensures both the minimum and the maximum number of regions limit is
respected even if the workload's real number of regions is less than the
minimum or larger than the maximum limits.

Link: https://lkml.kernel.org/r/20240625180538.73134-7-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>
This commit is contained in:
SeongJae Park 2024-06-25 11:05:36 -07:00 committed by Andrew Morton
parent f60636047a
commit 781497347d
2 changed files with 86 additions and 1 deletions

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@ -13,7 +13,7 @@ TEST_PROGS = debugfs_attrs.sh debugfs_schemes.sh debugfs_target_ids.sh
TEST_PROGS += sysfs.sh
TEST_PROGS += sysfs_update_schemes_tried_regions_wss_estimation.py
TEST_PROGS += damos_quota.py damos_quota_goal.py damos_apply_interval.py
TEST_PROGS += damos_tried_regions.py
TEST_PROGS += damos_tried_regions.py damon_nr_regions.py
TEST_PROGS += reclaim.sh lru_sort.sh
# regression tests (reproducers of previously found bugs)

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@ -0,0 +1,85 @@
#!/usr/bin/env python3
# SPDX-License-Identifier: GPL-2.0
import subprocess
import time
import _damon_sysfs
def test_nr_regions(real_nr_regions, min_nr_regions, max_nr_regions):
'''
Create process of the given 'real_nr_regions' regions, monitor it using
DAMON with given '{min,max}_nr_regions' monitoring parameter.
Exit with non-zero return code if the given {min,max}_nr_regions is not
kept.
'''
sz_region = 10 * 1024 * 1024
proc = subprocess.Popen(['./access_memory_even', '%d' % real_nr_regions,
'%d' % sz_region])
# stat every monitored regions
kdamonds = _damon_sysfs.Kdamonds([_damon_sysfs.Kdamond(
contexts=[_damon_sysfs.DamonCtx(
monitoring_attrs=_damon_sysfs.DamonAttrs(
min_nr_regions=min_nr_regions,
max_nr_regions=max_nr_regions),
ops='vaddr',
targets=[_damon_sysfs.DamonTarget(pid=proc.pid)],
schemes=[_damon_sysfs.Damos(action='stat',
)] # schemes
)] # contexts
)]) # kdamonds
err = kdamonds.start()
if err is not None:
proc.terminate()
print('kdamond start failed: %s' % err)
exit(1)
collected_nr_regions = []
while proc.poll() is None:
time.sleep(0.1)
err = kdamonds.kdamonds[0].update_schemes_tried_regions()
if err is not None:
proc.terminate()
print('tried regions update failed: %s' % err)
exit(1)
scheme = kdamonds.kdamonds[0].contexts[0].schemes[0]
if scheme.tried_regions is None:
proc.terminate()
print('tried regions is not collected')
exit(1)
nr_tried_regions = len(scheme.tried_regions)
if nr_tried_regions <= 0:
proc.terminate()
print('tried regions is not created')
exit(1)
collected_nr_regions.append(nr_tried_regions)
if len(collected_nr_regions) > 10:
break
proc.terminate()
kdamonds.stop()
test_name = 'nr_regions test with %d/%d/%d real/min/max nr_regions' % (
real_nr_regions, min_nr_regions, max_nr_regions)
if (collected_nr_regions[0] < min_nr_regions or
collected_nr_regions[-1] > max_nr_regions):
print('fail %s' % test_name)
print('number of regions that collected are:')
for nr in collected_nr_regions:
print(nr)
exit(1)
print('pass %s ' % test_name)
def main():
# test min_nr_regions larger than real nr regions
test_nr_regions(10, 20, 100)
# test max_nr_regions smaller than real nr regions
test_nr_regions(15, 3, 10)
if __name__ == '__main__':
main()