[RFC PATCH 0/4] Refault distance checking for MGLRU

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From: Kairui Song <kasong@xxxxxxxxxxx>

Hi, linux-mm

I noticed MGLRU not working very well on certain workflows, which is
observed on some instances on some heavily stressed machines.

I found this was related to refault distance detection, when the
file page workingset size exceeds total memory, and the access
distance (the left-shift time of a page before it gets activated,
considering LRU starts from right) of file pages also larger than
total memory. All file pages are stuck on the oldest generation
and getting read-in then evicted permutably, few get activated and
stay in memory.

This series tries to fix this problem by rework the refault distance
detection to better fit MGLRU, and also tries to use a unified
algorithm for both MGLRU and Inactive/Active LRU.

Patch 1/4 reworked the refault distance detection model for
Inactive/Active LRU.

Patch 2/4 and 3/4 are simplification and prepare.

Patch 4/4 applies the modified refault distance detection
for MGLRU.

Following benchmark showed 5x improvement:
To simulate the workflow, I setup a 3-replicated mongodb cluster using
docker, each in a standalone cgroup, set to use 5 gb of cache and 10g
of oplog, on a 32G VM. The benchmark is done using
https://github.com/apavlo/py-tpcc.git, modified to run STOCK_LEVEL
query only, for simulating slow query and get a stable result.

Before the patch (with 10G swap, the result won't change whether
swap is on or not):
$ tpcc.py --config=mongodb.config mongodb --duration=900 --warehouses=500 --clients=30
==================================================================
Execution Results after 904 seconds
------------------------------------------------------------------
                  Executed        Time (µs)       Rate
  STOCK_LEVEL     503             27150226136.4   0.02 txn/s
------------------------------------------------------------------
  TOTAL           503             27150226136.4   0.02 txn/s

$ cat /proc/vmstat | grep working
workingset_nodes 53391
workingset_refault_anon 0
workingset_refault_file 23856735
workingset_activate_anon 0
workingset_activate_file 23845737
workingset_restore_anon 0
workingset_restore_file 18280692
workingset_nodereclaim 1024

$ free -m
              total        used        free      shared  buff/cache   available
Mem:          31837        6752         379          23       24706       24607
Swap:         10239           0       10239

After the patch (with 10G swap on same disk, similar result using ZRAM):
$ tpcc.py --config=mongodb.config mongodb --duration=900 --warehouses=500 --clients=30
==================================================================
Execution Results after 903 seconds
------------------------------------------------------------------
                  Executed        Time (µs)       Rate
  STOCK_LEVEL     2575            27094953498.8   0.10 txn/s
------------------------------------------------------------------
  TOTAL           2575            27094953498.8   0.10 txn/s

$ cat /proc/vmstat | grep working
workingset_nodes 78249
workingset_refault_anon 10139
workingset_refault_file 23001863
workingset_activate_anon 7238
workingset_activate_file 6718032
workingset_restore_anon 7432
workingset_restore_file 6719406
workingset_nodereclaim 9747

$ free -m
              total        used        free      shared  buff/cache   available
Mem:          31837        7376         320           3       24140       24014
Swap:         10239        1662        8577

The performance is 5x times better than before, and the idle anon pages
now can get swapped out as expected. Testing with lower stress also shows
a improvement.

I also checked the benchmark with memtier/memcached and fio,
using similar setup as in commit ac35a4902374 but scaled down to fit in
my test environment:

  memtier test (with 16G ramdisk as swap and 2G cgroup limit):
  memcached -u nobody -m 16384 -s /tmp/memcached.socket -a 0766 \
    -t 12 -B binary &
  memtier_benchmark -S /tmp/memcached.socket -P memcache_binary -n allkeys\
    --key-minimum=1 --key-maximum=24000000 --key-pattern=P:P -c 1 \
    -t 12 --ratio 1:0 --pipeline 8 -d 2000 -x 6

  fio test (with 16G ramdisk on /mnt and 4G cgroup limit):
  fio -name=refault --numjobs=12 --directory=/mnt --size=1024m \
    --buffered=1 --ioengine=io_uring --iodepth=128 \
    --iodepth_batch_submit=32 --iodepth_batch_complete=32 \
    --rw=randread --random_distribution=random --norandommap \
    --time_based --ramp_time=5m --runtime=5m --group_reporting

Before this patch:
memcached:
            Ops/sec     Hits/sec   Misses/sec    Avg. Latency     p50 Latency     p99 Latency   p99.9 Latency       KB/sec
  Best      52832.79         0.00         0.00         1.82042         1.70300         4.54300         6.27100    105641.69
  Worst     46613.56         0.00         0.00         2.05686         1.77500         7.80700        11.83900     93206.05
  Avg (6x)  51024.85         0.00         0.00         1.88506         1.73500         5.43900         9.47100    102026.64
fio:
  read: IOPS=2211k, BW=8637MiB/s (9056MB/s)(2530GiB/300001msec)

After this patch:
memcached:
            Ops/sec     Avg. Latency     p50 Latency     p99 Latency   p99.9 Latency       KB/sec
  Best      54218.92         1.76930         1.65500         4.41500         6.27100    108413.34
  Worst     47640.13         2.01495         1.74300         7.64700        11.64700     95258.72
  Avg (6x)  51408.33         1.86988         1.71900         5.43900         9.34300    102793.42
fio:
  read: IOPS=2166k, BW=8462MiB/s (8873MB/s)(2479GiB/300001msec)

memcached looks ok but there is a %2 performance drop for FIO test,
and after some profiling this is mainly caused by the extra atomic
operations and new functions, there seems to be no LRU accuracy drop.

Sending this as RFC as I'm not entirely sure if this is the right
way to fix this issue, of if this is a generic issue or considered
more of a misconfiguration. Any suggetions about how should I test
it is welcomed.

Signed-off-by: Kairui Song <kasong@xxxxxxxxxxx>

Kairui Song (4):
  workingset: simplify and use a more intuitive model
  workingset: simplify lru_gen_test_recent
  lru_gen: convert avg_total and avg_refaulted to atomic
  workingset, lru_gen: apply refault-distance based re-activation

 include/linux/mmzone.h |   4 +-
 include/linux/swap.h   |   2 -
 mm/swap.c              |   1 -
 mm/vmscan.c            |  18 ++-
 mm/workingset.c        | 315 ++++++++++++++++++++++-------------------
 5 files changed, 179 insertions(+), 161 deletions(-)

-- 
2.41.0





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