Re: [PATCH 2/2] mm: memcontrol: make cgroup_memory_noswap a static key

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Michal Hocko <mhocko@xxxxxxxx> 于2022年8月30日周二 15:01写道:
>
> On Tue 30-08-22 13:59:49, Kairui Song wrote:
> > From: Kairui Song <kasong@xxxxxxxxxxx>
> >
> > cgroup_memory_noswap is used in many hot path, so make it a static key
> > to lower the kernel overhead.
> >
> > Using 8G of ZRAM as SWAP, benchmark using `perf stat -d -d -d --repeat 100`
> > with the following code snip in a non-root cgroup:
> >
> >    #include <stdio.h>
> >    #include <string.h>
> >    #include <linux/mman.h>
> >    #include <sys/mman.h>
> >    #define MB 1024UL * 1024UL
> >    int main(int argc, char **argv){
> >       void *p = mmap(NULL, 8000 * MB, PROT_READ | PROT_WRITE,
> >                      MAP_PRIVATE | MAP_ANONYMOUS, -1, 0);
> >       memset(p, 0xff, 8000 * MB);
> >       madvise(p, 8000 * MB, MADV_PAGEOUT);
> >       memset(p, 0xff, 8000 * MB);
> >       return 0;
> >    }
> >
> > Before:
> >           7,021.43 msec task-clock                #    0.967 CPUs utilized            ( +-  0.03% )
> >              4,010      context-switches          #  573.853 /sec                     ( +-  0.01% )
> >                  0      cpu-migrations            #    0.000 /sec
> >          2,052,057      page-faults               #  293.661 K/sec                    ( +-  0.00% )
> >     12,616,546,027      cycles                    #    1.805 GHz                      ( +-  0.06% )  (39.92%)
> >        156,823,666      stalled-cycles-frontend   #    1.25% frontend cycles idle     ( +-  0.10% )  (40.25%)
> >        310,130,812      stalled-cycles-backend    #    2.47% backend cycles idle      ( +-  4.39% )  (40.73%)
> >     18,692,516,591      instructions              #    1.49  insn per cycle
> >                                                   #    0.01  stalled cycles per insn  ( +-  0.04% )  (40.75%)
> >      4,907,447,976      branches                  #  702.283 M/sec                    ( +-  0.05% )  (40.30%)
> >         13,002,578      branch-misses             #    0.26% of all branches          ( +-  0.08% )  (40.48%)
> >      7,069,786,296      L1-dcache-loads           #    1.012 G/sec                    ( +-  0.03% )  (40.32%)
> >        649,385,847      L1-dcache-load-misses     #    9.13% of all L1-dcache accesses  ( +-  0.07% )  (40.10%)
> >      1,485,448,688      L1-icache-loads           #  212.576 M/sec                    ( +-  0.15% )  (39.49%)
> >         31,628,457      L1-icache-load-misses     #    2.13% of all L1-icache accesses  ( +-  0.40% )  (39.57%)
> >          6,667,311      dTLB-loads                #  954.129 K/sec                    ( +-  0.21% )  (39.50%)
> >          5,668,555      dTLB-load-misses          #   86.40% of all dTLB cache accesses  ( +-  0.12% )  (39.03%)
> >                765      iTLB-loads                #  109.476 /sec                     ( +- 21.81% )  (39.44%)
> >          4,370,351      iTLB-load-misses          # 214320.09% of all iTLB cache accesses  ( +-  1.44% )  (39.86%)
> >        149,207,254      L1-dcache-prefetches      #   21.352 M/sec                    ( +-  0.13% )  (40.27%)
> >
> >            7.25869 +- 0.00203 seconds time elapsed  ( +-  0.03% )
> >
> > After:
> >           6,576.16 msec task-clock                #    0.953 CPUs utilized            ( +-  0.10% )
> >              4,020      context-switches          #  605.595 /sec                     ( +-  0.01% )
> >                  0      cpu-migrations            #    0.000 /sec
> >          2,052,056      page-faults               #  309.133 K/sec                    ( +-  0.00% )
> >     11,967,619,180      cycles                    #    1.803 GHz                      ( +-  0.36% )  (38.76%)
> >        161,259,240      stalled-cycles-frontend   #    1.38% frontend cycles idle     ( +-  0.27% )  (36.58%)
> >        253,605,302      stalled-cycles-backend    #    2.16% backend cycles idle      ( +-  4.45% )  (34.78%)
> >     19,328,171,892      instructions              #    1.65  insn per cycle
> >                                                   #    0.01  stalled cycles per insn  ( +-  0.10% )  (31.46%)
> >      5,213,967,902      branches                  #  785.461 M/sec                    ( +-  0.18% )  (30.68%)
> >         12,385,170      branch-misses             #    0.24% of all branches          ( +-  0.26% )  (34.13%)
> >      7,271,687,822      L1-dcache-loads           #    1.095 G/sec                    ( +-  0.12% )  (35.29%)
> >        649,873,045      L1-dcache-load-misses     #    8.93% of all L1-dcache accesses  ( +-  0.11% )  (41.41%)
> >      1,950,037,608      L1-icache-loads           #  293.764 M/sec                    ( +-  0.33% )  (43.11%)
> >         31,365,566      L1-icache-load-misses     #    1.62% of all L1-icache accesses  ( +-  0.39% )  (45.89%)
> >          6,767,809      dTLB-loads                #    1.020 M/sec                    ( +-  0.47% )  (48.42%)
> >          6,339,590      dTLB-load-misses          #   95.43% of all dTLB cache accesses  ( +-  0.50% )  (46.60%)
> >                736      iTLB-loads                #  110.875 /sec                     ( +-  1.79% )  (48.60%)
> >          4,314,836      iTLB-load-misses          # 518653.73% of all iTLB cache accesses  ( +-  0.63% )  (42.91%)
> >        144,950,156      L1-dcache-prefetches      #   21.836 M/sec                    ( +-  0.37% )  (41.39%)
> >
> >            6.89935 +- 0.00703 seconds time elapsed  ( +-  0.10% )
>
> Do you happen to have a perf profile before and after to see which of
> the paths really benefits from this?

No I don't have a clear profile data about which path benefit the most.
The performance benchmark result can be stably reproduced, but perf
record & report & diff doesn't seems too helpful, as I can't see a
significant change of any single symbols.

There are quite a few callers of memcg_swap_enabled and
do_memsw_account (which also calls memcg_swap_enabled), to me, it
seems multiple pieces of optimization caused an overall improvement.
And a lower overhead for the branch predictor may also help in
general.

Any other suggestion about how to collect such data?





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