为什么 gcc -march=znver1 限制 uint64_t 向量化?

发布于 2025-01-20 15:26:18 字数 20048 浏览 5 评论 0原文

我试图确保 gcc 对我的循环进行矢量化。事实证明,通过使用 -march=znver1 (或 -march=native),gcc 会跳过一些循环,即使它们可以矢量化。为什么会出现这种情况?

在此代码中,将每个元素乘以标量的第二个循环未矢量化:

#include <stdio.h>
#include <inttypes.h>

int main() {
    const size_t N = 1000;
    uint64_t arr[N];
    for (size_t i = 0; i < N; ++i)
        arr[i] = 1;

    for (size_t i = 0; i < N; ++i)
        arr[i] *= 5;

    for (size_t i = 0; i < N; ++i)
        printf("%lu\n", arr[i]); // use the array so that it is not optimized away
}

gcc -O3 -fopt-info-vec-all -mavx2 main.c:

main.cpp:13:26: missed: couldn't vectorize loop
main.cpp:14:15: missed: statement clobbers memory: printf ("%lu\n", _3);
main.cpp:10:26: optimized: loop vectorized using 32 byte vectors
main.cpp:7:26: optimized: loop vectorized using 32 byte vectors
main.cpp:4:5: note: vectorized 2 loops in function.
main.cpp:14:15: missed: statement clobbers memory: printf ("%lu\n", _3);
main.cpp:15:1: note: ***** Analysis failed with vector mode V4DI
main.cpp:15:1: note: ***** Skipping vector mode V32QI, which would repeat the analysis for V4DI

gcc -O3 - fopt-info-vec-all -march=znver1 main.c:

main.cpp:13:26: missed: couldn't vectorize loop
main.cpp:14:15: missed: statement clobbers memory: printf ("%lu\n", _3);
main.cpp:10:26: missed: couldn't vectorize loop
main.cpp:10:26: missed: not vectorized: unsupported data-type
main.cpp:7:26: optimized: loop vectorized using 16 byte vectors
main.cpp:4:5: note: vectorized 1 loops in function.
main.cpp:14:15: missed: statement clobbers memory: printf ("%lu\n", _3);
main.cpp:15:1: note: ***** Analysis failed with vector mode V2DI
main.cpp:15:1: note: ***** Skipping vector mode V16QI, which would repeat the analysis for V2DI

-march=znver1 包含 -mavx2,所以我认为由于某种原因,gcc 选择不对其进行向量化:

~ $ gcc -march=znver1 -Q --help=target
The following options are target specific:
  -m128bit-long-double              [enabled]
  -m16                              [disabled]
  -m32                              [disabled]
  -m3dnow                           [disabled]
  -m3dnowa                          [disabled]
  -m64                              [enabled]
  -m80387                           [enabled]
  -m8bit-idiv                       [disabled]
  -m96bit-long-double               [disabled]
  -mabi=                            sysv
  -mabm                             [enabled]
  -maccumulate-outgoing-args        [disabled]
  -maddress-mode=                   long
  -madx                             [enabled]
  -maes                             [enabled]
  -malign-data=                     compat
  -malign-double                    [disabled]
  -malign-functions=                0
  -malign-jumps=                    0
  -malign-loops=                    0
  -malign-stringops                 [enabled]
  -mamx-bf16                        [disabled]
  -mamx-int8                        [disabled]
  -mamx-tile                        [disabled]
  -mandroid                         [disabled]
  -march=                           znver1
  -masm=                            att
  -mavx                             [enabled]
  -mavx2                            [enabled]
  -mavx256-split-unaligned-load     [disabled]
  -mavx256-split-unaligned-store    [enabled]
  -mavx5124fmaps                    [disabled]
  -mavx5124vnniw                    [disabled]
  -mavx512bf16                      [disabled]
  -mavx512bitalg                    [disabled]
  -mavx512bw                        [disabled]
  -mavx512cd                        [disabled]
  -mavx512dq                        [disabled]
  -mavx512er                        [disabled]
  -mavx512f                         [disabled]
  -mavx512ifma                      [disabled]
  -mavx512pf                        [disabled]
  -mavx512vbmi                      [disabled]
  -mavx512vbmi2                     [disabled]
  -mavx512vl                        [disabled]
  -mavx512vnni                      [disabled]
  -mavx512vp2intersect              [disabled]
  -mavx512vpopcntdq                 [disabled]
  -mavxvnni                         [disabled]
  -mbionic                          [disabled]
  -mbmi                             [enabled]
  -mbmi2                            [enabled]
  -mbranch-cost=<0,5>               3
  -mcall-ms2sysv-xlogues            [disabled]
  -mcet-switch                      [disabled]
  -mcld                             [disabled]
  -mcldemote                        [disabled]
  -mclflushopt                      [enabled]
  -mclwb                            [disabled]
  -mclzero                          [enabled]
  -mcmodel=                         [default]
  -mcpu=                            
  -mcrc32                           [disabled]
  -mcx16                            [enabled]
  -mdispatch-scheduler              [disabled]
  -mdump-tune-features              [disabled]
  -menqcmd                          [disabled]
  -mf16c                            [enabled]
  -mfancy-math-387                  [enabled]
  -mfentry                          [disabled]
  -mfentry-name=                    
  -mfentry-section=                 
  -mfma                             [enabled]
  -mfma4                            [disabled]
  -mforce-drap                      [disabled]
  -mforce-indirect-call             [disabled]
  -mfp-ret-in-387                   [enabled]
  -mfpmath=                         sse
  -mfsgsbase                        [enabled]
  -mfunction-return=                keep
  -mfused-madd                      -ffp-contract=fast
  -mfxsr                            [enabled]
  -mgeneral-regs-only               [disabled]
  -mgfni                            [disabled]
  -mglibc                           [enabled]
  -mhard-float                      [enabled]
  -mhle                             [disabled]
  -mhreset                          [disabled]
  -miamcu                           [disabled]
  -mieee-fp                         [enabled]
  -mincoming-stack-boundary=        0
  -mindirect-branch-register        [disabled]
  -mindirect-branch=                keep
  -minline-all-stringops            [disabled]
  -minline-stringops-dynamically    [disabled]
  -minstrument-return=              none
  -mintel-syntax                    -masm=intel
  -mkl                              [disabled]
  -mlarge-data-threshold=<number>   65536
  -mlong-double-128                 [disabled]
  -mlong-double-64                  [disabled]
  -mlong-double-80                  [enabled]
  -mlwp                             [disabled]
  -mlzcnt                           [enabled]
  -mmanual-endbr                    [disabled]
  -mmemcpy-strategy=                
  -mmemset-strategy=                
  -mmitigate-rop                    [disabled]
  -mmmx                             [enabled]
  -mmovbe                           [enabled]
  -mmovdir64b                       [disabled]
  -mmovdiri                         [disabled]
  -mmpx                             [disabled]
  -mms-bitfields                    [disabled]
  -mmusl                            [disabled]
  -mmwaitx                          [enabled]
  -mneeded                          [disabled]
  -mno-align-stringops              [disabled]
  -mno-default                      [disabled]
  -mno-fancy-math-387               [disabled]
  -mno-push-args                    [disabled]
  -mno-red-zone                     [disabled]
  -mno-sse4                         [disabled]
  -mnop-mcount                      [disabled]
  -momit-leaf-frame-pointer         [disabled]
  -mpc32                            [disabled]
  -mpc64                            [disabled]
  -mpc80                            [disabled]
  -mpclmul                          [enabled]
  -mpcommit                         [disabled]
  -mpconfig                         [disabled]
  -mpku                             [disabled]
  -mpopcnt                          [enabled]
  -mprefer-avx128                   -mprefer-vector-width=128
  -mprefer-vector-width=            128
  -mpreferred-stack-boundary=       0
  -mprefetchwt1                     [disabled]
  -mprfchw                          [enabled]
  -mptwrite                         [disabled]
  -mpush-args                       [enabled]
  -mrdpid                           [disabled]
  -mrdrnd                           [enabled]
  -mrdseed                          [enabled]
  -mrecip                           [disabled]
  -mrecip=                          
  -mrecord-mcount                   [disabled]
  -mrecord-return                   [disabled]
  -mred-zone                        [enabled]
  -mregparm=                        6
  -mrtd                             [disabled]
  -mrtm                             [disabled]
  -msahf                            [enabled]
  -mserialize                       [disabled]
  -msgx                             [disabled]
  -msha                             [enabled]
  -mshstk                           [disabled]
  -mskip-rax-setup                  [disabled]
  -msoft-float                      [disabled]
  -msse                             [enabled]
  -msse2                            [enabled]
  -msse2avx                         [disabled]
  -msse3                            [enabled]
  -msse4                            [enabled]
  -msse4.1                          [enabled]
  -msse4.2                          [enabled]
  -msse4a                           [enabled]
  -msse5                            -mavx
  -msseregparm                      [disabled]
  -mssse3                           [enabled]
  -mstack-arg-probe                 [disabled]
  -mstack-protector-guard-offset=   
  -mstack-protector-guard-reg=      
  -mstack-protector-guard-symbol=   
  -mstack-protector-guard=          tls
  -mstackrealign                    [disabled]
  -mstringop-strategy=              [default]
  -mstv                             [enabled]
  -mtbm                             [disabled]
  -mtls-dialect=                    gnu
  -mtls-direct-seg-refs             [enabled]
  -mtsxldtrk                        [disabled]
  -mtune-ctrl=                      
  -mtune=                           znver1
  -muclibc                          [disabled]
  -muintr                           [disabled]
  -mvaes                            [disabled]
  -mveclibabi=                      [default]
  -mvect8-ret-in-mem                [disabled]
  -mvpclmulqdq                      [disabled]
  -mvzeroupper                      [enabled]
  -mwaitpkg                         [disabled]
  -mwbnoinvd                        [disabled]
  -mwidekl                          [disabled]
  -mx32                             [disabled]
  -mxop                             [disabled]
  -mxsave                           [enabled]
  -mxsavec                          [enabled]
  -mxsaveopt                        [enabled]
  -mxsaves                          [enabled]

  Known assembler dialects (for use with the -masm= option):
    att intel

  Known ABIs (for use with the -mabi= option):
    ms sysv

  Known code models (for use with the -mcmodel= option):
    32 kernel large medium small

  Valid arguments to -mfpmath=:
    387 387+sse 387,sse both sse sse+387 sse,387

  Known indirect branch choices (for use with the -mindirect-branch=/-mfunction-return= options):
    keep thunk thunk-extern thunk-inline

  Known choices for return instrumentation with -minstrument-return=:
    call none nop5

  Known data alignment choices (for use with the -malign-data= option):
    abi cacheline compat

  Known vectorization library ABIs (for use with the -mveclibabi= option):
    acml svml

  Known address mode (for use with the -maddress-mode= option):
    long short

  Known preferred register vector length (to use with the -mprefer-vector-width= option):
    128 256 512 none

  Known stack protector guard (for use with the -mstack-protector-guard= option):
    global tls

  Valid arguments to -mstringop-strategy=:
    byte_loop libcall loop rep_4byte rep_8byte rep_byte unrolled_loop vector_loop

  Known TLS dialects (for use with the -mtls-dialect= option):
    gnu gnu2

  Known valid arguments for -march= option:
    i386 i486 i586 pentium lakemont pentium-mmx winchip-c6 winchip2 c3 samuel-2 c3-2 nehemiah c7 esther i686 pentiumpro pentium2 pentium3 pentium3m pentium-m pentium4 pentium4m prescott nocona core2 nehalem corei7 westmere sandybridge corei7-avx ivybridge core-avx-i haswell core-avx2 broadwell skylake skylake-avx512 cannonlake icelake-client rocketlake icelake-server cascadelake tigerlake cooperlake sapphirerapids alderlake bonnell atom silvermont slm goldmont goldmont-plus tremont knl knm intel geode k6 k6-2 k6-3 athlon athlon-tbird athlon-4 athlon-xp athlon-mp x86-64 x86-64-v2 x86-64-v3 x86-64-v4 eden-x2 nano nano-1000 nano-2000 nano-3000 nano-x2 eden-x4 nano-x4 k8 k8-sse3 opteron opteron-sse3 athlon64 athlon64-sse3 athlon-fx amdfam10 barcelona bdver1 bdver2 bdver3 bdver4 znver1 znver2 znver3 btver1 btver2 generic native

  Known valid arguments for -mtune= option:
    generic i386 i486 pentium lakemont pentiumpro pentium4 nocona core2 nehalem sandybridge haswell bonnell silvermont goldmont goldmont-plus tremont knl knm skylake skylake-avx512 cannonlake icelake-client icelake-server cascadelake tigerlake cooperlake sapphirerapids alderlake rocketlake intel geode k6 athlon k8 amdfam10 bdver1 bdver2 bdver3 bdver4 btver1 btver2 znver1 znver2 znver3

我也尝试过 clang,在这两种情况下,我相信循环都是由 32 字节向量向量化的: 备注:矢量化循环(矢量化宽度:4,交错计数:4)

我正在使用 gcc 11.2.0

编辑: 根据彼得·科德斯的要求 我意识到我实际上用乘以 4 进行基准测试已经有一段时间了。

Makefile:

all:
    gcc -O3 -mavx2 main.c -o 3
    gcc -O3 -march=znver2 main.c -o 32  
    gcc -O3 -march=znver2 main.c -mprefer-vector-width=128 -o 32128
    gcc -O3 -march=znver1 main.c -o 31
    gcc -O2 -mavx2 main.c -o 2
    gcc -O2 -march=znver2 main.c -o 22
    gcc -O2 -march=znver2 main.c -mprefer-vector-width=128 -o 22128
    gcc -O2 -march=znver1 main.c -o 21
    hyperfine -r5 ./3 ./32 ./32128 ./31 ./2 ./22 ./22128 ./21

clean:
    rm ./3 ./32 ./32128 ./31 ./2 ./22 ./22128 ./21

代码:

#include <stdio.h>
#include <inttypes.h>
#include <stdlib.h>
#include <time.h>

int main() {
    const size_t N = 500;
    uint64_t arr[N];
    for (size_t i = 0; i < N; ++i)
        arr[i] = 1;

    for (int j = 0; j < 20000000; ++j)
        for (size_t i = 0; i < N; ++i)
            arr[i] *= 4;

    srand(time(0));
    printf("%lu\n", arr[rand() % N]); // use the array so that it is not optimized away
}

N = 500, arr[i] *= 4:

Benchmark 1: ./3
  Time (mean ± σ):      1.780 s ±  0.011 s    [User: 1.778 s, System: 0.000 s]
  Range (min … max):    1.763 s …  1.791 s    5 runs

Benchmark 2: ./32
  Time (mean ± σ):      1.785 s ±  0.016 s    [User: 1.783 s, System: 0.000 s]
  Range (min … max):    1.773 s …  1.810 s    5 runs

Benchmark 3: ./32128
  Time (mean ± σ):      1.740 s ±  0.026 s    [User: 1.737 s, System: 0.000 s]
  Range (min … max):    1.724 s …  1.785 s    5 runs

Benchmark 4: ./31
  Time (mean ± σ):      1.757 s ±  0.022 s    [User: 1.754 s, System: 0.000 s]
  Range (min … max):    1.727 s …  1.785 s    5 runs

Benchmark 5: ./2
  Time (mean ± σ):      3.467 s ±  0.031 s    [User: 3.462 s, System: 0.000 s]
  Range (min … max):    3.443 s …  3.519 s    5 runs

Benchmark 6: ./22
  Time (mean ± σ):      3.475 s ±  0.028 s    [User: 3.469 s, System: 0.001 s]
  Range (min … max):    3.447 s …  3.512 s    5 runs

Benchmark 7: ./22128
  Time (mean ± σ):      3.464 s ±  0.034 s    [User: 3.459 s, System: 0.001 s]
  Range (min … max):    3.431 s …  3.509 s    5 runs

Benchmark 8: ./21
  Time (mean ± σ):      3.465 s ±  0.013 s    [User: 3.460 s, System: 0.001 s]
  Range (min … max):    3.443 s …  3.475 s    5 runs

N = 500, arr[i] *= 5:

Benchmark 1: ./3
  Time (mean ± σ):      1.789 s ±  0.004 s    [User: 1.786 s, System: 0.001 s]
  Range (min … max):    1.783 s …  1.793 s    5 runs

Benchmark 2: ./32
  Time (mean ± σ):      1.772 s ±  0.017 s    [User: 1.769 s, System: 0.000 s]
  Range (min … max):    1.755 s …  1.800 s    5 runs

Benchmark 3: ./32128
  Time (mean ± σ):      2.911 s ±  0.023 s    [User: 2.907 s, System: 0.001 s]
  Range (min … max):    2.880 s …  2.943 s    5 runs

Benchmark 4: ./31
  Time (mean ± σ):      2.924 s ±  0.013 s    [User: 2.921 s, System: 0.000 s]
  Range (min … max):    2.906 s …  2.934 s    5 runs

Benchmark 5: ./2
  Time (mean ± σ):      3.850 s ±  0.029 s    [User: 3.846 s, System: 0.000 s]
  Range (min … max):    3.823 s …  3.896 s    5 runs

Benchmark 6: ./22
  Time (mean ± σ):      3.816 s ±  0.036 s    [User: 3.812 s, System: 0.000 s]
  Range (min … max):    3.777 s …  3.855 s    5 runs

Benchmark 7: ./22128
  Time (mean ± σ):      3.813 s ±  0.026 s    [User: 3.809 s, System: 0.000 s]
  Range (min … max):    3.780 s …  3.834 s    5 runs

Benchmark 8: ./21
  Time (mean ± σ):      3.783 s ±  0.010 s    [User: 3.779 s, System: 0.000 s]
  Range (min … max):    3.773 s …  3.798 s    5 runs

N = 512, arr [i] *= 4

Benchmark 1: ./3
  Time (mean ± σ):      1.849 s ±  0.015 s    [User: 1.847 s, System: 0.000 s]
  Range (min … max):    1.831 s …  1.873 s    5 runs

Benchmark 2: ./32
  Time (mean ± σ):      1.846 s ±  0.013 s    [User: 1.844 s, System: 0.001 s]
  Range (min … max):    1.832 s …  1.860 s    5 runs

Benchmark 3: ./32128
  Time (mean ± σ):      1.756 s ±  0.012 s    [User: 1.754 s, System: 0.000 s]
  Range (min … max):    1.744 s …  1.771 s    5 runs

Benchmark 4: ./31
  Time (mean ± σ):      1.788 s ±  0.012 s    [User: 1.785 s, System: 0.001 s]
  Range (min … max):    1.774 s …  1.801 s    5 runs

Benchmark 5: ./2
  Time (mean ± σ):      3.476 s ±  0.015 s    [User: 3.472 s, System: 0.001 s]
  Range (min … max):    3.458 s …  3.494 s    5 runs

Benchmark 6: ./22
  Time (mean ± σ):      3.449 s ±  0.002 s    [User: 3.446 s, System: 0.000 s]
  Range (min … max):    3.446 s …  3.452 s    5 runs

Benchmark 7: ./22128
  Time (mean ± σ):      3.456 s ±  0.007 s    [User: 3.453 s, System: 0.000 s]
  Range (min … max):    3.446 s …  3.462 s    5 runs

Benchmark 8: ./21
  Time (mean ± σ):      3.547 s ±  0.044 s    [User: 3.542 s, System: 0.001 s]
  Range (min … max):    3.482 s …  3.600 s    5 runs

N = 512, arr[i] *= 5

Benchmark 1: ./3
  Time (mean ± σ):      1.847 s ±  0.013 s    [User: 1.845 s, System: 0.000 s]
  Range (min … max):    1.836 s …  1.863 s    5 runs

Benchmark 2: ./32
  Time (mean ± σ):      1.830 s ±  0.007 s    [User: 1.827 s, System: 0.001 s]
  Range (min … max):    1.820 s …  1.837 s    5 runs

Benchmark 3: ./32128
  Time (mean ± σ):      2.983 s ±  0.017 s    [User: 2.980 s, System: 0.000 s]
  Range (min … max):    2.966 s …  3.012 s    5 runs

Benchmark 4: ./31
  Time (mean ± σ):      3.026 s ±  0.039 s    [User: 3.021 s, System: 0.001 s]
  Range (min … max):    2.989 s …  3.089 s    5 runs

Benchmark 5: ./2
  Time (mean ± σ):      4.000 s ±  0.021 s    [User: 3.994 s, System: 0.001 s]
  Range (min … max):    3.982 s …  4.035 s    5 runs

Benchmark 6: ./22
  Time (mean ± σ):      3.940 s ±  0.041 s    [User: 3.934 s, System: 0.001 s]
  Range (min … max):    3.890 s …  3.981 s    5 runs

Benchmark 7: ./22128
  Time (mean ± σ):      3.928 s ±  0.032 s    [User: 3.922 s, System: 0.001 s]
  Range (min … max):    3.898 s …  3.979 s    5 runs

Benchmark 8: ./21
  Time (mean ± σ):      3.908 s ±  0.029 s    [User: 3.904 s, System: 0.000 s]
  Range (min … max):    3.879 s …  3.954 s    5 runs

我认为运行在 -O2 -march=znver1-O3 -march=znver1 的速度相同,这是我在文件命名方面的一个错误,当时我还没有创建 makefile,我正在使用 shell 的历史记录。

I'm trying to make sure gcc vectorizes my loops. It turns out, that by using -march=znver1 (or -march=native) gcc skips some loops even though they can be vectorized. Why does this happen?

In this code, the second loop, which multiplies each element by a scalar is not vectorised:

#include <stdio.h>
#include <inttypes.h>

int main() {
    const size_t N = 1000;
    uint64_t arr[N];
    for (size_t i = 0; i < N; ++i)
        arr[i] = 1;

    for (size_t i = 0; i < N; ++i)
        arr[i] *= 5;

    for (size_t i = 0; i < N; ++i)
        printf("%lu\n", arr[i]); // use the array so that it is not optimized away
}

gcc -O3 -fopt-info-vec-all -mavx2 main.c:

main.cpp:13:26: missed: couldn't vectorize loop
main.cpp:14:15: missed: statement clobbers memory: printf ("%lu\n", _3);
main.cpp:10:26: optimized: loop vectorized using 32 byte vectors
main.cpp:7:26: optimized: loop vectorized using 32 byte vectors
main.cpp:4:5: note: vectorized 2 loops in function.
main.cpp:14:15: missed: statement clobbers memory: printf ("%lu\n", _3);
main.cpp:15:1: note: ***** Analysis failed with vector mode V4DI
main.cpp:15:1: note: ***** Skipping vector mode V32QI, which would repeat the analysis for V4DI

gcc -O3 -fopt-info-vec-all -march=znver1 main.c:

main.cpp:13:26: missed: couldn't vectorize loop
main.cpp:14:15: missed: statement clobbers memory: printf ("%lu\n", _3);
main.cpp:10:26: missed: couldn't vectorize loop
main.cpp:10:26: missed: not vectorized: unsupported data-type
main.cpp:7:26: optimized: loop vectorized using 16 byte vectors
main.cpp:4:5: note: vectorized 1 loops in function.
main.cpp:14:15: missed: statement clobbers memory: printf ("%lu\n", _3);
main.cpp:15:1: note: ***** Analysis failed with vector mode V2DI
main.cpp:15:1: note: ***** Skipping vector mode V16QI, which would repeat the analysis for V2DI

-march=znver1 includes -mavx2, so I think gcc chooses not to vectorise it for some reason:

~ $ gcc -march=znver1 -Q --help=target
The following options are target specific:
  -m128bit-long-double              [enabled]
  -m16                              [disabled]
  -m32                              [disabled]
  -m3dnow                           [disabled]
  -m3dnowa                          [disabled]
  -m64                              [enabled]
  -m80387                           [enabled]
  -m8bit-idiv                       [disabled]
  -m96bit-long-double               [disabled]
  -mabi=                            sysv
  -mabm                             [enabled]
  -maccumulate-outgoing-args        [disabled]
  -maddress-mode=                   long
  -madx                             [enabled]
  -maes                             [enabled]
  -malign-data=                     compat
  -malign-double                    [disabled]
  -malign-functions=                0
  -malign-jumps=                    0
  -malign-loops=                    0
  -malign-stringops                 [enabled]
  -mamx-bf16                        [disabled]
  -mamx-int8                        [disabled]
  -mamx-tile                        [disabled]
  -mandroid                         [disabled]
  -march=                           znver1
  -masm=                            att
  -mavx                             [enabled]
  -mavx2                            [enabled]
  -mavx256-split-unaligned-load     [disabled]
  -mavx256-split-unaligned-store    [enabled]
  -mavx5124fmaps                    [disabled]
  -mavx5124vnniw                    [disabled]
  -mavx512bf16                      [disabled]
  -mavx512bitalg                    [disabled]
  -mavx512bw                        [disabled]
  -mavx512cd                        [disabled]
  -mavx512dq                        [disabled]
  -mavx512er                        [disabled]
  -mavx512f                         [disabled]
  -mavx512ifma                      [disabled]
  -mavx512pf                        [disabled]
  -mavx512vbmi                      [disabled]
  -mavx512vbmi2                     [disabled]
  -mavx512vl                        [disabled]
  -mavx512vnni                      [disabled]
  -mavx512vp2intersect              [disabled]
  -mavx512vpopcntdq                 [disabled]
  -mavxvnni                         [disabled]
  -mbionic                          [disabled]
  -mbmi                             [enabled]
  -mbmi2                            [enabled]
  -mbranch-cost=<0,5>               3
  -mcall-ms2sysv-xlogues            [disabled]
  -mcet-switch                      [disabled]
  -mcld                             [disabled]
  -mcldemote                        [disabled]
  -mclflushopt                      [enabled]
  -mclwb                            [disabled]
  -mclzero                          [enabled]
  -mcmodel=                         [default]
  -mcpu=                            
  -mcrc32                           [disabled]
  -mcx16                            [enabled]
  -mdispatch-scheduler              [disabled]
  -mdump-tune-features              [disabled]
  -menqcmd                          [disabled]
  -mf16c                            [enabled]
  -mfancy-math-387                  [enabled]
  -mfentry                          [disabled]
  -mfentry-name=                    
  -mfentry-section=                 
  -mfma                             [enabled]
  -mfma4                            [disabled]
  -mforce-drap                      [disabled]
  -mforce-indirect-call             [disabled]
  -mfp-ret-in-387                   [enabled]
  -mfpmath=                         sse
  -mfsgsbase                        [enabled]
  -mfunction-return=                keep
  -mfused-madd                      -ffp-contract=fast
  -mfxsr                            [enabled]
  -mgeneral-regs-only               [disabled]
  -mgfni                            [disabled]
  -mglibc                           [enabled]
  -mhard-float                      [enabled]
  -mhle                             [disabled]
  -mhreset                          [disabled]
  -miamcu                           [disabled]
  -mieee-fp                         [enabled]
  -mincoming-stack-boundary=        0
  -mindirect-branch-register        [disabled]
  -mindirect-branch=                keep
  -minline-all-stringops            [disabled]
  -minline-stringops-dynamically    [disabled]
  -minstrument-return=              none
  -mintel-syntax                    -masm=intel
  -mkl                              [disabled]
  -mlarge-data-threshold=<number>   65536
  -mlong-double-128                 [disabled]
  -mlong-double-64                  [disabled]
  -mlong-double-80                  [enabled]
  -mlwp                             [disabled]
  -mlzcnt                           [enabled]
  -mmanual-endbr                    [disabled]
  -mmemcpy-strategy=                
  -mmemset-strategy=                
  -mmitigate-rop                    [disabled]
  -mmmx                             [enabled]
  -mmovbe                           [enabled]
  -mmovdir64b                       [disabled]
  -mmovdiri                         [disabled]
  -mmpx                             [disabled]
  -mms-bitfields                    [disabled]
  -mmusl                            [disabled]
  -mmwaitx                          [enabled]
  -mneeded                          [disabled]
  -mno-align-stringops              [disabled]
  -mno-default                      [disabled]
  -mno-fancy-math-387               [disabled]
  -mno-push-args                    [disabled]
  -mno-red-zone                     [disabled]
  -mno-sse4                         [disabled]
  -mnop-mcount                      [disabled]
  -momit-leaf-frame-pointer         [disabled]
  -mpc32                            [disabled]
  -mpc64                            [disabled]
  -mpc80                            [disabled]
  -mpclmul                          [enabled]
  -mpcommit                         [disabled]
  -mpconfig                         [disabled]
  -mpku                             [disabled]
  -mpopcnt                          [enabled]
  -mprefer-avx128                   -mprefer-vector-width=128
  -mprefer-vector-width=            128
  -mpreferred-stack-boundary=       0
  -mprefetchwt1                     [disabled]
  -mprfchw                          [enabled]
  -mptwrite                         [disabled]
  -mpush-args                       [enabled]
  -mrdpid                           [disabled]
  -mrdrnd                           [enabled]
  -mrdseed                          [enabled]
  -mrecip                           [disabled]
  -mrecip=                          
  -mrecord-mcount                   [disabled]
  -mrecord-return                   [disabled]
  -mred-zone                        [enabled]
  -mregparm=                        6
  -mrtd                             [disabled]
  -mrtm                             [disabled]
  -msahf                            [enabled]
  -mserialize                       [disabled]
  -msgx                             [disabled]
  -msha                             [enabled]
  -mshstk                           [disabled]
  -mskip-rax-setup                  [disabled]
  -msoft-float                      [disabled]
  -msse                             [enabled]
  -msse2                            [enabled]
  -msse2avx                         [disabled]
  -msse3                            [enabled]
  -msse4                            [enabled]
  -msse4.1                          [enabled]
  -msse4.2                          [enabled]
  -msse4a                           [enabled]
  -msse5                            -mavx
  -msseregparm                      [disabled]
  -mssse3                           [enabled]
  -mstack-arg-probe                 [disabled]
  -mstack-protector-guard-offset=   
  -mstack-protector-guard-reg=      
  -mstack-protector-guard-symbol=   
  -mstack-protector-guard=          tls
  -mstackrealign                    [disabled]
  -mstringop-strategy=              [default]
  -mstv                             [enabled]
  -mtbm                             [disabled]
  -mtls-dialect=                    gnu
  -mtls-direct-seg-refs             [enabled]
  -mtsxldtrk                        [disabled]
  -mtune-ctrl=                      
  -mtune=                           znver1
  -muclibc                          [disabled]
  -muintr                           [disabled]
  -mvaes                            [disabled]
  -mveclibabi=                      [default]
  -mvect8-ret-in-mem                [disabled]
  -mvpclmulqdq                      [disabled]
  -mvzeroupper                      [enabled]
  -mwaitpkg                         [disabled]
  -mwbnoinvd                        [disabled]
  -mwidekl                          [disabled]
  -mx32                             [disabled]
  -mxop                             [disabled]
  -mxsave                           [enabled]
  -mxsavec                          [enabled]
  -mxsaveopt                        [enabled]
  -mxsaves                          [enabled]

  Known assembler dialects (for use with the -masm= option):
    att intel

  Known ABIs (for use with the -mabi= option):
    ms sysv

  Known code models (for use with the -mcmodel= option):
    32 kernel large medium small

  Valid arguments to -mfpmath=:
    387 387+sse 387,sse both sse sse+387 sse,387

  Known indirect branch choices (for use with the -mindirect-branch=/-mfunction-return= options):
    keep thunk thunk-extern thunk-inline

  Known choices for return instrumentation with -minstrument-return=:
    call none nop5

  Known data alignment choices (for use with the -malign-data= option):
    abi cacheline compat

  Known vectorization library ABIs (for use with the -mveclibabi= option):
    acml svml

  Known address mode (for use with the -maddress-mode= option):
    long short

  Known preferred register vector length (to use with the -mprefer-vector-width= option):
    128 256 512 none

  Known stack protector guard (for use with the -mstack-protector-guard= option):
    global tls

  Valid arguments to -mstringop-strategy=:
    byte_loop libcall loop rep_4byte rep_8byte rep_byte unrolled_loop vector_loop

  Known TLS dialects (for use with the -mtls-dialect= option):
    gnu gnu2

  Known valid arguments for -march= option:
    i386 i486 i586 pentium lakemont pentium-mmx winchip-c6 winchip2 c3 samuel-2 c3-2 nehemiah c7 esther i686 pentiumpro pentium2 pentium3 pentium3m pentium-m pentium4 pentium4m prescott nocona core2 nehalem corei7 westmere sandybridge corei7-avx ivybridge core-avx-i haswell core-avx2 broadwell skylake skylake-avx512 cannonlake icelake-client rocketlake icelake-server cascadelake tigerlake cooperlake sapphirerapids alderlake bonnell atom silvermont slm goldmont goldmont-plus tremont knl knm intel geode k6 k6-2 k6-3 athlon athlon-tbird athlon-4 athlon-xp athlon-mp x86-64 x86-64-v2 x86-64-v3 x86-64-v4 eden-x2 nano nano-1000 nano-2000 nano-3000 nano-x2 eden-x4 nano-x4 k8 k8-sse3 opteron opteron-sse3 athlon64 athlon64-sse3 athlon-fx amdfam10 barcelona bdver1 bdver2 bdver3 bdver4 znver1 znver2 znver3 btver1 btver2 generic native

  Known valid arguments for -mtune= option:
    generic i386 i486 pentium lakemont pentiumpro pentium4 nocona core2 nehalem sandybridge haswell bonnell silvermont goldmont goldmont-plus tremont knl knm skylake skylake-avx512 cannonlake icelake-client icelake-server cascadelake tigerlake cooperlake sapphirerapids alderlake rocketlake intel geode k6 athlon k8 amdfam10 bdver1 bdver2 bdver3 bdver4 btver1 btver2 znver1 znver2 znver3

I also tried clang and in both cases the loops are vectorised by, I believe, 32 byte vectors:
remark: vectorized loop (vectorization width: 4, interleaved count: 4)

I'm using gcc 11.2.0

Edit:
As requested by Peter Cordes
I realised I was actually benchmarking with a multiplication by 4 for some time.

Makefile:

all:
    gcc -O3 -mavx2 main.c -o 3
    gcc -O3 -march=znver2 main.c -o 32  
    gcc -O3 -march=znver2 main.c -mprefer-vector-width=128 -o 32128
    gcc -O3 -march=znver1 main.c -o 31
    gcc -O2 -mavx2 main.c -o 2
    gcc -O2 -march=znver2 main.c -o 22
    gcc -O2 -march=znver2 main.c -mprefer-vector-width=128 -o 22128
    gcc -O2 -march=znver1 main.c -o 21
    hyperfine -r5 ./3 ./32 ./32128 ./31 ./2 ./22 ./22128 ./21

clean:
    rm ./3 ./32 ./32128 ./31 ./2 ./22 ./22128 ./21

Code:

#include <stdio.h>
#include <inttypes.h>
#include <stdlib.h>
#include <time.h>

int main() {
    const size_t N = 500;
    uint64_t arr[N];
    for (size_t i = 0; i < N; ++i)
        arr[i] = 1;

    for (int j = 0; j < 20000000; ++j)
        for (size_t i = 0; i < N; ++i)
            arr[i] *= 4;

    srand(time(0));
    printf("%lu\n", arr[rand() % N]); // use the array so that it is not optimized away
}

N = 500, arr[i] *= 4:

Benchmark 1: ./3
  Time (mean ± σ):      1.780 s ±  0.011 s    [User: 1.778 s, System: 0.000 s]
  Range (min … max):    1.763 s …  1.791 s    5 runs

Benchmark 2: ./32
  Time (mean ± σ):      1.785 s ±  0.016 s    [User: 1.783 s, System: 0.000 s]
  Range (min … max):    1.773 s …  1.810 s    5 runs

Benchmark 3: ./32128
  Time (mean ± σ):      1.740 s ±  0.026 s    [User: 1.737 s, System: 0.000 s]
  Range (min … max):    1.724 s …  1.785 s    5 runs

Benchmark 4: ./31
  Time (mean ± σ):      1.757 s ±  0.022 s    [User: 1.754 s, System: 0.000 s]
  Range (min … max):    1.727 s …  1.785 s    5 runs

Benchmark 5: ./2
  Time (mean ± σ):      3.467 s ±  0.031 s    [User: 3.462 s, System: 0.000 s]
  Range (min … max):    3.443 s …  3.519 s    5 runs

Benchmark 6: ./22
  Time (mean ± σ):      3.475 s ±  0.028 s    [User: 3.469 s, System: 0.001 s]
  Range (min … max):    3.447 s …  3.512 s    5 runs

Benchmark 7: ./22128
  Time (mean ± σ):      3.464 s ±  0.034 s    [User: 3.459 s, System: 0.001 s]
  Range (min … max):    3.431 s …  3.509 s    5 runs

Benchmark 8: ./21
  Time (mean ± σ):      3.465 s ±  0.013 s    [User: 3.460 s, System: 0.001 s]
  Range (min … max):    3.443 s …  3.475 s    5 runs

N = 500, arr[i] *= 5:

Benchmark 1: ./3
  Time (mean ± σ):      1.789 s ±  0.004 s    [User: 1.786 s, System: 0.001 s]
  Range (min … max):    1.783 s …  1.793 s    5 runs

Benchmark 2: ./32
  Time (mean ± σ):      1.772 s ±  0.017 s    [User: 1.769 s, System: 0.000 s]
  Range (min … max):    1.755 s …  1.800 s    5 runs

Benchmark 3: ./32128
  Time (mean ± σ):      2.911 s ±  0.023 s    [User: 2.907 s, System: 0.001 s]
  Range (min … max):    2.880 s …  2.943 s    5 runs

Benchmark 4: ./31
  Time (mean ± σ):      2.924 s ±  0.013 s    [User: 2.921 s, System: 0.000 s]
  Range (min … max):    2.906 s …  2.934 s    5 runs

Benchmark 5: ./2
  Time (mean ± σ):      3.850 s ±  0.029 s    [User: 3.846 s, System: 0.000 s]
  Range (min … max):    3.823 s …  3.896 s    5 runs

Benchmark 6: ./22
  Time (mean ± σ):      3.816 s ±  0.036 s    [User: 3.812 s, System: 0.000 s]
  Range (min … max):    3.777 s …  3.855 s    5 runs

Benchmark 7: ./22128
  Time (mean ± σ):      3.813 s ±  0.026 s    [User: 3.809 s, System: 0.000 s]
  Range (min … max):    3.780 s …  3.834 s    5 runs

Benchmark 8: ./21
  Time (mean ± σ):      3.783 s ±  0.010 s    [User: 3.779 s, System: 0.000 s]
  Range (min … max):    3.773 s …  3.798 s    5 runs

N = 512, arr[i] *= 4

Benchmark 1: ./3
  Time (mean ± σ):      1.849 s ±  0.015 s    [User: 1.847 s, System: 0.000 s]
  Range (min … max):    1.831 s …  1.873 s    5 runs

Benchmark 2: ./32
  Time (mean ± σ):      1.846 s ±  0.013 s    [User: 1.844 s, System: 0.001 s]
  Range (min … max):    1.832 s …  1.860 s    5 runs

Benchmark 3: ./32128
  Time (mean ± σ):      1.756 s ±  0.012 s    [User: 1.754 s, System: 0.000 s]
  Range (min … max):    1.744 s …  1.771 s    5 runs

Benchmark 4: ./31
  Time (mean ± σ):      1.788 s ±  0.012 s    [User: 1.785 s, System: 0.001 s]
  Range (min … max):    1.774 s …  1.801 s    5 runs

Benchmark 5: ./2
  Time (mean ± σ):      3.476 s ±  0.015 s    [User: 3.472 s, System: 0.001 s]
  Range (min … max):    3.458 s …  3.494 s    5 runs

Benchmark 6: ./22
  Time (mean ± σ):      3.449 s ±  0.002 s    [User: 3.446 s, System: 0.000 s]
  Range (min … max):    3.446 s …  3.452 s    5 runs

Benchmark 7: ./22128
  Time (mean ± σ):      3.456 s ±  0.007 s    [User: 3.453 s, System: 0.000 s]
  Range (min … max):    3.446 s …  3.462 s    5 runs

Benchmark 8: ./21
  Time (mean ± σ):      3.547 s ±  0.044 s    [User: 3.542 s, System: 0.001 s]
  Range (min … max):    3.482 s …  3.600 s    5 runs

N = 512, arr[i] *= 5

Benchmark 1: ./3
  Time (mean ± σ):      1.847 s ±  0.013 s    [User: 1.845 s, System: 0.000 s]
  Range (min … max):    1.836 s …  1.863 s    5 runs

Benchmark 2: ./32
  Time (mean ± σ):      1.830 s ±  0.007 s    [User: 1.827 s, System: 0.001 s]
  Range (min … max):    1.820 s …  1.837 s    5 runs

Benchmark 3: ./32128
  Time (mean ± σ):      2.983 s ±  0.017 s    [User: 2.980 s, System: 0.000 s]
  Range (min … max):    2.966 s …  3.012 s    5 runs

Benchmark 4: ./31
  Time (mean ± σ):      3.026 s ±  0.039 s    [User: 3.021 s, System: 0.001 s]
  Range (min … max):    2.989 s …  3.089 s    5 runs

Benchmark 5: ./2
  Time (mean ± σ):      4.000 s ±  0.021 s    [User: 3.994 s, System: 0.001 s]
  Range (min … max):    3.982 s …  4.035 s    5 runs

Benchmark 6: ./22
  Time (mean ± σ):      3.940 s ±  0.041 s    [User: 3.934 s, System: 0.001 s]
  Range (min … max):    3.890 s …  3.981 s    5 runs

Benchmark 7: ./22128
  Time (mean ± σ):      3.928 s ±  0.032 s    [User: 3.922 s, System: 0.001 s]
  Range (min … max):    3.898 s …  3.979 s    5 runs

Benchmark 8: ./21
  Time (mean ± σ):      3.908 s ±  0.029 s    [User: 3.904 s, System: 0.000 s]
  Range (min … max):    3.879 s …  3.954 s    5 runs

I think the run where -O2 -march=znver1 was the same speed as -O3 -march=znver1 was a mistake on my part with the naming of the files, I had not created the makefile back then yet, I was using my shell's history.

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兲鉂ぱ嘚淚 2025-01-27 15:26:18

默认的 -mtune=generic 具有 -mprefer-vector-width=256,并且 -mavx2 不会改变这一点。

znver1 意味着 -mprefer-vector-width=128,因为这是硬件的所有本机宽度。使用 32 字节 YMM 向量的指令解码为至少 2 个微指令,如果是跨车道洗牌,则更多。对于像这样的简单垂直 SIMD,32 字节向量就可以了;管道有效地处理 2-uop 指令。 (我认为是 6 uop 宽,但只有 5 条指令宽,因此仅使用 1 uop 指令无法获得最大前端吞吐量)。但是,当矢量化需要改组时,例如使用不同元素宽度的数组,GCC 代码生成在 256 位或更宽的情况下可能会变得更加混乱。

vmovdqa ymm0, ymm1 mov-elimination 仅适用于 Zen1 上的低 128 位一半。此外,通常使用 256 位向量意味着之后应该使用 vzeroupper,以避免在其他 CPU(但不是 Zen1)上出现性能问题。

我不知道 Zen1 如何处理未对齐的 32 字节加载/存储,其中每个 16 字节一半都是对齐的,但位于单独的缓存行中。如果效果良好,GCC 可能会考虑将 znver1 -mprefer-vector-width 增加到 256。但是,如果不知道大小是向量的倍数,则更宽的向量意味着更多的清理代码宽度。

理想情况下,GCC 能够检测到这样的简单情况,并在那里使用 256 位向量。 (纯垂直,没有元素宽度的混合,恒定大小是 32 字节的倍数。)至少在 CPU 上这很好:znver1,但不是 bdver2,例如,由于 CPU 设计错误,256 位存储总是很慢。

您可以通过使用 vmovdqu [rdx], xmm0 对第一个循环(类似于 memset 的循环)进行矢量化的方式来查看此选择的结果。 https://godbolt.org/z/E5Tq7Gfzc


因此,鉴于 GCC 决定仅使用 128-位向量,只能容纳两个 uint64_t 元素,它(正确或错误)决定它不值得使用vpsllq / vpaddd 将 qword *5 实现为 (v<<2) + v,与执行它与一条 LEA 指令中的整数一起。

在这种情况下几乎肯定是错误的,因为它仍然需要为每个元素或元素对进行单独的加载和存储。 (循环开销,因为 GCC 默认不会展开,除非使用 PGO,-fprofile-use。SIMD 就像循环展开,特别是在将 256 位向量作为 2 个单独的微指令处理的 CPU 上。

)我不确定 GCC 所说的“未矢量化:不支持的数据类型”到底是什么意思。 x86 在 AVX-512 之前没有 SIMD uint64_t 乘法指令,因此 GCC 可能会根据 一般情况必须用多个 32x32 来模拟它=> 64 位 pmuludq 指令和一堆随机播放。只有在克服了这个困难之后,它才意识到对于像 5 这样只有 2 个设置位的常量来说实际上相当便宜?

这可以解释 GCC 的决策过程,但我不确定这是否完全正确。尽管如此,这些类型的因素仍然发生在像编译器这样的复杂机器中。熟练的人可以轻松做出更明智的选择,但编译器只是执行一系列优化过程,并不总是同时考虑大局和所有细节。


-mprefer-vector-width=256 没有帮助:

不矢量化 uint64_t *= 5 似乎是 GCC9 回归

(问题中的基准确认实际的 Zen1 CPU 获得近 2 倍的加速,正如预期的那样,在 6 uops 中执行 2x uint64,而在 5 uops 中执行 1x 标量或 4x uint64_t。具有 256 位向量的 10 个微指令,包括两个 128 位存储,这将与前端一起成为吞吐量瓶颈。)

即使使用 -march=znver1 -O3 -mprefer-vector-width=256,我们没有得到使用 GCC9、10 或 11 或当前主干向量化的 *= 5 循环。正如您所说,我们使用 -march=znver2 进行操作。 https://godbolt.org/z/dMTh7Wxcq

我们确实使用这些选项进行矢量化uint32_t(甚至将向量宽度保留为 128 位)。无论 Zen1 上的向量化是 128 位还是 256 位,标量每个向量 uop(不是指令)都会花费 4 次操作,因此这并不能告诉我们 *= 是否是使成本模型决定不这样做的原因向量化,或者只是每个 128 位内部 uop 2 与 4 个元素。


使用 uint64_t,更改为 arr[i] += arr[i]<<2; 仍然不会矢量化,但 arr[i] < ;<= 1; 确实如此。 (https://godbolt.org/z/6PMn93Y5G)。甚至同一循环中的 arr[i] <<= 2;arr[i] += 123 也会向量化为 GCC 认为不是的相同指令向量化 *= 5 是值得的,只是不同的操作数,常数而不是原始向量。 (标量仍然可以使用一个 LEA)。很明显,成本模型并没有考虑到最终的 x86 asm 机器指令,但我不知道为什么 arr[i] += arr[i] 会被认为比 arr[i] += arr[i] 更昂贵code>arr[i] <<= 1; 这是完全相同的事情。

即使矢量宽度为 128 位,GCC8 也会对循环进行矢量化: https://godbolt .org/z/5o6qjc7f6

# GCC8.5 -march=znver1 -O3  (-mprefer-vector-width=128)
.L12:                                            # do{
        vmovups xmm1, XMMWORD PTR [rsi]            # 16-byte load
        add     rsi, 16                             # ptr += 2 elements
        vpsllq  xmm0, xmm1, 2                      # v << 2
        vpaddq  xmm0, xmm0, xmm1                   # tmp += v
        vmovups XMMWORD PTR [rsi-16], xmm0         # store
        cmp     rax, rsi
        jne     .L12                             # } while(p != endp)

使用 -march=znver1 -mprefer-vector-width=256,将商店存储为两个 16 字节的半部 vmovups xmm / vextracti128为什么 gcc 不将 _mm256_loadu_pd 解析为 single vmovupd? znver1 暗示 -mavx256-split-unaligned-store (当 GCC 不确定知道它是否对齐时,它会影响每个存储。所以它即使数据确实对齐,也会花费额外的指令)。

不过,znver1 并不意味着 -mavx256-split-unaligned-load ,因此 GCC 愿意将负载作为内存源操作数折叠到代码中有用的 ALU 操作中。

The default -mtune=generic has -mprefer-vector-width=256, and -mavx2 doesn't change that.

znver1 implies -mprefer-vector-width=128, because that's all the native width of the HW. An instruction using 32-byte YMM vectors decodes to at least 2 uops, more if it's a lane-crossing shuffle. For simple vertical SIMD like this, 32-byte vectors would be ok; the pipeline handles 2-uop instructions efficiently. (And I think is 6 uops wide but only 5 instructions wide, so max front-end throughput isn't available using only 1-uop instructions). But when vectorization would require shuffling, e.g. with arrays of different element widths, GCC code-gen can get messier with 256-bit or wider.

And vmovdqa ymm0, ymm1 mov-elimination only works on the low 128-bit half on Zen1. Also, normally using 256-bit vectors would imply one should use vzeroupper afterwards, to avoid performance problems on other CPUs (but not Zen1).

I don't know how Zen1 handles misaligned 32-byte loads/stores where each 16-byte half is aligned but in separate cache lines. If that performs well, GCC might want to consider increasing the znver1 -mprefer-vector-width to 256. But wider vectors means more cleanup code if the size isn't known to be a multiple of the vector width.

Ideally GCC would be able to detect easy cases like this and use 256-bit vectors there. (Pure vertical, no mixing of element widths, constant size that's am multiple of 32 bytes.) At least on CPUs where that's fine: znver1, but not bdver2 for example where 256-bit stores are always slow due to a CPU design bug.

You can see the result of this choice in the way it vectorizes your first loop, the memset-like loop, with a vmovdqu [rdx], xmm0. https://godbolt.org/z/E5Tq7Gfzc


So given that GCC has decided to only use 128-bit vectors, which can only hold two uint64_t elements, it (rightly or wrongly) decides it wouldn't be worth using vpsllq / vpaddd to implement qword *5 as (v<<2) + v, vs. doing it with integer in one LEA instruction.

Almost certainly wrongly in this case, since it still requires a separate load and store for every element or pair of elements. (And loop overhead since GCC's default is not to unroll except with PGO, -fprofile-use. SIMD is like loop unrolling, especially on a CPU that handles 256-bit vectors as 2 separate uops.)

I'm not sure exactly what GCC means by "not vectorized: unsupported data-type". x86 doesn't have a SIMD uint64_t multiply instruction until AVX-512, so perhaps GCC assigns it a cost based on the general case of having to emulate it with multiple 32x32 => 64-bit pmuludq instructions and a bunch of shuffles. And it's only after it gets over that hump that it realizes that it's actually quite cheap for a constant like 5 with only 2 set bits?

That would explain GCC's decision-making process here, but I'm not sure it's exactly the right explanation. Still, these kinds of factors are what happen in a complex piece of machinery like a compiler. A skilled human can easily make smarter choices, but compilers just do sequences of optimization passes that don't always consider the big picture and all the details at the same time.


-mprefer-vector-width=256 doesn't help:

Not vectorizing uint64_t *= 5 seems to be a GCC9 regression

(The benchmarks in the question confirm that an actual Zen1 CPU gets a nearly 2x speedup, as expected from doing 2x uint64 in 6 uops vs. 1x in 5 uops with scalar. Or 4x uint64_t in 10 uops with 256-bit vectors, including two 128-bit stores which will be the throughput bottleneck along with the front-end.)

Even with -march=znver1 -O3 -mprefer-vector-width=256, we don't get the *= 5 loop vectorized with GCC9, 10, or 11, or current trunk. As you say, we do with -march=znver2. https://godbolt.org/z/dMTh7Wxcq

We do get vectorization with those options for uint32_t (even leaving the vector width at 128-bit). Scalar would cost 4 operations per vector uop (not instruction), regardless of 128 or 256-bit vectorization on Zen1, so this doesn't tell us whether *= is what makes the cost-model decide not to vectorize, or just the 2 vs. 4 elements per 128-bit internal uop.


With uint64_t, changing to arr[i] += arr[i]<<2; still doesn't vectorize, but arr[i] <<= 1; does. (https://godbolt.org/z/6PMn93Y5G). Even arr[i] <<= 2; and arr[i] += 123 in the same loop vectorize, to the same instructions that GCC thinks aren't worth it for vectorizing *= 5, just different operands, constant instead of the original vector again. (Scalar could still use one LEA). So clearly the cost-model isn't looking as far as final x86 asm machine instructions, but I don't know why arr[i] += arr[i] would be considered more expensive than arr[i] <<= 1; which is exactly the same thing.

GCC8 does vectorize your loop, even with 128-bit vector width: https://godbolt.org/z/5o6qjc7f6

# GCC8.5 -march=znver1 -O3  (-mprefer-vector-width=128)
.L12:                                            # do{
        vmovups xmm1, XMMWORD PTR [rsi]            # 16-byte load
        add     rsi, 16                             # ptr += 2 elements
        vpsllq  xmm0, xmm1, 2                      # v << 2
        vpaddq  xmm0, xmm0, xmm1                   # tmp += v
        vmovups XMMWORD PTR [rsi-16], xmm0         # store
        cmp     rax, rsi
        jne     .L12                             # } while(p != endp)

With -march=znver1 -mprefer-vector-width=256, doing the store as two 16-byte halves with vmovups xmm / vextracti128 is Why doesn't gcc resolve _mm256_loadu_pd as single vmovupd? znver1 implies -mavx256-split-unaligned-store (which affects every store when GCC doesn't know for sure that it is aligned. So it costs extra instructions even when data does happen to be aligned).

znver1 doesn't imply -mavx256-split-unaligned-load, though, so GCC is willing to fold loads as memory source operands into ALU operations in code where that's useful.

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