sglang_v0.5.2/pytorch_2.8.0/third_party/XNNPACK/bench/f16-gemm.cc

365 lines
15 KiB
C++

// Copyright (c) Facebook, Inc. and its affiliates.
// All rights reserved.
//
// Copyright 2019 Google LLC
//
// This source code is licensed under the BSD-style license found in the
// LICENSE file in the root directory of this source tree.
#include <algorithm>
#include <cfloat>
#include <cmath>
#include <functional>
#include <random>
#include <vector>
#include "gemm.h"
#include "utils.h"
#include "xnnpack.h"
#include "xnnpack/common.h"
#include "xnnpack/gemm.h"
#include "xnnpack/math.h"
#include "xnnpack/microfnptr.h"
#include "xnnpack/microparams-init.h"
#include "xnnpack/pack.h"
#include "xnnpack/buffer.h"
#include <benchmark/benchmark.h>
static void f16_gemm(benchmark::State& state,
xnn_f16_gemm_minmax_ukernel_fn gemm,
xnn_init_f16_minmax_params_fn init_params,
size_t mr, size_t nr, size_t kr, size_t sr,
benchmark::utils::IsaCheckFunction isa_check = nullptr)
{
if (isa_check != nullptr && !isa_check(state)) {
return;
}
const size_t mc = state.range(0);
const size_t nc = state.range(1);
const size_t kc = state.range(2);
const size_t nc_stride = benchmark::utils::RoundUp(nc, nr);
const size_t kc_stride = benchmark::utils::RoundUp(kc, kr * sr);
std::random_device random_device;
auto rng = std::mt19937(random_device());
auto f32rng = std::bind(std::uniform_real_distribution<float>(), std::ref(rng));
xnnpack::Buffer<xnn_float16> a(mc * kc + XNN_EXTRA_BYTES / sizeof(xnn_float16));
std::generate(a.begin(), a.end(), f32rng);
xnnpack::Buffer<xnn_float16> k(nc * kc);
std::generate(k.begin(), k.end(), f32rng);
xnnpack::Buffer<xnn_float16> b(nc);
std::generate(b.begin(), b.end(), f32rng);
const size_t w_elements = nc_stride * kc_stride + nc_stride;
const size_t c_elements = mc * nc;
const size_t num_buffers = 1 +
benchmark::utils::DivideRoundUp<size_t>(benchmark::utils::GetMaxCacheSize(),
sizeof(xnn_float16) * (w_elements + c_elements));
xnnpack::Buffer<xnn_float16, XNN_ALLOCATION_ALIGNMENT> w(w_elements * num_buffers);
xnn_pack_f16_gemm_goi_w(/*groups=*/1, nc, kc, nr, kr, sr,
reinterpret_cast<const uint16_t*>(k.data()),
reinterpret_cast<const uint16_t*>(b.data()),
/*scale=*/nullptr,
reinterpret_cast<uint16_t*>(w.data()),
/*extra_bytes=*/0, /*params=*/nullptr);
xnnpack::Buffer<xnn_float16> c(c_elements * num_buffers);
// Prepare minmax parameters.
xnn_f16_minmax_params params;
init_params(&params, static_cast<xnn_float16>(-INFINITY), static_cast<xnn_float16>(INFINITY));
size_t buffer_index = 0;
for (auto _ : state) {
// Use circular buffers (exceeding cache size) and prefetch to control cache state:
// - A is always in L1 cache (if fits, otherwise L2, L3, etc)
// - W is not in cache (for any cache level)
// - C is not in cache (for any cache level)
state.PauseTiming();
benchmark::utils::PrefetchToL1(a.data(), a.size() * sizeof(xnn_float16));
buffer_index = (buffer_index + 1) % num_buffers;
state.ResumeTiming();
for (uint32_t m = 0; m < mc; m += mr) {
const uint32_t mb = min(mc - m, mr);
for (uint32_t n = 0; n < nc; n += nr) {
const uint32_t nb = min(nc - n, nr);
gemm(
mb, nb, kc * sizeof(xnn_float16),
a.data() + m * kc, kc * sizeof(xnn_float16),
w.data() + (nc_stride * buffer_index + n) * (kc_stride + 1),
c.data() + (mc * buffer_index + m) * nc + n, nc * sizeof(xnn_float16), nr * sizeof(xnn_float16),
&params);
}
}
}
const uint64_t cpu_frequency = benchmark::utils::GetCurrentCpuFrequency();
if (cpu_frequency != 0) {
state.counters["cpufreq"] = cpu_frequency;
}
state.counters["FLOPS"] = benchmark::Counter(
uint64_t(state.iterations()) * 2 * mc * nc * kc, benchmark::Counter::kIsRate);
}
#if XNN_ARCH_ARM64 && XNN_ENABLE_ASSEMBLY
static void f16_gemm_1x16__asm_aarch64_neonfp16arith_ld32(benchmark::State& state, const char* net) {
f16_gemm(state,
xnn_f16_gemm_minmax_ukernel_1x16__asm_aarch64_neonfp16arith_ld32,
xnn_init_f16_minmax_scalar_params,
/*mr=*/1, /*nr=*/16, /*kr=*/1, /*sr=*/1,
benchmark::utils::CheckNEONFP16ARITH);
}
static void f16_gemm_1x16__asm_aarch64_neonfp16arith_ld64(benchmark::State& state, const char* net) {
f16_gemm(state,
xnn_f16_gemm_minmax_ukernel_1x16__asm_aarch64_neonfp16arith_ld64,
xnn_init_f16_minmax_scalar_params,
/*mr=*/1, /*nr=*/16, /*kr=*/1, /*sr=*/1,
benchmark::utils::CheckNEONFP16ARITH);
}
static void f16_gemm_4x16__asm_aarch64_neonfp16arith_ld32(benchmark::State& state, const char* net) {
f16_gemm(state,
xnn_f16_gemm_minmax_ukernel_4x16__asm_aarch64_neonfp16arith_ld32,
xnn_init_f16_minmax_scalar_params,
/*mr=*/4, /*nr=*/16, /*kr=*/1, /*sr=*/1,
benchmark::utils::CheckNEONFP16ARITH);
}
static void f16_gemm_4x16__asm_aarch64_neonfp16arith_ld64(benchmark::State& state, const char* net) {
f16_gemm(state,
xnn_f16_gemm_minmax_ukernel_4x16__asm_aarch64_neonfp16arith_ld64,
xnn_init_f16_minmax_scalar_params,
/*mr=*/4, /*nr=*/16, /*kr=*/1, /*sr=*/1,
benchmark::utils::CheckNEONFP16ARITH);
}
static void f16_gemm_6x16__asm_aarch64_neonfp16arith_cortex_a55(benchmark::State& state, const char* net) {
f16_gemm(state,
xnn_f16_gemm_minmax_ukernel_6x16__asm_aarch64_neonfp16arith_cortex_a55,
xnn_init_f16_minmax_scalar_params,
/*mr=*/6, /*nr=*/16, /*kr=*/1, /*sr=*/1,
benchmark::utils::CheckNEONFP16ARITH);
}
static void f16_gemm_6x16__asm_aarch64_neonfp16arith_cortex_a55r0(benchmark::State& state, const char* net) {
f16_gemm(state,
xnn_f16_gemm_minmax_ukernel_6x16__asm_aarch64_neonfp16arith_cortex_a55r0,
xnn_init_f16_minmax_scalar_params,
/*mr=*/6, /*nr=*/16, /*kr=*/1, /*sr=*/1,
benchmark::utils::CheckNEONFP16ARITH);
}
static void f16_gemm_6x16__asm_aarch64_neonfp16arith_cortex_a75(benchmark::State& state, const char* net) {
f16_gemm(state,
xnn_f16_gemm_minmax_ukernel_6x16__asm_aarch64_neonfp16arith_cortex_a75,
xnn_init_f16_minmax_scalar_params,
/*mr=*/6, /*nr=*/16, /*kr=*/1, /*sr=*/1,
benchmark::utils::CheckNEONFP16ARITH);
}
static void f16_gemm_6x16__asm_aarch64_neonfp16arith_ld32(benchmark::State& state, const char* net) {
f16_gemm(state,
xnn_f16_gemm_minmax_ukernel_6x16__asm_aarch64_neonfp16arith_ld32,
xnn_init_f16_minmax_scalar_params,
/*mr=*/6, /*nr=*/16, /*kr=*/1, /*sr=*/1,
benchmark::utils::CheckNEONFP16ARITH);
}
static void f16_gemm_6x16__asm_aarch64_neonfp16arith_ld64(benchmark::State& state, const char* net) {
f16_gemm(state,
xnn_f16_gemm_minmax_ukernel_6x16__asm_aarch64_neonfp16arith_ld64,
xnn_init_f16_minmax_scalar_params,
/*mr=*/6, /*nr=*/16, /*kr=*/1, /*sr=*/1,
benchmark::utils::CheckNEONFP16ARITH);
}
static void f16_gemm_1x8__asm_aarch64_neonfp16arith_ld64(benchmark::State& state, const char* net) {
f16_gemm(state,
xnn_f16_gemm_minmax_ukernel_1x8__asm_aarch64_neonfp16arith_ld64,
xnn_init_f16_minmax_scalar_params,
/*mr=*/1, /*nr=*/8, /*kr=*/1, /*sr=*/1,
benchmark::utils::CheckNEONFP16ARITH);
}
static void f16_gemm_4x8__asm_aarch64_neonfp16arith_ld64(benchmark::State& state, const char* net) {
f16_gemm(state,
xnn_f16_gemm_minmax_ukernel_4x8__asm_aarch64_neonfp16arith_ld64,
xnn_init_f16_minmax_scalar_params,
/*mr=*/4, /*nr=*/8, /*kr=*/1, /*sr=*/1,
benchmark::utils::CheckNEONFP16ARITH);
}
static void f16_gemm_6x8__asm_aarch64_neonfp16arith_ld64(benchmark::State& state, const char* net) {
f16_gemm(state,
xnn_f16_gemm_minmax_ukernel_6x8__asm_aarch64_neonfp16arith_ld64,
xnn_init_f16_minmax_scalar_params,
/*mr=*/6, /*nr=*/8, /*kr=*/1, /*sr=*/1,
benchmark::utils::CheckNEONFP16ARITH);
}
static void f16_gemm_8x8__asm_aarch64_neonfp16arith_ld64(benchmark::State& state, const char* net) {
f16_gemm(state,
xnn_f16_gemm_minmax_ukernel_8x8__asm_aarch64_neonfp16arith_ld64,
xnn_init_f16_minmax_scalar_params,
/*mr=*/8, /*nr=*/8, /*kr=*/1, /*sr=*/1,
benchmark::utils::CheckNEONFP16ARITH);
}
BENCHMARK_GEMM(f16_gemm_1x16__asm_aarch64_neonfp16arith_ld32)
BENCHMARK_GEMM(f16_gemm_1x16__asm_aarch64_neonfp16arith_ld64)
BENCHMARK_GEMM(f16_gemm_4x16__asm_aarch64_neonfp16arith_ld32)
BENCHMARK_GEMM(f16_gemm_4x16__asm_aarch64_neonfp16arith_ld64)
BENCHMARK_GEMM(f16_gemm_6x16__asm_aarch64_neonfp16arith_cortex_a55)
BENCHMARK_GEMM(f16_gemm_6x16__asm_aarch64_neonfp16arith_cortex_a55r0)
BENCHMARK_GEMM(f16_gemm_6x16__asm_aarch64_neonfp16arith_cortex_a75)
BENCHMARK_GEMM(f16_gemm_6x16__asm_aarch64_neonfp16arith_ld32)
BENCHMARK_GEMM(f16_gemm_6x16__asm_aarch64_neonfp16arith_ld64)
BENCHMARK_GEMM(f16_gemm_1x8__asm_aarch64_neonfp16arith_ld64)
BENCHMARK_GEMM(f16_gemm_4x8__asm_aarch64_neonfp16arith_ld64)
BENCHMARK_GEMM(f16_gemm_6x8__asm_aarch64_neonfp16arith_ld64)
BENCHMARK_GEMM(f16_gemm_8x8__asm_aarch64_neonfp16arith_ld64)
#endif // XNN_ARCH_ARM64 && XNN_ENABLE_ASSEMBLY
#if XNN_ENABLE_ARM_FP16_VECTOR && (XNN_ARCH_ARM || XNN_ARCH_ARM64)
static void f16_gemm_1x8__neonfp16arith_ld64(benchmark::State& state, const char* net) {
f16_gemm(state,
xnn_f16_gemm_minmax_ukernel_1x8__neonfp16arith_ld64,
xnn_init_f16_minmax_scalar_params,
/*mr=*/1, /*nr=*/8, /*kr=*/1, /*sr=*/1,
benchmark::utils::CheckNEONFP16ARITH);
}
static void f16_gemm_4x8__neonfp16arith_ld64(benchmark::State& state, const char* net) {
f16_gemm(state,
xnn_f16_gemm_minmax_ukernel_4x8__neonfp16arith_ld64,
xnn_init_f16_minmax_scalar_params,
/*mr=*/4, /*nr=*/8, /*kr=*/1, /*sr=*/1,
benchmark::utils::CheckNEONFP16ARITH);
}
static void f16_gemm_6x8__neonfp16arith_ld64(benchmark::State& state, const char* net) {
f16_gemm(state,
xnn_f16_gemm_minmax_ukernel_6x8__neonfp16arith_ld64,
xnn_init_f16_minmax_scalar_params,
/*mr=*/6, /*nr=*/8, /*kr=*/1, /*sr=*/1,
benchmark::utils::CheckNEONFP16ARITH);
}
static void f16_gemm_8x8__neonfp16arith_ld64(benchmark::State& state, const char* net) {
f16_gemm(state,
xnn_f16_gemm_minmax_ukernel_8x8__neonfp16arith_ld64,
xnn_init_f16_minmax_scalar_params,
/*mr=*/8, /*nr=*/8, /*kr=*/1, /*sr=*/1,
benchmark::utils::CheckNEONFP16ARITH);
}
static void f16_gemm_1x16__neonfp16arith_ld64(benchmark::State& state, const char* net) {
f16_gemm(state,
xnn_f16_gemm_minmax_ukernel_1x16__neonfp16arith_ld64,
xnn_init_f16_minmax_scalar_params,
/*mr=*/1, /*nr=*/16, /*kr=*/1, /*sr=*/1,
benchmark::utils::CheckNEONFP16ARITH);
}
static void f16_gemm_4x16__neonfp16arith_ld64(benchmark::State& state, const char* net) {
f16_gemm(state,
xnn_f16_gemm_minmax_ukernel_4x16__neonfp16arith_ld64,
xnn_init_f16_minmax_scalar_params,
/*mr=*/4, /*nr=*/16, /*kr=*/1, /*sr=*/1,
benchmark::utils::CheckNEONFP16ARITH);
}
static void f16_gemm_6x16__neonfp16arith_ld64(benchmark::State& state, const char* net) {
f16_gemm(state,
xnn_f16_gemm_minmax_ukernel_6x16__neonfp16arith_ld64,
xnn_init_f16_minmax_scalar_params,
/*mr=*/6, /*nr=*/16, /*kr=*/1, /*sr=*/1,
benchmark::utils::CheckNEONFP16ARITH);
}
static void f16_gemm_8x16__neonfp16arith_ld64(benchmark::State& state, const char* net) {
f16_gemm(state,
xnn_f16_gemm_minmax_ukernel_8x16__neonfp16arith_ld64,
xnn_init_f16_minmax_scalar_params,
/*mr=*/8, /*nr=*/16, /*kr=*/1, /*sr=*/1,
benchmark::utils::CheckNEONFP16ARITH);
}
BENCHMARK_GEMM(f16_gemm_1x8__neonfp16arith_ld64)
BENCHMARK_GEMM(f16_gemm_4x8__neonfp16arith_ld64)
BENCHMARK_GEMM(f16_gemm_6x8__neonfp16arith_ld64)
BENCHMARK_GEMM(f16_gemm_8x8__neonfp16arith_ld64)
BENCHMARK_GEMM(f16_gemm_1x16__neonfp16arith_ld64)
BENCHMARK_GEMM(f16_gemm_4x16__neonfp16arith_ld64)
BENCHMARK_GEMM(f16_gemm_6x16__neonfp16arith_ld64)
BENCHMARK_GEMM(f16_gemm_8x16__neonfp16arith_ld64)
#endif // XNN_ENABLE_ARM_FP16_VECTOR && (XNN_ARCH_ARM || XNN_ARCH_ARM64)
#if XNN_ARCH_X86 || XNN_ARCH_X86_64
static void f16_gemm_1x8__avx2_broadcast(benchmark::State& state, const char* net) {
f16_gemm(state,
xnn_f16_gemm_minmax_ukernel_1x8__avx2_broadcast,
xnn_init_f16_minmax_scalar_params,
/*mr=*/1, /*nr=*/8, /*kr=*/1, /*sr=*/1,
benchmark::utils::CheckAVX2);
}
static void f16_gemm_4x8__avx2_broadcast(benchmark::State& state, const char* net) {
f16_gemm(state,
xnn_f16_gemm_minmax_ukernel_4x8__avx2_broadcast,
xnn_init_f16_minmax_scalar_params,
/*mr=*/4, /*nr=*/8, /*kr=*/1, /*sr=*/1,
benchmark::utils::CheckAVX2);
}
static void f16_gemm_5x8__avx2_broadcast(benchmark::State& state, const char* net) {
f16_gemm(state,
xnn_f16_gemm_minmax_ukernel_5x8__avx2_broadcast,
xnn_init_f16_minmax_scalar_params,
/*mr=*/5, /*nr=*/8, /*kr=*/1, /*sr=*/1,
benchmark::utils::CheckAVX2);
}
static void f16_gemm_6x8__avx2_broadcast(benchmark::State& state, const char* net) {
f16_gemm(state,
xnn_f16_gemm_minmax_ukernel_6x8__avx2_broadcast,
xnn_init_f16_minmax_scalar_params,
/*mr=*/6, /*nr=*/8, /*kr=*/1, /*sr=*/1,
benchmark::utils::CheckAVX2);
}
static void f16_gemm_7x8__avx2_broadcast(benchmark::State& state, const char* net) {
f16_gemm(state,
xnn_f16_gemm_minmax_ukernel_7x8__avx2_broadcast,
xnn_init_f16_minmax_scalar_params,
/*mr=*/7, /*nr=*/8, /*kr=*/1, /*sr=*/1,
benchmark::utils::CheckAVX2);
}
static void f16_gemm_1x16__avx2_broadcast(benchmark::State& state, const char* net) {
f16_gemm(state,
xnn_f16_gemm_minmax_ukernel_1x16__avx2_broadcast,
xnn_init_f16_minmax_scalar_params,
/*mr=*/1, /*nr=*/16, /*kr=*/1, /*sr=*/1,
benchmark::utils::CheckAVX2);
}
static void f16_gemm_3x16__avx2_broadcast(benchmark::State& state, const char* net) {
f16_gemm(state,
xnn_f16_gemm_minmax_ukernel_3x16__avx2_broadcast,
xnn_init_f16_minmax_scalar_params,
/*mr=*/3, /*nr=*/16, /*kr=*/1, /*sr=*/1,
benchmark::utils::CheckAVX2);
}
static void f16_gemm_4x16__avx2_broadcast(benchmark::State& state, const char* net) {
f16_gemm(state,
xnn_f16_gemm_minmax_ukernel_4x16__avx2_broadcast,
xnn_init_f16_minmax_scalar_params,
/*mr=*/4, /*nr=*/16, /*kr=*/1, /*sr=*/1,
benchmark::utils::CheckAVX2);
}
static void f16_gemm_5x16__avx2_broadcast(benchmark::State& state, const char* net) {
f16_gemm(state,
xnn_f16_gemm_minmax_ukernel_5x16__avx2_broadcast,
xnn_init_f16_minmax_scalar_params,
/*mr=*/5, /*nr=*/16, /*kr=*/1, /*sr=*/1,
benchmark::utils::CheckAVX2);
}
BENCHMARK_GEMM(f16_gemm_1x8__avx2_broadcast)
BENCHMARK_GEMM(f16_gemm_4x8__avx2_broadcast)
BENCHMARK_GEMM(f16_gemm_5x8__avx2_broadcast)
BENCHMARK_GEMM(f16_gemm_6x8__avx2_broadcast)
BENCHMARK_GEMM(f16_gemm_7x8__avx2_broadcast)
BENCHMARK_GEMM(f16_gemm_1x16__avx2_broadcast)
BENCHMARK_GEMM(f16_gemm_3x16__avx2_broadcast)
BENCHMARK_GEMM(f16_gemm_4x16__avx2_broadcast)
BENCHMARK_GEMM(f16_gemm_5x16__avx2_broadcast)
#endif // XNN_ARCH_X86 || XNN_ARCH_X86_64
#ifndef XNNPACK_BENCHMARK_NO_MAIN
BENCHMARK_MAIN();
#endif