| // 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 <chrono> |
| #include <cmath> |
| #include <functional> |
| #include <limits> |
| #include <mutex> |
| #include <random> |
| #include <vector> |
| |
| #include <cpuinfo.h> |
| |
| #include <benchmark/benchmark.h> |
| #ifdef BENCHMARK_GEMMLOWP |
| #include "gemmlowp/public/gemmlowp.h" |
| #endif // BENCHMARK_GEMMLOWP |
| #ifdef BENCHMARK_RUY |
| #include "ruy/ruy.h" |
| #endif // BENCHMARK_RUY |
| #include "bench/gemm.h" |
| #include "bench/utils.h" |
| #include <xnnpack/AlignedAllocator.h> |
| #include <xnnpack/common.h> |
| #include <xnnpack/gemm.h> |
| #include <xnnpack/pack.h> |
| #include <xnnpack/params-init.h> |
| #include <xnnpack/params.h> |
| |
| |
| static void GEMMBenchmark(benchmark::State& state, |
| xnn_q8_gemm_ukernel_function q8gemm, |
| size_t mr, size_t nr, size_t kr, size_t sr) |
| { |
| if (!cpuinfo_initialize()) { |
| state.SkipWithError("cpuinfo initialization failed"); |
| 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); |
| |
| std::random_device random_device; |
| auto rng = std::mt19937(random_device()); |
| auto s32rng = std::bind(std::uniform_int_distribution<int32_t>(-10000, 10000), rng); |
| auto u8rng = std::bind(std::uniform_int_distribution<uint32_t>(0, std::numeric_limits<uint8_t>::max()), rng); |
| |
| std::vector<uint8_t> a(mc * kc); |
| std::generate(a.begin(), a.end(), std::ref(u8rng)); |
| std::vector<uint8_t> k(nc * kc); |
| std::generate(k.begin(), k.end(), std::ref(u8rng)); |
| std::vector<int32_t> b(nc); |
| std::generate(b.begin(), b.end(), std::ref(s32rng)); |
| |
| const size_t w_elements = kc_stride * nc_stride + nc_stride * sizeof(int32_t) / sizeof(uint8_t); |
| const size_t c_elements = mc * nc; |
| const size_t num_buffers = 1 + |
| benchmark::utils::DivideRoundUp<size_t>(benchmark::utils::GetMaxCacheSize(), |
| sizeof(uint8_t) * (w_elements + c_elements)); |
| |
| std::vector<uint8_t, AlignedAllocator<uint8_t, 32>> w(w_elements * num_buffers); |
| std::fill(w.begin(), w.end(), 0); |
| const xnn_q8_packing_params packing_params = { 127, 127 }; |
| xnn_pack_q8_gemm_goi_w(1 /* groups */, nc, kc, nr, kr, sr, k.data(), b.data(), w.data(), &packing_params); |
| std::vector<uint8_t> c(c_elements * num_buffers); |
| std::fill(c.begin(), c.end(), 0xA5); |
| |
| union xnn_q8_gemm_params quantization_params = |
| xnn_init_q8_gemm_params(127, 127, 0.75f, 127, 1, 254); |
| |
| 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(uint8_t)); |
| 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); |
| q8gemm( |
| mb, nb, kc * sizeof(uint8_t), |
| a.data() + m * kc, kc * sizeof(uint8_t), |
| w.data() + (w_elements * buffer_index + n * (kc_stride + sizeof(int32_t))) / sizeof(uint8_t), |
| c.data() + (mc * buffer_index + m) * nc + n, nc * sizeof(uint8_t), nr * sizeof(uint8_t), |
| &quantization_params); |
| } |
| } |
| } |
| |
| state.counters["Freq"] = benchmark::utils::GetCurrentCpuFrequency(); |
| state.counters["OPS"] = benchmark::Counter( |
| uint64_t(state.iterations()) * 2 * mc * nc * kc, benchmark::Counter::kIsRate); |
| } |
| |
| #ifdef BENCHMARK_GEMMLOWP |
| struct GemmlowpOutputPipeline { |
| typedef gemmlowp::VectorMap<const int32_t, gemmlowp::VectorShape::Col> ColVectorMap; |
| typedef std::tuple< |
| gemmlowp::OutputStageBiasAddition<ColVectorMap>, |
| gemmlowp::OutputStageQuantizeDownInt32ToUint8ScaleByFixedPoint, |
| gemmlowp::OutputStageClamp, |
| gemmlowp::OutputStageSaturatingCastToUint8> |
| Pipeline; |
| |
| static Pipeline Make( |
| const int32_t* bias_data, |
| int output_rows, |
| int32_t output_offset, |
| int32_t output_multiplier, |
| int output_shift, |
| int32_t output_activation_min, |
| int32_t output_activation_max) |
| { |
| ColVectorMap bias_vector(bias_data, output_rows); |
| gemmlowp::OutputStageBiasAddition<ColVectorMap> bias_addition_stage; |
| bias_addition_stage.bias_vector = bias_vector; |
| gemmlowp::OutputStageQuantizeDownInt32ToUint8ScaleByFixedPoint quantize_down_stage; |
| quantize_down_stage.result_offset_after_shift = output_offset; |
| quantize_down_stage.result_fixedpoint_multiplier = output_multiplier; |
| quantize_down_stage.result_shift = output_shift; |
| gemmlowp::OutputStageClamp clamp_stage; |
| clamp_stage.min = output_activation_min; |
| clamp_stage.max = output_activation_max; |
| gemmlowp::OutputStageSaturatingCastToUint8 saturating_cast_stage; |
| return std::make_tuple(bias_addition_stage, quantize_down_stage, clamp_stage, saturating_cast_stage); |
| } |
| }; |
| |
| static void GemmlowpBenchmark(benchmark::State& state, uint32_t threads) |
| { |
| if (!cpuinfo_initialize()) { |
| state.SkipWithError("cpuinfo initialization failed"); |
| return; |
| } |
| |
| const size_t mc = state.range(0); |
| const size_t nc = state.range(1); |
| const size_t kc = state.range(2); |
| |
| std::random_device random_device; |
| auto rng = std::mt19937(random_device()); |
| auto s32rng = std::bind(std::uniform_int_distribution<int32_t>(-10000, 10000), rng); |
| auto u8rng = std::bind(std::uniform_int_distribution<uint32_t>(0, std::numeric_limits<uint8_t>::max()), rng); |
| |
| std::vector<uint8_t> a(mc * kc); |
| std::generate(a.begin(), a.end(), std::ref(u8rng)); |
| |
| const size_t kElements = nc * kc; |
| const size_t bElements = nc; |
| const size_t c_elements = mc * nc; |
| const size_t num_buffers = 1 + |
| benchmark::utils::DivideRoundUp<size_t>(benchmark::utils::GetMaxCacheSize(), |
| kElements * sizeof(uint8_t) + bElements * sizeof(int32_t) + c_elements * sizeof(uint8_t)); |
| |
| std::vector<uint8_t> k(kElements * num_buffers); |
| std::generate(k.begin(), k.end(), std::ref(u8rng)); |
| std::vector<int32_t> b(bElements * num_buffers); |
| std::generate(b.begin(), b.end(), std::ref(s32rng)); |
| std::vector<uint8_t> c(c_elements * num_buffers); |
| std::fill(c.begin(), c.end(), 0xA5); |
| |
| gemmlowp::MultiThreadGemmContext threadingContext; |
| threadingContext.set_max_num_threads(threads); |
| |
| size_t buffer_index = 0; |
| for (auto _ : state) { |
| state.PauseTiming(); |
| benchmark::utils::PrefetchToL1(a.data(), a.size() * sizeof(uint8_t)); |
| buffer_index = (buffer_index + 1) % num_buffers; |
| state.ResumeTiming(); |
| |
| gemmlowp::MatrixMap<const uint8_t, gemmlowp::MapOrder::RowMajor> AM(a.data(), mc, kc, kc); |
| gemmlowp::MatrixMap<const uint8_t, gemmlowp::MapOrder::ColMajor> BM(k.data() + buffer_index * kElements, kc, nc, kc); |
| gemmlowp::MatrixMap<uint8_t, gemmlowp::MapOrder::RowMajor> CM(c.data() + buffer_index * c_elements, mc, nc, nc); |
| const auto& outputPipeline = GemmlowpOutputPipeline::Make(b.data() + buffer_index * bElements, nc, 127, 127, 127, 0, 255); |
| gemmlowp::GemmWithOutputPipeline<uint8_t, uint8_t, gemmlowp::L8R8WithLhsNonzeroBitDepthParams>( |
| &threadingContext, AM, BM, &CM, 127, 127, outputPipeline); |
| } |
| |
| state.counters["Freq"] = benchmark::utils::GetCurrentCpuFrequency(); |
| state.counters["OPS"] = benchmark::Counter( |
| uint64_t(state.iterations()) * 2 * mc * nc * kc, benchmark::Counter::kIsRate); |
| } |
| |
| static void gemmlowp_st(benchmark::State& state, const char* net) |
| { |
| GemmlowpBenchmark(state, 1); |
| } |
| #endif // BENCHMARK_GEMMLOWP |
| |
| |
| #ifdef BENCHMARK_RUY |
| static void RuyBenchmark(benchmark::State& state, size_t threads) |
| { |
| const size_t mc = state.range(0); |
| const size_t nc = state.range(1); |
| const size_t kc = state.range(2); |
| |
| std::random_device random_device; |
| auto rng = std::mt19937(random_device()); |
| auto s32rng = std::bind(std::uniform_int_distribution<int32_t>(-10000, 10000), rng); |
| auto u8rng = std::bind(std::uniform_int_distribution<uint32_t>(0, std::numeric_limits<uint8_t>::max()), rng); |
| |
| const size_t num_buffers = 1 + |
| benchmark::utils::DivideRoundUp<size_t>(benchmark::utils::GetMaxCacheSize(), |
| nc * (sizeof(uint8_t) * (mc + kc) + sizeof(int32_t))); |
| |
| std::vector<uint8_t> a(mc * kc); |
| std::generate(a.begin(), a.end(), std::ref(u8rng)); |
| std::vector<uint8_t> k(num_buffers * nc * kc); |
| std::generate(k.begin(), k.end(), std::ref(u8rng)); |
| std::vector<int32_t> b(num_buffers * nc); |
| std::generate(b.begin(), b.end(), std::ref(s32rng)); |
| std::vector<uint8_t> c(num_buffers * nc * mc); |
| std::fill(c.begin(), c.end(), std::nanf("")); |
| |
| // Note: context must be static to avoid the cost of re-creating it for each benchmark. |
| static ruy::Context context; |
| context.set_max_num_threads(threads); |
| |
| ruy::Matrix<uint8_t> ruy_a; |
| ruy::MakeSimpleLayout(nc, kc, ruy::Order::kRowMajor, ruy_a.mutable_layout()); |
| ruy_a.set_zero_point(127); |
| ruy::Matrix<uint8_t> ruy_b; |
| ruy::MakeSimpleLayout(kc, mc, ruy::Order::kColMajor, ruy_b.mutable_layout()); |
| ruy_b.set_data(a.data()); |
| ruy_b.set_zero_point(127); |
| ruy::Matrix<uint8_t> ruy_c; |
| ruy::MakeSimpleLayout(nc, mc, ruy::Order::kColMajor, ruy_c.mutable_layout()); |
| ruy_c.set_zero_point(127); |
| |
| ruy::MulParams<int32_t, uint8_t> mul_params; |
| mul_params.set_multiplier_fixedpoint(0x40000000); |
| |
| // ruy::Context uses deferred initialization, which affects percieved GEMM performance. Initialization happens during |
| // the first GEMM calls, and per Benoit Jacob it takes up to ~250 milliseconds for performance to stabilize. |
| // Thus, on the first benchmark, we compute GEMM for 500 milliseconds (to be safe) without recording performance, and |
| // keep the ruy::Context object initialized (by being static) between subsequent benchmarks. |
| static std::once_flag warmup; |
| std::call_once(warmup, [&](){ |
| auto start = std::chrono::steady_clock::now(); |
| do { |
| ruy_a.set_data(k.data()); |
| ruy_c.set_data(c.data()); |
| mul_params.set_bias(b.data()); |
| |
| ruy::Mul(ruy_a, ruy_b, mul_params, &context, &ruy_c); |
| } while (std::chrono::duration<double>(std::chrono::steady_clock::now() - start).count() < 0.5); |
| }); |
| |
| 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) |
| // - K is not in cache (for any cache level) |
| // - B 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(uint8_t)); |
| buffer_index = (buffer_index + 1) % num_buffers; |
| state.ResumeTiming(); |
| |
| ruy_a.set_data(k.data() + buffer_index * nc * kc); |
| ruy_c.set_data(c.data() + buffer_index * mc * nc); |
| mul_params.set_bias(b.data() + buffer_index * nc); |
| |
| ruy::Mul(ruy_a, ruy_b, mul_params, &context, &ruy_c); |
| } |
| |
| state.counters["Freq"] = benchmark::utils::GetCurrentCpuFrequency(); |
| state.counters["OPS"] = benchmark::Counter( |
| uint64_t(state.iterations()) * 2 * mc * nc * kc, benchmark::Counter::kIsRate); |
| } |
| |
| static void ruy_st(benchmark::State& state, const char* net) |
| { |
| RuyBenchmark(state, 1); |
| } |
| #endif // BENCHMARK_RUY |
| |
| |
| #if XNN_ARCH_ARM || XNN_ARCH_ARM64 |
| static void q8gemm_4x8__neon(benchmark::State& state, const char* net) { |
| GEMMBenchmark(state, xnn_q8_gemm_minmax_ukernel_4x8__neon, 4, 8, 1, 1); |
| } |
| |
| static void q8gemm_8x8__neon(benchmark::State& state, const char* net) { |
| GEMMBenchmark(state, xnn_q8_gemm_minmax_ukernel_8x8__neon, 8, 8, 1, 1); |
| } |
| |
| BENCHMARK_GEMM(q8gemm_4x8__neon) |
| BENCHMARK_GEMM(q8gemm_8x8__neon) |
| #endif |
| |
| #if XNN_ARCH_X86 || XNN_ARCH_X86_64 |
| static void q8gemm_4x4c2__sse2(benchmark::State& state, const char* net) { |
| GEMMBenchmark(state, xnn_q8_gemm_minmax_ukernel_4x4c2__sse2, 4, 4, 2, 1); |
| } |
| |
| static void q8gemm_2x4c8__sse2(benchmark::State& state, const char* net) { |
| GEMMBenchmark(state, xnn_q8_gemm_minmax_ukernel_2x4c8__sse2, 2, 4, 8, 1); |
| } |
| |
| BENCHMARK_GEMM(q8gemm_4x4c2__sse2) |
| BENCHMARK_GEMM(q8gemm_2x4c8__sse2) |
| #endif |
| |
| #ifdef BENCHMARK_RUY |
| BENCHMARK_GEMM(ruy_st) |
| #endif // BENCHMARK_RUY |
| #ifdef BENCHMARK_GEMMLOWP |
| BENCHMARK_GEMM(gemmlowp_st) |
| #endif // BENCHMARK_GEMMLOWP |
| |
| #ifndef XNNPACK_BENCHMARK_NO_MAIN |
| BENCHMARK_MAIN(); |
| #endif |