| // 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 <cpuinfo.h> |
| |
| #include <benchmark/benchmark.h> |
| #include "bench/gemm.h" |
| #include "bench/utils.h" |
| #include <xnnpack/AlignedAllocator.h> |
| #include <xnnpack/common.h> |
| #include <xnnpack/params-init.h> |
| #include <xnnpack/params.h> |
| #include <xnnpack/spmm.h> |
| |
| |
| static void SpMMBenchmark(benchmark::State& state, |
| xnn_f32_spmm_minmax_ukernel_function spmm, uint32_t mr, uint32_t nr, float sparsity) |
| { |
| 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 f32rng = std::bind(std::uniform_real_distribution<float>(), std::ref(rng)); |
| |
| // if using blocks, generate the reduced matrix first and then extrude along |
| // the block dimension (n), to get the full matrix |
| size_t ncols = nc / nr + nc % nr; |
| std::vector<float> b(ncols * kc); |
| std::vector<float> bias(nc); |
| std::vector<float> w; |
| std::vector<uint32_t> nmap; |
| std::vector<int32_t> dmap; |
| const size_t sparse_end = std::min(size_t(float(b.size()) * sparsity), b.size()); |
| const size_t num_nonzeroes = nr * (b.size() - sparse_end); |
| |
| const size_t w_elements = num_nonzeroes + nc; |
| const size_t c_elements = mc * nc; |
| const size_t dmap_elements = num_nonzeroes / nr; |
| const size_t nmap_elements = nc; |
| const size_t num_buffers = 1 + |
| benchmark::utils::DivideRoundUp<size_t>(benchmark::utils::GetMaxCacheSize(), |
| sizeof(float) * (w_elements + c_elements) + sizeof(uint32_t) * (dmap_elements + nmap_elements)); |
| |
| // Micro-kernel can access one element beyond w and dmap for software pipelining. |
| w.reserve(num_buffers * w_elements + 1); |
| dmap.reserve(num_buffers * dmap_elements + 1); |
| nmap.resize(num_buffers * nmap_elements); |
| |
| std::vector<size_t> a_offsets(num_buffers); |
| |
| for (size_t buffer_index = 0; buffer_index < num_buffers; buffer_index++) { |
| // Re-generate weights. Note: each re-generation produces the number of non-zeroes. |
| std::fill(b.begin(), b.begin() + sparse_end, 0.0f); |
| std::generate(b.begin() + sparse_end, b.end(), std::ref(f32rng)); |
| std::shuffle(b.begin(), b.end(), rng); |
| std::generate(bias.begin(), bias.end(), std::ref(f32rng)); |
| |
| uint32_t first_j = 0, last_j = 0; |
| bool is_first_nonzero = true; |
| for (uint32_t i = 0; i < nc / nr; i++) { |
| for (uint32_t n = 0; n < nr; n++) |
| w.push_back(bias[nr * i + n]); |
| for (uint32_t j = 0; j < kc; j++) { |
| if (b[i * kc + j] != 0.0f) { |
| for (size_t l = 0; l < nr; l++) |
| w.push_back(b[i * kc + j] + static_cast<float>(i)); |
| if (is_first_nonzero) { |
| first_j = j; |
| } else { |
| const ptrdiff_t increment = int32_t(j - last_j) * int32_t(mc) * int32_t(sizeof(float)); |
| dmap.push_back(increment); |
| } |
| last_j = j; |
| is_first_nonzero = false; |
| nmap[buffer_index * nmap_elements + i] += 1; |
| } |
| } |
| } |
| for (uint32_t i = nc / nr; i < ncols; i++) { |
| w.push_back(bias[i]); |
| for (uint32_t j = 0; j < kc; j++) { |
| if (b[i * kc + j] != 0.0f) { |
| w.push_back(b[i * kc + j]); |
| if (is_first_nonzero) { |
| first_j = j; |
| } else { |
| const ptrdiff_t increment = int32_t(j - last_j) * int32_t(mc) * int32_t(sizeof(float)); |
| dmap.push_back(increment); |
| } |
| last_j = j; |
| is_first_nonzero = false; |
| nmap[buffer_index * nmap_elements + i] += 1; |
| } |
| } |
| } |
| { |
| const ptrdiff_t increment = int32_t(first_j - last_j) * int32_t(mc) * int32_t(sizeof(float)); |
| dmap.push_back(increment); |
| } |
| |
| a_offsets[buffer_index] = first_j * mc; |
| } |
| |
| // Micro-kernel can access one element beyond w and dmap for software pipelining. |
| w.resize(w.size() + 1); |
| dmap.resize(dmap.size() + 1); |
| |
| std::vector<float, AlignedAllocator<float, 64>> a(kc * mc); |
| std::vector<float, AlignedAllocator<float, 64>> c(num_buffers * c_elements); |
| |
| std::generate(a.begin(), a.end(), std::ref(f32rng)); |
| std::fill(c.begin(), c.end(), nanf("")); |
| |
| xnn_f32_minmax_params params = |
| xnn_init_f32_minmax_params(-std::numeric_limits<float>::infinity(), +std::numeric_limits<float>::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, Kmap, and Nmap 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(float)); |
| buffer_index = (buffer_index + 1) % num_buffers; |
| state.ResumeTiming(); |
| |
| spmm(mc, nc, |
| a.data() + a_offsets[buffer_index], |
| w.data() + buffer_index * w_elements, |
| dmap.data() + buffer_index * dmap_elements, |
| nmap.data() + buffer_index * nmap_elements, |
| c.data() + buffer_index * c_elements, |
| ¶ms); |
| } |
| |
| state.counters["Freq"] = benchmark::utils::GetCurrentCpuFrequency(); |
| state.counters["FLOPS"] = benchmark::Counter( |
| uint64_t(state.iterations()) * 2 * mc * num_nonzeroes, benchmark::Counter::kIsRate); |
| |
| state.counters["EffFLOPS"] = benchmark::Counter( |
| uint64_t(state.iterations()) * 2 * mc * nc * kc, benchmark::Counter::kIsRate); |
| } |
| |
| |
| #if XNN_ARCH_ARM64 |
| static void spmm80_4x1__neonfma(benchmark::State& state, const char* net) { |
| SpMMBenchmark(state, xnn_f32_spmm_minmax_ukernel_4x1__neonfma, 4, 1, 0.8f); |
| } |
| static void spmm80_4x2__neonfma(benchmark::State& state, const char* net) { |
| SpMMBenchmark(state, xnn_f32_spmm_minmax_ukernel_4x2__neonfma, 4, 2, 0.8f); |
| } |
| static void spmm80_4x4__neonfma(benchmark::State& state, const char* net) { |
| SpMMBenchmark(state, xnn_f32_spmm_minmax_ukernel_4x4__neonfma, 4, 4, 0.8f); |
| } |
| |
| static void spmm80_8x1__neonfma(benchmark::State& state, const char* net) { |
| SpMMBenchmark(state, xnn_f32_spmm_minmax_ukernel_8x1__neonfma, 8, 1, 0.8f); |
| } |
| |
| static void spmm80_8x2__neonfma(benchmark::State& state, const char* net) { |
| SpMMBenchmark(state, xnn_f32_spmm_minmax_ukernel_8x2__neonfma, 8, 2, 0.8f); |
| } |
| |
| static void spmm80_8x4__neonfma(benchmark::State& state, const char* net) { |
| SpMMBenchmark(state, xnn_f32_spmm_minmax_ukernel_8x4__neonfma, 8, 4, 0.8f); |
| } |
| |
| static void spmm80_12x1__neonfma(benchmark::State& state, const char* net) { |
| SpMMBenchmark(state, xnn_f32_spmm_minmax_ukernel_12x1__neonfma, 12, 1, 0.8f); |
| } |
| |
| static void spmm80_12x2__neonfma(benchmark::State& state, const char* net) { |
| SpMMBenchmark(state, xnn_f32_spmm_minmax_ukernel_12x2__neonfma, 12, 2, 0.8f); |
| } |
| |
| static void spmm80_12x4__neonfma(benchmark::State& state, const char* net) { |
| SpMMBenchmark(state, xnn_f32_spmm_minmax_ukernel_12x4__neonfma, 12, 4, 0.8f); |
| } |
| |
| static void spmm80_16x1__neonfma(benchmark::State& state, const char* net) { |
| SpMMBenchmark(state, xnn_f32_spmm_minmax_ukernel_16x1__neonfma, 16, 1, 0.8f); |
| } |
| |
| static void spmm80_16x2__neonfma(benchmark::State& state, const char* net) { |
| SpMMBenchmark(state, xnn_f32_spmm_minmax_ukernel_16x2__neonfma, 16, 2, 0.8f); |
| } |
| |
| static void spmm80_16x4__neonfma(benchmark::State& state, const char* net) { |
| SpMMBenchmark(state, xnn_f32_spmm_minmax_ukernel_16x4__neonfma, 16, 4, 0.8f); |
| } |
| |
| static void spmm80_4x1__neonfma_unroll2(benchmark::State& state, const char* net) { |
| SpMMBenchmark(state, xnn_f32_spmm_minmax_ukernel_4x1__neonfma_unroll2, 4, 1, 0.8f); |
| } |
| |
| static void spmm80_8x1__neonfma_unroll2(benchmark::State& state, const char* net) { |
| SpMMBenchmark(state, xnn_f32_spmm_minmax_ukernel_8x1__neonfma_unroll2, 8, 1, 0.8f); |
| } |
| |
| static void spmm80_16x1__neonfma_unroll2(benchmark::State& state, const char* net) { |
| SpMMBenchmark(state, xnn_f32_spmm_minmax_ukernel_16x1__neonfma_unroll2, 16, 1, 0.8f); |
| } |
| |
| static void spmm80_4x1__neonfma_pipelined(benchmark::State& state, const char* net) { |
| SpMMBenchmark(state, xnn_f32_spmm_minmax_ukernel_4x1__neonfma_pipelined, 4, 1, 0.8f); |
| } |
| |
| static void spmm80_8x1__neonfma_pipelined(benchmark::State& state, const char* net) { |
| SpMMBenchmark(state, xnn_f32_spmm_minmax_ukernel_8x1__neonfma_pipelined, 8, 1, 0.8f); |
| } |
| |
| static void spmm80_16x1__neonfma_pipelined(benchmark::State& state, const char* net) { |
| SpMMBenchmark(state, xnn_f32_spmm_minmax_ukernel_16x1__neonfma_pipelined, 16, 1, 0.8f); |
| } |
| |
| BENCHMARK_GEMM(spmm80_4x1__neonfma) |
| BENCHMARK_GEMM(spmm80_4x2__neonfma) |
| BENCHMARK_GEMM(spmm80_4x4__neonfma) |
| BENCHMARK_GEMM(spmm80_8x1__neonfma) |
| BENCHMARK_GEMM(spmm80_8x2__neonfma) |
| BENCHMARK_GEMM(spmm80_8x4__neonfma) |
| BENCHMARK_GEMM(spmm80_12x1__neonfma) |
| BENCHMARK_GEMM(spmm80_12x2__neonfma) |
| BENCHMARK_GEMM(spmm80_12x4__neonfma) |
| BENCHMARK_GEMM(spmm80_16x1__neonfma) |
| BENCHMARK_GEMM(spmm80_16x2__neonfma) |
| BENCHMARK_GEMM(spmm80_16x4__neonfma) |
| BENCHMARK_GEMM(spmm80_4x1__neonfma_unroll2) |
| BENCHMARK_GEMM(spmm80_8x1__neonfma_unroll2) |
| BENCHMARK_GEMM(spmm80_16x1__neonfma_unroll2) |
| BENCHMARK_GEMM(spmm80_4x1__neonfma_pipelined) |
| BENCHMARK_GEMM(spmm80_8x1__neonfma_pipelined) |
| BENCHMARK_GEMM(spmm80_16x1__neonfma_pipelined) |
| #endif // XNN_ARCH_ARM64 |
| |
| #if XNN_ARCH_X86 || XNN_ARCH_X86_64 |
| static void spmm80_4x1__sse(benchmark::State& state, const char* net) { |
| SpMMBenchmark(state, xnn_f32_spmm_minmax_ukernel_4x1__sse, 4, 1, 0.8f); |
| } |
| |
| static void spmm80_8x1__sse(benchmark::State& state, const char* net) { |
| SpMMBenchmark(state, xnn_f32_spmm_minmax_ukernel_8x1__sse, 8, 1, 0.8f); |
| } |
| |
| static void spmm80_16x1__sse(benchmark::State& state, const char* net) { |
| SpMMBenchmark(state, xnn_f32_spmm_minmax_ukernel_16x1__sse, 16, 1, 0.8f); |
| } |
| |
| BENCHMARK_GEMM(spmm80_4x1__sse) |
| BENCHMARK_GEMM(spmm80_8x1__sse) |
| BENCHMARK_GEMM(spmm80_16x1__sse) |
| #endif // XNN_ARCH_X86 || XNN_ARCH_X86_64 |
| |
| static void spmm80_1x1__scalar(benchmark::State& state, const char* net) { |
| SpMMBenchmark(state, xnn_f32_spmm_minmax_ukernel_1x1__scalar, 1, 1, 0.8f); |
| } |
| |
| static void spmm80_2x1__scalar(benchmark::State& state, const char* net) { |
| SpMMBenchmark(state, xnn_f32_spmm_minmax_ukernel_2x1__scalar, 2, 1, 0.8f); |
| } |
| |
| static void spmm80_4x1__scalar(benchmark::State& state, const char* net) { |
| SpMMBenchmark(state, xnn_f32_spmm_minmax_ukernel_4x1__scalar, 4, 1, 0.8f); |
| } |
| |
| static void spmm80_8x1__scalar(benchmark::State& state, const char* net) { |
| SpMMBenchmark(state, xnn_f32_spmm_minmax_ukernel_8x1__scalar, 8, 1, 0.8f); |
| } |
| |
| static void spmm80_8x2__scalar(benchmark::State& state, const char* net) { |
| SpMMBenchmark(state, xnn_f32_spmm_minmax_ukernel_8x2__scalar, 8, 2, 0.8f); |
| } |
| |
| static void spmm80_8x4__scalar(benchmark::State& state, const char* net) { |
| SpMMBenchmark(state, xnn_f32_spmm_minmax_ukernel_8x4__scalar, 8, 4, 0.8f); |
| } |
| |
| static void spmm80_1x1__scalar_pipelined(benchmark::State& state, const char* net) { |
| SpMMBenchmark(state, xnn_f32_spmm_minmax_ukernel_1x1__scalar_pipelined, 1, 1, 0.8f); |
| } |
| |
| static void spmm80_2x1__scalar_pipelined(benchmark::State& state, const char* net) { |
| SpMMBenchmark(state, xnn_f32_spmm_minmax_ukernel_2x1__scalar_pipelined, 2, 1, 0.8f); |
| } |
| |
| static void spmm80_4x1__scalar_pipelined(benchmark::State& state, const char* net) { |
| SpMMBenchmark(state, xnn_f32_spmm_minmax_ukernel_4x1__scalar_pipelined, 4, 1, 0.8f); |
| } |
| |
| static void spmm80_8x1__scalar_pipelined(benchmark::State& state, const char* net) { |
| SpMMBenchmark(state, xnn_f32_spmm_minmax_ukernel_8x1__scalar_pipelined, 8, 1, 0.8f); |
| } |
| |
| BENCHMARK_GEMM(spmm80_1x1__scalar) |
| BENCHMARK_GEMM(spmm80_2x1__scalar) |
| BENCHMARK_GEMM(spmm80_4x1__scalar) |
| BENCHMARK_GEMM(spmm80_8x1__scalar) |
| BENCHMARK_GEMM(spmm80_8x2__scalar) |
| BENCHMARK_GEMM(spmm80_8x4__scalar) |
| BENCHMARK_GEMM(spmm80_1x1__scalar_pipelined) |
| BENCHMARK_GEMM(spmm80_2x1__scalar_pipelined) |
| BENCHMARK_GEMM(spmm80_4x1__scalar_pipelined) |
| BENCHMARK_GEMM(spmm80_8x1__scalar_pipelined) |
| |
| #if !XNN_ARCH_WASM && !XNN_COMPILER_MSVC && !XNN_COMPILER_ICC |
| static void spmm80_4x1__psimd(benchmark::State& state, const char* net) { |
| SpMMBenchmark(state, xnn_f32_spmm_minmax_ukernel_4x1__psimd, 4, 1, 0.8f); |
| } |
| |
| static void spmm80_8x1__psimd(benchmark::State& state, const char* net) { |
| SpMMBenchmark(state, xnn_f32_spmm_minmax_ukernel_8x1__psimd, 8, 1, 0.8f); |
| } |
| |
| static void spmm80_16x1__psimd(benchmark::State& state, const char* net) { |
| SpMMBenchmark(state, xnn_f32_spmm_minmax_ukernel_16x1__psimd, 16, 1, 0.8f); |
| } |
| |
| BENCHMARK_GEMM(spmm80_4x1__psimd) |
| BENCHMARK_GEMM(spmm80_8x1__psimd) |
| BENCHMARK_GEMM(spmm80_16x1__psimd) |
| #endif // !XNN_ARCH_WASM && !XNN_COMPILER_MSVC && !XNN_COMPILER_ICC |
| |
| #ifndef XNNPACK_BENCHMARK_NO_MAIN |
| BENCHMARK_MAIN(); |
| #endif |