// 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 #include #include #include #include #include #include #include #include #include #include #include "bench/utils.h" #include #include #include #include struct ComputeErrorContext { const float* input; const float* output; float* error; }; static void ComputeError( struct ComputeErrorContext* context, size_t start, size_t range) { const float* input = context->input; const float* output = context->output; float* error = context->error; for (size_t i = start; i < start + range; i++) { const double output_ref = std::sqrt(double(input[i])); const double abs_error = std::abs(output_ref - double(output[i])); const float output_abs = std::abs(output_ref); const float output_ulp = uint32_as_float(float_as_uint32(output_abs) + 1) - output_abs; error[i] = float(abs_error / output_ulp); } } static void SqrtError(benchmark::State& state, xnn_f32_unary_math_fn sqrt, benchmark::utils::IsaCheckFunction isa_check = nullptr) { if (!cpuinfo_initialize()) { state.SkipWithError("failed cpuinfo init"); return; } if (isa_check != nullptr && !isa_check(state)) { return; } const uint32_t min_input = 0x3F800000; const uint32_t max_input = 0x41800000; // Number of elements in one block of inputs/outputs. // Combining multiple elements in a block reduce function call overhead. const size_t block_size = 1048576; // Number of elements in one parallelization tile. Worker threads process this many elements in each task. const size_t tile_size = 64; uint32_t num_threads = cpuinfo_get_processors_count(); #if XNN_ARCH_ARM || XNN_ARCH_ARM64 // Use all cores except for the least performant cluster if (cpuinfo_get_clusters_count() > 1) { num_threads -= cpuinfo_get_cluster(cpuinfo_get_clusters_count() - 1)->core_count; } #endif // XNN_ARCH_ARM || XNN_ARCH_ARM64 std::unique_ptr threadpool( pthreadpool_create(num_threads), pthreadpool_destroy); std::vector> x(block_size); std::vector> y(block_size); std::vector ulp_error(block_size); float max_ulp_error = 0.0f; ComputeErrorContext context; context.input = x.data(); context.output = y.data(); context.error = ulp_error.data(); for (auto _ : state) { for (uint32_t n = min_input; n < max_input; n += block_size) { for (uint32_t i = 0; i < block_size; i++) { x[i] = uint32_as_float(std::min(n + i, max_input)); } std::fill(y.begin(), y.end(), std::nanf("")); sqrt(block_size * sizeof(float), x.data(), y.data()); pthreadpool_parallelize_1d_tile_1d( threadpool.get(), reinterpret_cast(ComputeError), static_cast(&context), block_size, tile_size, 0 /* flags */); max_ulp_error = std::accumulate(ulp_error.cbegin(), ulp_error.cend(), max_ulp_error, static_cast(std::max)); } } state.counters["ULPERROR"] = benchmark::Counter(max_ulp_error); } #if XNN_ARCH_ARM || XNN_ARCH_ARM64 BENCHMARK_CAPTURE(SqrtError, neonfma_nr1fma, xnn_math_f32_sqrt__neonfma_nr1fma, benchmark::utils::CheckNEONFMA) ->Unit(benchmark::kMillisecond) ->Iterations(1); BENCHMARK_CAPTURE(SqrtError, neonfma_nr2fma, xnn_math_f32_sqrt__neonfma_nr2fma, benchmark::utils::CheckNEONFMA) ->Unit(benchmark::kMillisecond) ->Iterations(1); BENCHMARK_CAPTURE(SqrtError, neonfma_nr3fma, xnn_math_f32_sqrt__neonfma_nr3fma, benchmark::utils::CheckNEONFMA) ->Unit(benchmark::kMillisecond) ->Iterations(1); BENCHMARK_CAPTURE(SqrtError, neonfma_nr2fma1adj, xnn_math_f32_sqrt__neonfma_nr2fma1adj, benchmark::utils::CheckNEONFMA) ->Unit(benchmark::kMillisecond) ->Iterations(1); BENCHMARK_CAPTURE(SqrtError, neonfma_nr1rsqrts1fma1adj, xnn_math_f32_sqrt__neonfma_nr1rsqrts1fma1adj, benchmark::utils::CheckNEONFMA) ->Unit(benchmark::kMillisecond) ->Iterations(1); BENCHMARK_CAPTURE(SqrtError, neon_nr1rsqrts, xnn_math_f32_sqrt__neon_nr1rsqrts, benchmark::utils::CheckNEON) ->Unit(benchmark::kMillisecond) ->Iterations(1); BENCHMARK_CAPTURE(SqrtError, neon_nr2rsqrts, xnn_math_f32_sqrt__neon_nr2rsqrts, benchmark::utils::CheckNEON) ->Unit(benchmark::kMillisecond) ->Iterations(1); BENCHMARK_CAPTURE(SqrtError, neon_nr3rsqrts, xnn_math_f32_sqrt__neon_nr3rsqrts, benchmark::utils::CheckNEON) ->Unit(benchmark::kMillisecond) ->Iterations(1); #endif // XNN_ARCH_ARM || XNN_ARCH_ARM64 #if XNN_ARCH_X86 || XNN_ARCH_X86_64 BENCHMARK_CAPTURE(SqrtError, avx512f_nr1fma, xnn_math_f32_sqrt__avx512f_nr1fma, benchmark::utils::CheckAVX512F) ->Unit(benchmark::kMillisecond) ->Iterations(1); BENCHMARK_CAPTURE(SqrtError, avx512f_nr2fma, xnn_math_f32_sqrt__avx512f_nr2fma, benchmark::utils::CheckAVX512F) ->Unit(benchmark::kMillisecond) ->Iterations(1); BENCHMARK_CAPTURE(SqrtError, avx512f_nr1fma1adj, xnn_math_f32_sqrt__avx512f_nr1fma1adj, benchmark::utils::CheckAVX512F) ->Unit(benchmark::kMillisecond) ->Iterations(1); BENCHMARK_CAPTURE(SqrtError, fma3_nr1fma, xnn_math_f32_sqrt__fma3_nr1fma, benchmark::utils::CheckFMA3) ->Unit(benchmark::kMillisecond) ->Iterations(1); BENCHMARK_CAPTURE(SqrtError, fma3_nr2fma, xnn_math_f32_sqrt__fma3_nr2fma, benchmark::utils::CheckFMA3) ->Unit(benchmark::kMillisecond) ->Iterations(1); BENCHMARK_CAPTURE(SqrtError, fma3_nr1fma1adj, xnn_math_f32_sqrt__fma3_nr1fma1adj, benchmark::utils::CheckFMA3) ->Unit(benchmark::kMillisecond) ->Iterations(1); BENCHMARK_CAPTURE(SqrtError, sse_nr1mac, xnn_math_f32_sqrt__sse_nr1mac) ->Unit(benchmark::kMillisecond) ->Iterations(1); BENCHMARK_CAPTURE(SqrtError, sse_nr2mac, xnn_math_f32_sqrt__sse_nr2mac) ->Unit(benchmark::kMillisecond) ->Iterations(1); BENCHMARK_CAPTURE(SqrtError, sse_hh1mac, xnn_math_f32_sqrt__sse_hh1mac) ->Unit(benchmark::kMillisecond) ->Iterations(1); #endif // XNN_ARCH_X86 || XNN_ARCH_X86_64 #ifndef XNNPACK_BENCHMARK_NO_MAIN BENCHMARK_MAIN(); #endif