/* * Copyright (c) Advanced Micro Devices, Inc., or its affiliates. * * SPDX-License-Identifier: MIT */ #pragma once #include "math_common.hh" #include "math_special_values.hh" #include #include namespace cg = cooperative_groups; #define MATH_UNARY_KERNEL_DEF(func_name) \ template \ __global__ void func_name##_kernel(RT* const ys, const size_t num_xs, T* const xs) { \ const auto tid = cg::this_grid().thread_rank(); \ const auto stride = cg::this_grid().size(); \ \ for (size_t i = tid; i < num_xs; i += stride) { \ if constexpr (std::is_same_v) { \ ys[i] = func_name##f(xs[i]); \ } else if constexpr (std::is_same_v) { \ ys[i] = func_name(xs[i]); \ } \ } \ } template void UnaryHalfPrecisionBruteForceTest(kernel_sig kernel, ref_sig ref_func, const ValidatorBuilder& validator_builder) { const auto [grid_size, block_size] = GetOccupancyMaxPotentialBlockSize(kernel); const auto reduction_factor = GetTestReductionFactor(); const auto inv_reduction_factor = 1 / reduction_factor; const auto stop = static_cast( std::ceil((std::numeric_limits::max() + 1ul) * reduction_factor)); const auto max_batch_size = std::min(GetMaxAllowedDeviceMemoryUsage() / (sizeof(Float16) + sizeof(T)), stop); LinearAllocGuard values{LinearAllocs::hipHostMalloc, max_batch_size * sizeof(Float16)}; MathTest math_test(kernel, max_batch_size); auto batch_size = max_batch_size; const auto num_threads = thread_pool.thread_count(); for (uint64_t v = 0u; v < stop;) { batch_size = std::min(max_batch_size, stop - v); const auto min_sub_batch_size = batch_size / num_threads; const auto tail = batch_size % num_threads; auto base_idx = 0u; for (auto i = 0u; i < num_threads; ++i) { const auto sub_batch_size = min_sub_batch_size + (i < tail); thread_pool.Post([=, &values] { auto t = v * inv_reduction_factor; uint16_t val; for (auto j = 0u; j < sub_batch_size; ++j) { val = static_cast(std::floor(t)); t += inv_reduction_factor; values.ptr()[base_idx + j] = *reinterpret_cast(&val); } }); v += sub_batch_size; base_idx += sub_batch_size; } thread_pool.Wait(); math_test.Run(validator_builder, grid_size, block_size, ref_func, batch_size, values.ptr()); } } template void UnarySinglePrecisionBruteForceTest(kernel_sig kernel, ref_sig ref_func, const ValidatorBuilder& validator_builder) { const auto [grid_size, block_size] = GetOccupancyMaxPotentialBlockSize(kernel); const auto reduction_factor = GetTestReductionFactor(); const auto inv_reduction_factor = 1 / reduction_factor; const auto stop = static_cast( std::ceil((std::numeric_limits::max() + 1ul) * reduction_factor)); const auto max_batch_size = std::min(GetMaxAllowedDeviceMemoryUsage() / (sizeof(float) + sizeof(T)), stop); LinearAllocGuard values{LinearAllocs::hipHostMalloc, max_batch_size * sizeof(float)}; MathTest math_test(kernel, max_batch_size); auto batch_size = max_batch_size; const auto num_threads = thread_pool.thread_count(); for (uint64_t v = 0u; v < stop;) { batch_size = std::min(max_batch_size, stop - v); const auto min_sub_batch_size = batch_size / num_threads; const auto tail = batch_size % num_threads; auto base_idx = 0u; for (auto i = 0u; i < num_threads; ++i) { const auto sub_batch_size = min_sub_batch_size + (i < tail); thread_pool.Post([=, &values] { auto t = v * inv_reduction_factor; uint32_t val; for (auto j = 0u; j < sub_batch_size; ++j) { val = static_cast(std::floor(t)); t += inv_reduction_factor; values.ptr()[base_idx + j] = *reinterpret_cast(&val); } }); v += sub_batch_size; base_idx += sub_batch_size; } thread_pool.Wait(); math_test.Run(validator_builder, grid_size, block_size, ref_func, batch_size, values.ptr()); } } template void UnarySinglePrecisionRangeTest(kernel_sig kernel, ref_sig ref_func, const ValidatorBuilder& validator_builder, const float a, const float b) { const auto [grid_size, block_size] = GetOccupancyMaxPotentialBlockSize(kernel); const auto reduction_factor = GetTestReductionFactor(); const auto max_batch_size = GetMaxAllowedDeviceMemoryUsage() / (sizeof(float) + sizeof(T)); LinearAllocGuard values{LinearAllocs::hipHostMalloc, max_batch_size * sizeof(float)}; MathTest math_test(kernel, max_batch_size); const auto run = [&, gs = grid_size, bs = block_size](size_t inserted) { math_test.Run(validator_builder, gs, bs, ref_func, inserted, values.ptr()); }; SinglePrecisionReducedRun(run, values, a, b, reduction_factor, max_batch_size); } template void UnaryDoublePrecisionBruteForceTest(kernel_sig kernel, ref_sig ref_func, const ValidatorBuilder& validator_builder, const double a = std::numeric_limits::lowest(), const double b = std::numeric_limits::max()) { const auto [grid_size, block_size] = GetOccupancyMaxPotentialBlockSize(kernel); const uint64_t num_iterations = GetTestIterationCount(); const auto max_batch_size = std::min(GetMaxAllowedDeviceMemoryUsage() / (sizeof(double) + sizeof(T)), num_iterations); LinearAllocGuard values{LinearAllocs::hipHostMalloc, max_batch_size * sizeof(double)}; MathTest math_test(kernel, max_batch_size); auto batch_size = max_batch_size; const auto num_threads = thread_pool.thread_count(); for (uint64_t i = 0ul; i < num_iterations; i += batch_size) { batch_size = std::min(max_batch_size, num_iterations - i); const auto min_sub_batch_size = batch_size / num_threads; const auto tail = batch_size % num_threads; auto base_idx = 0u; for (auto i = 0u; i < num_threads; ++i) { const auto sub_batch_size = min_sub_batch_size + (i < tail); thread_pool.Post([=, &values] { const auto generator = [=] { static thread_local std::mt19937 rng(std::random_device{}()); std::uniform_real_distribution unif_dist(a, b); return static_cast(unif_dist(rng)); }; std::generate(values.ptr() + base_idx, values.ptr() + base_idx + sub_batch_size, generator); }); base_idx += sub_batch_size; } thread_pool.Wait(); math_test.Run(validator_builder, grid_size, block_size, ref_func, batch_size, values.ptr()); } } template void UnaryDoublePrecisionSpecialValuesTest(kernel_sig kernel, ref_sig ref_func, const ValidatorBuilder& validator_builder) { const auto [grid_size, block_size] = GetOccupancyMaxPotentialBlockSize(kernel); const auto values = std::get>(kSpecialValRegistry); MathTest math_test(kernel, values.size); math_test.template Run(validator_builder, grid_size, block_size, ref_func, values.size, values.data); } template void UnaryHalfPrecisionTest(kernel_sig kernel, ref_sig ref, const ValidatorBuilder& validator_builder) { SECTION("Brute force") { UnaryHalfPrecisionBruteForceTest(kernel, ref, validator_builder); } } template void UnarySinglePrecisionTest(kernel_sig kernel, ref_sig ref, const ValidatorBuilder& validator_builder) { SECTION("Brute force") { UnarySinglePrecisionBruteForceTest(kernel, ref, validator_builder); } } template void UnaryDoublePrecisionTest(kernel_sig kernel, ref_sig ref, const ValidatorBuilder& validator_builder) { SECTION("Special values") { UnaryDoublePrecisionSpecialValuesTest(kernel, ref, validator_builder); } SECTION("Brute force") { UnaryDoublePrecisionBruteForceTest(kernel, ref, validator_builder); } } #define MATH_UNARY_WITHIN_ULP_TEST_DEF(kern_name, ref_func, sp_ulp, dp_ulp) \ MATH_UNARY_KERNEL_DEF(kern_name) \ \ HIP_TEST_CASE(Unit_Device_##kern_name##_Accuracy_Positive_float) { \ double (*ref)(double) = ref_func; \ UnarySinglePrecisionTest(kern_name##_kernel, ref, \ ULPValidatorBuilderFactory(sp_ulp)); \ } \ \ HIP_TEST_CASE(Unit_Device_##kern_name##_Accuracy_Positive_double) { \ long double (*ref)(long double) = ref_func; \ UnaryDoublePrecisionTest(kern_name##_kernel, ref, \ ULPValidatorBuilderFactory(dp_ulp)); \ } #define MATH_UNARY_WITHIN_ULP_STL_REF_TEST_DEF(func_name, sp_ulp, dp_ulp) \ MATH_UNARY_WITHIN_ULP_TEST_DEF(func_name, std::func_name, sp_ulp, dp_ulp)