/*************************************************************************************************** * Copyright (c) 2024 - 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. * SPDX-License-Identifier: BSD-3-Clause * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions are met: * * 1. Redistributions of source code must retain the above copyright notice, this * list of conditions and the following disclaimer. * * 2. Redistributions in binary form must reproduce the above copyright notice, * this list of conditions and the following disclaimer in the documentation * and/or other materials provided with the distribution. * * 3. Neither the name of the copyright holder nor the names of its * contributors may be used to endorse or promote products derived from * this software without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL * DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR * SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, * OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. * **************************************************************************************************/ #pragma once #include #include "cutlass/util/device_memory.h" template __global__ void reference_abs_diff_kernel( Element* data, Element* data_ref, size_t count, double* max_diff, double* sum_diff, bool print_diff ) { double thread_max_diff = 0; double thread_sum_diff = 0; __shared__ double block_max_diff; __shared__ double block_sum_diff; for (size_t i = threadIdx.x + blockIdx.x * blockDim.x; i < count; i += blockDim.x * gridDim.x) { double diff = fabs(data[i] - data_ref[i]); if (print_diff) if (diff != diff || diff > 0.01f) printf("difference at %lld: %f ... %f vs %f\n", static_cast(i), diff, (double)data[i], (double)data_ref[i]); thread_max_diff = fmax(diff, thread_max_diff); thread_sum_diff += diff; } for (int i = 0; i < blockDim.x; i++) { if (i == threadIdx.x) { if (i == 0) { block_max_diff = thread_max_diff; block_sum_diff = thread_sum_diff; } else { block_max_diff = fmax(block_max_diff, thread_max_diff); block_sum_diff += thread_sum_diff; } } __syncthreads(); } if (threadIdx.x == 0) { atomicAdd(sum_diff, block_sum_diff); for (;;) { unsigned long long prev = *reinterpret_cast(max_diff); double prev_diff = reinterpret_cast(prev); double new_max_diff = fmax(block_max_diff, prev_diff); unsigned long long found = atomicCAS(reinterpret_cast(max_diff), prev, reinterpret_cast(new_max_diff)); if (found == prev) break; } } } template void reference_abs_diff( cutlass::DeviceAllocation const& data, cutlass::DeviceAllocation const& data_ref, double& max_diff, double& mean_diff ) { static bool kPrintDiff = getenv("REF_PRINT_DIFF") && atoi(getenv("REF_PRINT_DIFF")) == 1; cutlass::DeviceAllocation result; result.reset(2); assert(data.size() == data_ref.size()); cudaError_t err = cudaMemset(result.get(), 0, result.size() * sizeof(double)); if (err != cudaSuccess) { std::cerr << "Memset failed. Last CUDA error: " << cudaGetErrorString(err) << std::endl; max_diff = mean_diff = 1e20; return; } dim3 block(256, 1, 1); dim3 grid(1024, 1, 1); reference_abs_diff_kernel<<>>( data.get(), data_ref.get(), data.size(), result.get(), result.get() + 1, kPrintDiff); err = cudaDeviceSynchronize(); if (err != cudaSuccess) { std::cerr << "Difference kernel failed. Last CUDA error: " << cudaGetErrorString(err) << std::endl; max_diff = mean_diff = 1e20; return; } double result_host[2]; err = cudaMemcpy(result_host, result.get(), result.size() * sizeof(double), cudaMemcpyDefault); if (err != cudaSuccess) { std::cerr << "Copy failed. Last CUDA error: " << cudaGetErrorString(err) << std::endl; max_diff = mean_diff = 1e20; return; } max_diff = result_host[0]; mean_diff = result_host[1] / static_cast(data.size()); }