/* ************************************************************************ * Copyright (C) 2016-2024 Advanced Micro Devices, Inc. All rights reserved. * * Permission is hereby granted, free of charge, to any person obtaining a copy * of this software and associated documentation files (the "Software"), to deal * in the Software without restriction, including without limitation the rights * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell cop- * ies of the Software, and to permit persons to whom the Software is furnished * to do so, subject to the following conditions: * * The above copyright notice and this permission notice shall be included in all * copies or substantial portions of the Software. * * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IM- * PLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS * FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR * COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER * IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNE- * CTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. * * ************************************************************************ */ #include "client_utility.hpp" #include #include #define DIM1 1023 #define DIM2 1024 #define DIM3 1025 template void mat_mat_mult(T alpha, T beta, int M, int N, int K, const T* A, int As1, int As2, const T* B, int Bs1, int Bs2, T* C, int Cs1, int Cs2) { for(int i1 = 0; i1 < M; i1++) { for(int i2 = 0; i2 < N; i2++) { T t = 0.0; for(int i3 = 0; i3 < K; i3++) { t += A[i1 * As1 + i3 * As2] * B[i3 * Bs1 + i2 * Bs2]; } C[i1 * Cs1 + i2 * Cs2] = beta * C[i1 * Cs1 + i2 * Cs2] + alpha * t; } } } int main() { rocblas_operation transa = rocblas_operation_none, transb = rocblas_operation_transpose; float alpha = 1.1, beta = 0.9; rocblas_int m = DIM1, n = DIM2, k = DIM3; rocblas_int lda, ldb, ldc, size_a, size_b, size_c; int a_stride_1, a_stride_2, b_stride_1, b_stride_2; rocblas_cout << "sgemm example" << std::endl; if(transa == rocblas_operation_none) { lda = m; size_a = k * lda; a_stride_1 = 1; a_stride_2 = lda; rocblas_cout << "N"; } else { lda = k; size_a = m * lda; a_stride_1 = lda; a_stride_2 = 1; rocblas_cout << "T"; } if(transb == rocblas_operation_none) { ldb = k; size_b = n * ldb; b_stride_1 = 1; b_stride_2 = ldb; rocblas_cout << "N: "; } else { ldb = n; size_b = k * ldb; b_stride_1 = ldb; b_stride_2 = 1; rocblas_cout << "T: "; } ldc = m; size_c = n * ldc; // Naming: da is in GPU (device) memory. ha is in CPU (host) memory std::vector ha(size_a); std::vector hb(size_b); std::vector hc(size_c); std::vector hc_gold(size_c); // initial data on host srand(1); for(int i = 0; i < size_a; ++i) { ha[i] = rand() % 17; } for(int i = 0; i < size_b; ++i) { hb[i] = rand() % 17; } for(int i = 0; i < size_c; ++i) { hc[i] = rand() % 17; } hc_gold = hc; // allocate memory on device float *da, *db, *dc; CHECK_HIP_ERROR(hipMalloc(&da, size_a * sizeof(float))); CHECK_HIP_ERROR(hipMalloc(&db, size_b * sizeof(float))); CHECK_HIP_ERROR(hipMalloc(&dc, size_c * sizeof(float))); // copy matrices from host to device CHECK_HIP_ERROR(hipMemcpy(da, ha.data(), sizeof(float) * size_a, hipMemcpyHostToDevice)); CHECK_HIP_ERROR(hipMemcpy(db, hb.data(), sizeof(float) * size_b, hipMemcpyHostToDevice)); CHECK_HIP_ERROR(hipMemcpy(dc, hc.data(), sizeof(float) * size_c, hipMemcpyHostToDevice)); rocblas_handle handle; CHECK_ROCBLAS_ERROR(rocblas_create_handle(&handle)); CHECK_ROCBLAS_ERROR( rocblas_sgemm(handle, transa, transb, m, n, k, &alpha, da, lda, db, ldb, &beta, dc, ldc)); // copy output from device to CPU CHECK_HIP_ERROR(hipMemcpy(hc.data(), dc, sizeof(float) * size_c, hipMemcpyDeviceToHost)); rocblas_cout << "m, n, k, lda, ldb, ldc = " << m << ", " << n << ", " << k << ", " << lda << ", " << ldb << ", " << ldc << std::endl; float max_relative_error = std::numeric_limits::min(); // calculate golden or correct result mat_mat_mult(alpha, beta, m, n, k, ha.data(), a_stride_1, a_stride_2, hb.data(), b_stride_1, b_stride_2, hc_gold.data(), 1, ldc); for(int i = 0; i < size_c; i++) { float relative_error = (hc_gold[i] - hc[i]) / hc_gold[i]; relative_error = relative_error > 0 ? relative_error : -relative_error; max_relative_error = relative_error < max_relative_error ? max_relative_error : relative_error; } float eps = std::numeric_limits::epsilon(); float tolerance = 10; if(max_relative_error != max_relative_error || max_relative_error > eps * tolerance) { rocblas_cout << "FAIL: max_relative_error = " << max_relative_error << std::endl; } else { rocblas_cout << "PASS: max_relative_error = " << max_relative_error << std::endl; } CHECK_HIP_ERROR(hipFree(da)); CHECK_HIP_ERROR(hipFree(db)); CHECK_HIP_ERROR(hipFree(dc)); CHECK_ROCBLAS_ERROR(rocblas_destroy_handle(handle)); return EXIT_SUCCESS; }