/* ************************************************************************ * 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 * copies 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 * IMPLIED, 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 CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE * SOFTWARE. * * ************************************************************************ */ #include #include #include #include #include "testing_common.hpp" using hipblasGetrfModel = ArgumentModel; inline void testname_getrf(const Arguments& arg, std::string& name) { hipblasGetrfModel{}.test_name(arg, name); } template void testing_getrf_bad_arg(const Arguments& arg) { bool FORTRAN = arg.api == hipblas_client_api::FORTRAN; auto hipblasGetrfFn = FORTRAN ? hipblasGetrf : hipblasGetrf; hipblasLocalHandle handle(arg); int64_t N = 101; int64_t M = N; int64_t lda = 102; int64_t Ipiv_size = std::min(M, N); host_matrix hA(M, N, lda); // Allocate device memory device_matrix dA(M, N, lda); device_matrix dIpiv(1, Ipiv_size, 1); device_vector dInfo(1); EXPECT_HIPBLAS_STATUS(hipblasGetrfFn(nullptr, N, dA, lda, dIpiv, dInfo), HIPBLAS_STATUS_NOT_INITIALIZED); EXPECT_HIPBLAS_STATUS(hipblasGetrfFn(handle, -1, dA, lda, dIpiv, dInfo), HIPBLAS_STATUS_INVALID_VALUE); EXPECT_HIPBLAS_STATUS(hipblasGetrfFn(handle, N, dA, N - 1, dIpiv, dInfo), HIPBLAS_STATUS_INVALID_VALUE); // If N == 0, A and ipiv can be nullptr CHECK_HIPBLAS_ERROR(hipblasGetrfFn(handle, 0, nullptr, lda, nullptr, dInfo)); if(arg.bad_arg_all) { EXPECT_HIPBLAS_STATUS(hipblasGetrfFn(handle, N, nullptr, lda, dIpiv, dInfo), HIPBLAS_STATUS_INVALID_VALUE); EXPECT_HIPBLAS_STATUS(hipblasGetrfFn(handle, N, dA, lda, dIpiv, nullptr), HIPBLAS_STATUS_INVALID_VALUE); } } template void testing_getrf(const Arguments& arg) { using U = real_t; bool FORTRAN = arg.api == hipblas_client_api::FORTRAN; auto hipblasGetrfFn = FORTRAN ? hipblasGetrf : hipblasGetrf; int M = arg.N; int N = arg.N; int lda = arg.lda; int Ipiv_size = std::min(M, N); // Check to prevent memory allocation error if(M < 0 || N < 0 || lda < M) { return; } // Naming: dK is in GPU (device) memory. hK is in CPU (host) memory host_matrix hA(M, N, lda); host_matrix hA1(M, N, lda); host_matrix hIpiv(1, Ipiv_size, 1); host_matrix hIpiv64(1, Ipiv_size, 1); host_vector hInfo(1); host_vector hInfo1(1); // Allocate device memory device_matrix dA(M, N, lda); device_matrix dIpiv(1, Ipiv_size, 1); device_vector dInfo(1); // Check device memory allocation CHECK_DEVICE_ALLOCATION(dA.memcheck()); CHECK_DEVICE_ALLOCATION(dIpiv.memcheck()); CHECK_DEVICE_ALLOCATION(dInfo.memcheck()); double gpu_time_used{0}, hipblas_error{0}; hipblasLocalHandle handle(arg); // Initial hA on CPU hipblas_init_matrix(hA, arg, hipblas_client_never_set_nan, hipblas_general_matrix, true); T* A = (T*)hA; // scale A to avoid singularities for(int i = 0; i < M; i++) { for(int j = 0; j < N; j++) { if(i == j) A[i + j * lda] += 400; else A[i + j * lda] -= 4; } } // Copy data from CPU to device CHECK_HIP_ERROR(dA.transfer_from(hA)); CHECK_HIP_ERROR(hipMemset(dIpiv, 0, Ipiv_size * sizeof(int))); CHECK_HIP_ERROR(hipMemset(dInfo, 0, sizeof(int))); if(arg.unit_check || arg.norm_check) { /* ===================================================================== HIPBLAS =================================================================== */ CHECK_HIPBLAS_ERROR(hipblasGetrfFn(handle, N, dA, lda, dIpiv, dInfo)); // Copy output from device to CPU CHECK_HIP_ERROR(hA1.transfer_from(dA)); CHECK_HIP_ERROR(hIpiv.transfer_from(dIpiv)); CHECK_HIP_ERROR(hipMemcpy(hInfo1, dInfo, sizeof(int), hipMemcpyDeviceToHost)); /* ===================================================================== CPU LAPACK =================================================================== */ for(int i = 0; i < Ipiv_size; i++) hIpiv64[0][i] = hIpiv[0][i]; hInfo[0] = ref_getrf(M, N, hA.data(), lda, hIpiv64.data()); hipblas_error = norm_check_general('F', M, N, lda, hA, hA1); if(arg.unit_check) { U eps = std::numeric_limits::epsilon(); double tolerance = eps * 2000; unit_check_error(hipblas_error, tolerance); } } if(arg.timing) { hipStream_t stream; CHECK_HIPBLAS_ERROR(hipblasGetStream(handle, &stream)); int runs = arg.cold_iters + arg.iters; for(int iter = 0; iter < runs; iter++) { if(iter == arg.cold_iters) gpu_time_used = get_time_us_sync(stream); CHECK_HIPBLAS_ERROR(hipblasGetrfFn(handle, N, dA, lda, dIpiv, dInfo)); } gpu_time_used = get_time_us_sync(stream) - gpu_time_used; hipblasGetrfModel{}.log_args(std::cout, arg, gpu_time_used, getrf_gflop_count(N, M), ArgumentLogging::NA_value, hipblas_error); } }