/* ************************************************************************ * Copyright (c) 2020 Advanced Micro Devices, Inc. * * 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. * * ************************************************************************ */ #pragma once #ifndef TESTING_SPARSE_TO_DENSE_CSR_HPP #define TESTING_SPARSE_TO_DENSE_CSR_HPP #include "hipsparse_test_unique_ptr.hpp" #include "unit.hpp" #include "utility.hpp" #include #include #include using namespace hipsparse_test; void testing_sparse_to_dense_csr_bad_arg(void) { #if(!defined(CUDART_VERSION) || CUDART_VERSION >= 11020) int64_t safe_size = 100; int32_t m = 10; int32_t n = 10; int64_t nnz = 10; int64_t ld = m; hipsparseIndexBase_t idxBase = HIPSPARSE_INDEX_BASE_ZERO; hipsparseSparseToDenseAlg_t alg = HIPSPARSE_SPARSETODENSE_ALG_DEFAULT; hipsparseOrder_t order = HIPSPARSE_ORDER_COLUMN; // Index and data type hipsparseIndexType_t iType = HIPSPARSE_INDEX_64I; hipsparseIndexType_t jType = HIPSPARSE_INDEX_32I; hipDataType dataType = HIP_R_32F; // Create handle std::unique_ptr unique_ptr_handle(new handle_struct); hipsparseHandle_t handle = unique_ptr_handle->handle; auto ddense_val_managed = hipsparse_unique_ptr{device_malloc(sizeof(float) * safe_size), device_free}; auto dcsr_row_ptr_managed = hipsparse_unique_ptr{device_malloc(sizeof(int64_t) * safe_size), device_free}; auto dcsr_col_ind_managed = hipsparse_unique_ptr{device_malloc(sizeof(int32_t) * safe_size), device_free}; auto dcsr_val_managed = hipsparse_unique_ptr{device_malloc(sizeof(float) * safe_size), device_free}; auto dbuf_managed = hipsparse_unique_ptr{device_malloc(sizeof(char) * safe_size), device_free}; float* ddense_val = (float*)ddense_val_managed.get(); int64_t* dcsr_row_ptr = (int64_t*)dcsr_row_ptr_managed.get(); int32_t* dcsr_col_ind = (int32_t*)dcsr_col_ind_managed.get(); float* dcsr_val = (float*)dcsr_val_managed.get(); void* dbuf = (void*)dbuf_managed.get(); if(!ddense_val || !dcsr_row_ptr || !dcsr_col_ind || !dcsr_val || !dbuf) { PRINT_IF_HIP_ERROR(hipErrorOutOfMemory); return; } // Matrix structures hipsparseSpMatDescr_t matA; hipsparseDnVecDescr_t matB; size_t bsize; // Create matrix structures verify_hipsparse_status_success(hipsparseCreateCsr(&matA, m, n, nnz, dcsr_row_ptr, dcsr_col_ind, dcsr_val, iType, jType, idxBase, dataType), "success"); verify_hipsparse_status_success( hipsparseCreateDnMat(&matB, m, n, ld, ddense_val, dataType, order), "success"); // SparseToDense buffer size verify_hipsparse_status_invalid_handle( hipsparseSparseToDense_bufferSize(nullptr, matA, matB, alg, &bsize)); verify_hipsparse_status_invalid_pointer( hipsparseSparseToDense_bufferSize(handle, nullptr, matB, alg, &bsize), "Error: matA is nullptr"); verify_hipsparse_status_invalid_pointer( hipsparseSparseToDense_bufferSize(handle, matA, nullptr, alg, &bsize), "Error: matB is nullptr"); verify_hipsparse_status_invalid_pointer( hipsparseSparseToDense_bufferSize(handle, matA, matB, alg, nullptr), "Error: bsize is nullptr"); // SparseToDense verify_hipsparse_status_invalid_handle(hipsparseSparseToDense(nullptr, matA, matB, alg, dbuf)); verify_hipsparse_status_invalid_pointer( hipsparseSparseToDense(handle, nullptr, matB, alg, dbuf), "Error: matA is nullptr"); verify_hipsparse_status_invalid_pointer( hipsparseSparseToDense(handle, matA, nullptr, alg, dbuf), "Error: matB is nullptr"); verify_hipsparse_status_invalid_pointer( hipsparseSparseToDense(handle, matA, matB, alg, nullptr), "Error: dbuf is nullptr"); // Destruct verify_hipsparse_status_success(hipsparseDestroySpMat(matA), "success"); verify_hipsparse_status_success(hipsparseDestroyDnMat(matB), "success"); #endif } template hipsparseStatus_t testing_sparse_to_dense_csr(void) { #if(!defined(CUDART_VERSION) || CUDART_VERSION >= 11020) hipsparseIndexBase_t idx_base = HIPSPARSE_INDEX_BASE_ZERO; hipsparseSparseToDenseAlg_t alg = HIPSPARSE_SPARSETODENSE_ALG_DEFAULT; hipsparseOrder_t order = HIPSPARSE_ORDER_COLUMN; // Matrices are stored at the same path in matrices directory std::string filename = hipsparse_exepath() + "../matrices/nos3.bin"; // Index and data type hipsparseIndexType_t typeI = (typeid(I) == typeid(int32_t)) ? HIPSPARSE_INDEX_32I : HIPSPARSE_INDEX_64I; hipsparseIndexType_t typeJ = (typeid(J) == typeid(int32_t)) ? HIPSPARSE_INDEX_32I : HIPSPARSE_INDEX_64I; hipDataType typeT = (typeid(T) == typeid(float)) ? HIP_R_32F : ((typeid(T) == typeid(double)) ? HIP_R_64F : ((typeid(T) == typeid(hipComplex) ? HIP_C_32F : HIP_C_64F))); // hipSPARSE handle std::unique_ptr test_handle(new handle_struct); hipsparseHandle_t handle = test_handle->handle; // Host structures std::vector hcsr_row_ptr; std::vector hcsr_col_ind; std::vector hcsr_val; // Initial Data on CPU srand(12345ULL); J m; J n; I nnz; if(read_bin_matrix(filename.c_str(), m, n, nnz, hcsr_row_ptr, hcsr_col_ind, hcsr_val, idx_base) != 0) { fprintf(stderr, "Cannot open [read] %s\n", filename.c_str()); return HIPSPARSE_STATUS_INTERNAL_ERROR; } I ld = m; // allocate memory on device auto dptr_managed = hipsparse_unique_ptr{device_malloc(sizeof(I) * (m + 1)), device_free}; auto dcol_managed = hipsparse_unique_ptr{device_malloc(sizeof(J) * nnz), device_free}; auto dval_managed = hipsparse_unique_ptr{device_malloc(sizeof(T) * nnz), device_free}; auto ddense_managed = hipsparse_unique_ptr{device_malloc(sizeof(T) * ld * n), device_free}; I* dptr = (I*)dptr_managed.get(); J* dcol = (J*)dcol_managed.get(); T* dval = (T*)dval_managed.get(); T* ddense = (T*)ddense_managed.get(); if(!dval || !dptr || !dcol || !ddense) { verify_hipsparse_status_success(HIPSPARSE_STATUS_ALLOC_FAILED, "!dval || !dptr || !dcol || !ddense"); return HIPSPARSE_STATUS_ALLOC_FAILED; } // Dense matrix std::vector hdense(ld * n); // copy data from CPU to device CHECK_HIP_ERROR( hipMemcpy(dptr, hcsr_row_ptr.data(), sizeof(I) * (m + 1), hipMemcpyHostToDevice)); CHECK_HIP_ERROR(hipMemcpy(dcol, hcsr_col_ind.data(), sizeof(J) * nnz, hipMemcpyHostToDevice)); CHECK_HIP_ERROR(hipMemcpy(dval, hcsr_val.data(), sizeof(T) * nnz, hipMemcpyHostToDevice)); // Create matrices hipsparseSpMatDescr_t matA; CHECK_HIPSPARSE_ERROR( hipsparseCreateCsr(&matA, m, n, nnz, dptr, dcol, dval, typeI, typeJ, idx_base, typeT)); // Create dense matrix hipsparseDnMatDescr_t matB; CHECK_HIPSPARSE_ERROR(hipsparseCreateDnMat(&matB, m, n, ld, ddense, typeT, order)); // Query SparseToDense buffer size_t bufferSize; CHECK_HIPSPARSE_ERROR(hipsparseSparseToDense_bufferSize(handle, matA, matB, alg, &bufferSize)); void* buffer; CHECK_HIP_ERROR(hipMalloc(&buffer, bufferSize)); CHECK_HIPSPARSE_ERROR(hipsparseSparseToDense(handle, matA, matB, alg, buffer)); // copy output from device to CPU CHECK_HIP_ERROR(hipMemcpy(hdense.data(), ddense, sizeof(T) * ld * n, hipMemcpyDeviceToHost)); // Query for warpSize hipDeviceProp_t prop; hipGetDeviceProperties(&prop, 0); std::vector hdense_cpu(ld * n); for(J col = 0; col < n; ++col) { for(J row = 0; row < m; ++row) { hdense_cpu[row + ld * col] = make_DataType(0.0); } } for(J row = 0; row < m; ++row) { I start = hcsr_row_ptr[row] - idx_base; I end = hcsr_row_ptr[row + 1] - idx_base; for(I at = start; at < end; ++at) { hdense_cpu[(hcsr_col_ind[at] - idx_base) * ld + row] = hcsr_val[at]; } } unit_check_general(m, n, ld, hdense_cpu.data(), hdense.data()); CHECK_HIP_ERROR(hipFree(buffer)); CHECK_HIPSPARSE_ERROR(hipsparseDestroySpMat(matA)); CHECK_HIPSPARSE_ERROR(hipsparseDestroyDnMat(matB)); #endif return HIPSPARSE_STATUS_SUCCESS; } #endif // TESTING_SPARSE_TO_DENSE_CSR_HPP