/*! \file */ /* ************************************************************************ * Copyright (C) 2025 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. * * ************************************************************************ */ #ifndef HIPSPARSE_GEMMI_H #define HIPSPARSE_GEMMI_H #ifdef __cplusplus extern "C" { #endif #if(!defined(CUDART_VERSION) || CUDART_VERSION < 12000) /*! \ingroup level3_module * \brief Dense matrix sparse matrix multiplication using the CSC storage format. * * \details * \p hipsparseXgemmi multiplies the scalar \f$\alpha\f$ with a dense column-oriented \f$m \times k\f$ * matrix \f$A\f$ and the sparse \f$k \times n\f$ matrix \f$B\f$, defined in CSC * storage format, and adds the result to the dense column-oriented \f$m \times n\f$ matrix \f$C\f$ that * is multiplied by the scalar \f$\beta\f$, such that * \f[ * C := \alpha \cdot A \cdot B + \beta \cdot C * \f] * * \note * This function is non-blocking and executed asynchronously with respect to the host. * It can return before the actual computation has finished. * * \deprecated * This function is deprecated when using the CUDA backend (CUDA 11.0+) and will be * removed in CUDA 12.0. This deprecation does not apply to the ROCm backend. * * @param[in] * handle handle to the hipSPARSE library context queue. * @param[in] * m number of rows of the dense matrix \f$A\f$. Must be non-negative. * @param[in] * n number of columns of the sparse CSC matrix \f$op(B)\f$ and \f$C\f$. Must be non-negative. * @param[in] * k number of columns of the dense matrix \f$A\f$. Must be non-negative. * @param[in] * nnz number of non-zero entries of the sparse CSC matrix \f$B\f$. Must be non-negative. * @param[in] * alpha scalar \f$\alpha\f$. * @param[in] * A array of dimension \f$lda \times k\f$ (\f$op(A) == A\f$) or * \f$lda \times m\f$ (\f$op(A) == A^T\f$ or \f$op(A) == A^H\f$). * @param[in] * lda leading dimension of \f$A\f$, must be at least \f$m\f$ * (\f$op(A) == A\f$) or \f$k\f$ (\f$op(A) == A^T\f$ or * \f$op(A) == A^H\f$). * @param[in] * cscValB array of \p nnz elements of the sparse CSC matrix \f$B\f$. * @param[in] * cscColPtrB array of \p n+1 elements that point to the start of every column of the * sparse CSC matrix \f$B\f$. * @param[in] * cscRowIndB array of \p nnz elements containing the column indices of the sparse CSC * matrix \f$B\f$. * @param[in] * beta scalar \f$\beta\f$. * @param[inout] * C array of dimension \f$ldc \times n\f$ that holds the values of \f$C\f$. * @param[in] * ldc leading dimension of \f$C\f$, must be at least \f$m\f$. * * \retval HIPSPARSE_STATUS_SUCCESS the operation completed successfully. * \retval HIPSPARSE_STATUS_NOT_INITIALIZED \p handle is not initialized. * \retval HIPSPARSE_STATUS_INVALID_VALUE \p handle, \p alpha or \p beta is nullptr, * \p m, \p n, \p k, or \p nnz is negative, \p lda or \p ldc is invalid, or * \p A, \p cscValB, \p cscColPtrB, \p cscRowIndB, or \p C is nullptr. */ /**@{*/ DEPRECATED_CUDA_11000("The routine will be removed in CUDA 12") HIPSPARSE_EXPORT hipsparseStatus_t hipsparseSgemmi(hipsparseHandle_t handle, int m, int n, int k, int nnz, const float* alpha, const float* A, int lda, const float* cscValB, const int* cscColPtrB, const int* cscRowIndB, const float* beta, float* C, int ldc); DEPRECATED_CUDA_11000("The routine will be removed in CUDA 12") HIPSPARSE_EXPORT hipsparseStatus_t hipsparseDgemmi(hipsparseHandle_t handle, int m, int n, int k, int nnz, const double* alpha, const double* A, int lda, const double* cscValB, const int* cscColPtrB, const int* cscRowIndB, const double* beta, double* C, int ldc); DEPRECATED_CUDA_11000("The routine will be removed in CUDA 12") HIPSPARSE_EXPORT hipsparseStatus_t hipsparseCgemmi(hipsparseHandle_t handle, int m, int n, int k, int nnz, const hipComplex* alpha, const hipComplex* A, int lda, const hipComplex* cscValB, const int* cscColPtrB, const int* cscRowIndB, const hipComplex* beta, hipComplex* C, int ldc); DEPRECATED_CUDA_11000("The routine will be removed in CUDA 12") HIPSPARSE_EXPORT hipsparseStatus_t hipsparseZgemmi(hipsparseHandle_t handle, int m, int n, int k, int nnz, const hipDoubleComplex* alpha, const hipDoubleComplex* A, int lda, const hipDoubleComplex* cscValB, const int* cscColPtrB, const int* cscRowIndB, const hipDoubleComplex* beta, hipDoubleComplex* C, int ldc); /**@}*/ #endif #ifdef __cplusplus } #endif #endif /* HIPSPARSE_GEMMI_H */