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165 lines
7.8 KiB
C

/*! \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 */