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290 lines
13 KiB
C
290 lines
13 KiB
C
/*! \file */
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/* ************************************************************************
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* Copyright (C) 2023-2026 Advanced Micro Devices, Inc. All rights Reserved.
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*
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* Permission is hereby granted, free of charge, to any person obtaining a copy
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* of this software and associated documentation files (the Software), to deal
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* in the Software without restriction, including without limitation the rights
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* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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* copies of the Software, and to permit persons to whom the Software is
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* furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in
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* all copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED AS IS, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
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* THE SOFTWARE.
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*
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* ************************************************************************ */
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#ifndef ROCSPARSE_SDDMM_H
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#define ROCSPARSE_SDDMM_H
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#include "../../rocsparse-types.h"
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#include "rocsparse/rocsparse-export.h"
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#ifdef __cplusplus
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extern "C" {
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#endif
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/*! \ingroup generic_module
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* \details
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* \p rocsparse_sddmm_buffer_size returns the size of the required buffer to execute the SDDMM operation from a given configuration.
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* This routine is used in conjunction with \ref rocsparse_sddmm_preprocess() and \ref rocsparse_sddmm().
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*
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* \note
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* This routine does not support execution in a hipGraph context.
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*
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* @param[in]
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* handle handle to the rocSPARSE library context queue.
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* @param[in]
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* opA dense matrix \f$A\f$ operation type.
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* @param[in]
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* opB dense matrix \f$B\f$ operation type.
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* @param[in]
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* alpha scalar \f$\alpha\f$.
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* @param[in]
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* mat_A dense matrix \f$A\f$ descriptor.
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* @param[in]
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* mat_B dense matrix \f$B\f$ descriptor.
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* @param[in]
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* beta scalar \f$\beta\f$.
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* @param[inout]
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* mat_C sparse matrix \f$C\f$ descriptor.
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* @param[in]
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* compute_type floating point precision for the SDDMM computation.
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* @param[in]
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* alg specification of the algorithm to use.
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* @param[out]
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* buffer_size number of bytes of the temporary storage buffer.
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*
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* \retval rocsparse_status_success the operation completed successfully.
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* \retval rocsparse_status_invalid_value the value of \p opA or \p opB is incorrect.
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* \retval rocsparse_status_invalid_handle the library context was not initialized.
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* \retval rocsparse_status_invalid_pointer \p alpha and \p beta are invalid,
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* or the \p mat_A, \p mat_B, \p mat_C, or \p buffer_size pointer is invalid.
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* \retval rocsparse_status_not_implemented
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* \p opA == \ref rocsparse_operation_conjugate_transpose or
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* \p opB == \ref rocsparse_operation_conjugate_transpose.
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*/
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ROCSPARSE_EXPORT
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rocsparse_status rocsparse_sddmm_buffer_size(rocsparse_handle handle,
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rocsparse_operation opA,
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rocsparse_operation opB,
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const void* alpha,
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rocsparse_const_dnmat_descr mat_A,
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rocsparse_const_dnmat_descr mat_B,
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const void* beta,
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rocsparse_spmat_descr mat_C,
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rocsparse_datatype compute_type,
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rocsparse_sddmm_alg alg,
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size_t* buffer_size);
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/*! \ingroup generic_module
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* \details
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* \p rocsparse_sddmm_preprocess executes a part of the algorithm that can be calculated once in the context of multiple
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* calls of the \ref rocsparse_sddmm with the same sparsity pattern.
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*
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* \note
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* This routine does not support execution in a hipGraph context.
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*
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* @param[in]
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* handle handle to the rocSPARSE library context queue.
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* @param[in]
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* opA dense matrix \f$A\f$ operation type.
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* @param[in]
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* opB dense matrix \f$B\f$ operation type.
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* @param[in]
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* alpha scalar \f$\alpha\f$.
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* @param[in]
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* mat_A dense matrix \f$A\f$ descriptor.
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* @param[in]
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* mat_B dense matrix \f$B\f$ descriptor.
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* @param[in]
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* beta scalar \f$\beta\f$.
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* @param[inout]
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* mat_C sparse matrix \f$C\f$ descriptor.
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* @param[in]
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* compute_type floating point precision for the SDDMM computation.
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* @param[in]
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* alg specification of the algorithm to use.
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* @param[in]
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* temp_buffer temporary storage buffer allocated by the user.
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* The size must be greater or equal to the size obtained with \ref rocsparse_sddmm_buffer_size.
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*
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* \retval rocsparse_status_success the operation completed successfully.
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* \retval rocsparse_status_invalid_value the value of \p opA or \p opB is incorrect.
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* \retval rocsparse_status_invalid_handle the library context was not initialized.
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* \retval rocsparse_status_invalid_pointer \p alpha and \p beta are invalid, or the
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* \p mat_A, \p mat_B, \p mat_C, or \p temp_buffer pointer is invalid.
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* \retval rocsparse_status_not_implemented
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* \p opA == \ref rocsparse_operation_conjugate_transpose or
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* \p opB == \ref rocsparse_operation_conjugate_transpose.
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*/
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ROCSPARSE_EXPORT
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rocsparse_status rocsparse_sddmm_preprocess(rocsparse_handle handle,
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rocsparse_operation opA,
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rocsparse_operation opB,
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const void* alpha,
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rocsparse_const_dnmat_descr mat_A,
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rocsparse_const_dnmat_descr mat_B,
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const void* beta,
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rocsparse_spmat_descr mat_C,
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rocsparse_datatype compute_type,
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rocsparse_sddmm_alg alg,
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void* temp_buffer);
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/*! \ingroup generic_module
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* \brief Sampled Dense-Dense Matrix Multiplication.
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*
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* \details
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* \p rocsparse_sddmm multiplies the scalar \f$\alpha\f$ with the dense
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* \f$m \times k\f$ matrix \f$op(A)\f$, the dense \f$k \times n\f$ matrix \f$op(B)\f$, filtered by the sparsity pattern
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* of the \f$m \times n\f$ sparse matrix \f$C\f$ and adds the result to \f$C\f$ scaled by
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* \f$\beta\f$. The final result is stored in the sparse \f$m \times n\f$ matrix \f$C\f$,
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* such that
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* \f[
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* C := \alpha ( op(A) \cdot op(B) ) \circ spy(C) + \beta C,
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* \f]
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* with
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* \f[
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* op(A) = \left\{
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* \begin{array}{ll}
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* A, & \text{if op(A) == rocsparse_operation_none} \\
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* A^T, & \text{if op(A) == rocsparse_operation_transpose} \\
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* \end{array}
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* \right.
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* \f],
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* \f[
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* op(B) = \left\{
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* \begin{array}{ll}
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* B, & \text{if op(B) == rocsparse_operation_none} \\
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* B^T, & \text{if op(B) == rocsparse_operation_transpose} \\
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* \end{array}
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* \right.
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* \f]
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* and
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* \f[
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* spy(C)_{ij} = \left\{
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* \begin{array}{ll}
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* 1, & \text{ if C_{ij} != 0} \\
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* 0, & \text{ otherwise} \\
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* \end{array}
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* \right.
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* \f]
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*
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* Computing the above sampled dense-dense multiplication requires three steps to complete. First, call
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* \ref rocsparse_sddmm_buffer_size to determine the size of the required temporary storage buffer. Next,
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* allocate this buffer and call \ref rocsparse_sddmm_preprocess, which performs any analysis of the input matrices
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* that might be required. Finally, call \p rocsparse_sddmm to complete the computation. After all calls to
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* \p rocsparse_sddmm are complete, the temporary buffer can be deallocated.
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*
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* \p rocsparse_sddmm supports different algorithms which can provide better performance for different matrices.
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*
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* <table>
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* <caption id="sddmm_algorithms">Algorithms</caption>
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* <tr><th>Algorithms <th>Deterministic <th>Preprocessing <th>Notes
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* <tr><td>rocsparse_sddmm_alg_default</td> <td>Yes</td> <td>No</td> <td>Uses the sparsity pattern of matrix C to perform a limited set of dot products. </td>
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* <tr><td>rocsparse_sddmm_alg_dense</td> <td>Yes</td> <td>No</td> <td>Explicitly converts the matrix C into a dense matrix to perform a dense matrix multiply and add. </td>
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* </table>
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*
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* Currently, \p rocsparse_sddmm only supports the uniform precisions indicated in the table below. For the sparse matrix \f$C\f$, \p rocsparse_sddmm supports the index types
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* \ref rocsparse_indextype_i32 and \ref rocsparse_indextype_i64.
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*
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* \par Uniform Precisions:
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* <table>
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* <caption id="sddmm_uniform">Uniform Precisions</caption>
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* <tr><th>A / B / C / compute_type
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* <tr><td>rocsparse_datatype_f16_r
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* <tr><td>rocsparse_datatype_f32_r
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* <tr><td>rocsparse_datatype_f64_r
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* <tr><td>rocsparse_datatype_f32_c
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* <tr><td>rocsparse_datatype_f64_c
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* </table>
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*
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* \par Mixed Precisions:
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* <table>
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* <caption id="sddmm_mixed">Mixed Precisions</caption>
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* <tr><th>A / B <th>C <th>compute_type
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* <tr><td>rocsparse_datatype_f16_r <td>rocsparse_datatype_f32_r <td>rocsparse_datatype_f32_r
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* <tr><td>rocsparse_datatype_f16_r <td>rocsparse_datatype_f16_r <td>rocsparse_datatype_f32_r
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* <tr><td>rocsparse_datatype_bf16_r <td>rocsparse_datatype_f32_r <td>rocsparse_datatype_f32_r
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* <tr><td>rocsparse_datatype_bf16_r <td>rocsparse_datatype_bf16_r <td>rocsparse_datatype_f32_r
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* </table>
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*
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* \note
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* The sparse matrix formats currently supported are: \ref rocsparse_format_csr,
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* \ref rocsparse_format_csc, \ref rocsparse_format_coo, \ref rocsparse_format_coo_aos,
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* and \ref rocsparse_format_ell.
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*
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* \note \p opA == \ref rocsparse_operation_conjugate_transpose is not supported.
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* \note \p opB == \ref rocsparse_operation_conjugate_transpose is not supported.
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*
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* \note
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* This routine supports execution in a hipGraph context only when \p alg == \ref rocsparse_sddmm_alg_default.
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*
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* \note
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* This routine does not support batched computation.
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*
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* @param[in]
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* handle handle to the rocSPARSE library context queue.
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* @param[in]
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* opA dense matrix \f$A\f$ operation type.
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* @param[in]
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* opB dense matrix \f$B\f$ operation type.
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* @param[in]
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* alpha scalar \f$\alpha\f$.
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* @param[in]
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* mat_A dense matrix \f$A\f$ descriptor.
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* @param[in]
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* mat_B dense matrix \f$B\f$ descriptor.
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* @param[in]
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* beta scalar \f$\beta\f$.
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* @param[inout]
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* mat_C sparse matrix \f$C\f$ descriptor.
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* @param[in]
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* compute_type floating point precision for the SDDMM computation.
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* @param[in]
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* alg specification of the algorithm to use.
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* @param[in]
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* temp_buffer temporary storage buffer allocated by the user.
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* The size must be greater or equal to the size obtained with \ref rocsparse_sddmm_buffer_size.
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*
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* \retval rocsparse_status_success the operation completed successfully.
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* \retval rocsparse_status_invalid_value the value of \p opA, \p opB, \p compute\_type, or \p alg is incorrect.
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* \retval rocsparse_status_invalid_handle the library context was not initialized.
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* \retval rocsparse_status_invalid_pointer \p alpha and \p beta are invalid, or the
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* \p mat_A, \p mat_B, \p mat_C, or \p temp_buffer pointer is invalid.
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* \retval rocsparse_status_not_implemented
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* \p opA == \ref rocsparse_operation_conjugate_transpose or
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* \p opB == \ref rocsparse_operation_conjugate_transpose.
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*
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* \par Example
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* This example performs a sampled dense-dense matrix product, \f$C := \alpha ( A \cdot B ) \circ spy(C) + \beta C\f$
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* where \f$\circ\f$ is the Hadamard product.
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* \snippet example_rocsparse_sddmm.cpp doc example
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*/
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ROCSPARSE_EXPORT
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rocsparse_status rocsparse_sddmm(rocsparse_handle handle,
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rocsparse_operation opA,
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rocsparse_operation opB,
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const void* alpha,
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rocsparse_const_dnmat_descr mat_A,
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rocsparse_const_dnmat_descr mat_B,
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const void* beta,
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rocsparse_spmat_descr mat_C,
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rocsparse_datatype compute_type,
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rocsparse_sddmm_alg alg,
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void* temp_buffer);
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#ifdef __cplusplus
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}
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#endif
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#endif /* ROCSPARSE_SDDMM_H */
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