oneapi::mkl::sparse::matmatd

oneMKL - Data Parallel C++ Developer Reference

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ID 772045

Date 10/31/2024

Version

Public

Visible to Intel only — GUID: GUID-C5F4A385-B075-4BAC-AAE7-D5F472ECFF37

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oneapi::mkl::sparse::matmatd

Computes a sparse matrix-sparse matrix product with a dense result.

Description
API
Examples

Description

NOTE:

Refer to Sparse BLAS Supported Data and Integer Types for a list of supported <DATA_TYPE> and <INT_TYPE> data and integer types, and refer to Error Handling for a detailed description of the possible exceptions thrown.

The oneapi::mkl::sparse::matmatd routine computes a sparse matrix-sparse matrix product with a dense matrix result defined as

where: and are scalars, and are sparse matrices, and is a dense matrix of size c_nrows rows by c_ncols columns, and is a matrix modifier for A and B using the following description:

The dense matrix object C is stored with row-major or column-major layout. The sparse matrix objects A and B have an appropriate number of rows and columns for the matrix product.

API

Syntax

Using SYCL buffers:

namespace oneapi::mkl::sparse {
    void matmatd(sycl::queue &queue,
      oneapi::mkl::layout c_layout,
      oneapi::mkl::transpose opA,
      oneapi::mkl::transpose opB,
      const DATA_TYPE alpha,
      matrix_handle_t A,
      matrix_handle_t B,
      const DATA_TYPE beta,
      sycl::buffer<DATA_TYPE, 1> &C
      const std::int64_t c_nrows,
      const std::int64_t c_ncols,
      const std::int64_t ldc);
}

Using USM pointers:

namespace oneapi::mkl::sparse {
    sycl::event matmatd(
        sycl::queue &queue,
        oneapi::mkl::layout c_layout,
        oneapi::mkl::transpose opA,
        oneapi::mkl::transpose opB,
        const DATA_TYPE alpha,
        matrix_handle_t A,
        matrix_handle_t B,
        const DATA_TYPE beta,
        DATA_TYPE *C,
        const std::int64_t c_nrows,
        const std::int64_t c_ncols,
        const std::int64_t ldc,
        const std::vector<sycl::event> &dependencies = {});
}

Include Files

oneapi/mkl/spblas.hpp

Input Parameters

queue

Specifies the SYCL command queue that will be used for SYCL kernels execution.

c_layout

Specifies the storage scheme in memory for the dense matrix C.

opA

Specifies operation op() on input matrix A.

`oneapi::mkl::transpose::nontrans`	Non-transpose, .
`oneapi::mkl::transpose::trans`	Transpose, .
`oneapi::mkl::transpose::conjtrans`	Conjugate transpose, .

opB

Specifies operation op() on input matrix B.

`oneapi::mkl::transpose::nontrans`	Non-transpose, .
`oneapi::mkl::transpose::trans`	Transpose, .
`oneapi::mkl::transpose::conjtrans`	Conjugate transpose, .

alpha

Specifies the scalar, .

A

Handle to object containing sparse matrix and other internal data. Created using one of the oneapi::mkl::sparse::set_<sparse_matrix_type>_data routines.

NOTE:

The ony currently supported case for <sparse_matrix_type> is csr.

B

Handle to object containing sparse matrix and other internal data. Created using one of the oneapi::mkl::sparse::set_<sparse_matrix_type>_data routines.

NOTE:

The ony currently supported case for <sparse_matrix_type> is csr.

beta

Specifies the scalar, .

C

SYCL buffer or device-accessible USM pointer of size at least rows*cols, where

	`layout=oneapi::mkl::layout::col_major`	`layout=oneapi::mkl::layout::row_major`
rows (number of rows in `C`)	ldc	c_ncols
cols (number of columns in `C`)	c_nrows	ldc

c_nrows

Number of rows of matrix C.

c_ncols

Number of columns of matrix C.

ldc

Specifies the leading dimension of matrix C. Must be positive, and at least c_ncols if c_layout=oneapi::mkl::layout::row_major or at least c_nrows if c_layout=oneapi::mkl::layout::col_major.

dependencies

A vector of type std::vector<sycl::event> containing the list of events that the oneapi::mkl::sparse::matmatd routine depends on.

Output Parameters

C: Overwritten by the updated matrix C.

Return Values (USM Only)

sycl::event: SYCL event that can be waited upon or added as a dependency for the completion of the matmatd routine.

Examples

An example of how to use oneapi::mkl::sparse::matmatd with SYCL buffers or USM can be found in the oneMKL installation directory, under:

share/doc/mkl/examples/sycl/sparse_blas/source/csr_matmatd.cpp

share/doc/mkl/examples/sycl/sparse_blas/source/csr_matmatd_usm.cpp

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oneMKL - Data Parallel C++ Developer Reference

oneapi::mkl::sparse::matmatd

Description

API

Examples