clSPARSE
v0.10.0.0
a software library containing Sparse functions written in OpenCL
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Sparse BLAS level 2 routines for sparse matrix dense vector. More...
CLSPARSE_EXPORT clsparseStatus | clsparseScsrmv (const clsparseScalar *alpha, const clsparseCsrMatrix *matx, const cldenseVector *x, const clsparseScalar *beta, cldenseVector *y, const clsparseControl control) |
Single precision CSR sparse matrix times dense vector. More... | |
CLSPARSE_EXPORT clsparseStatus | clsparseDcsrmv (const clsparseScalar *alpha, const clsparseCsrMatrix *matx, const cldenseVector *x, const clsparseScalar *beta, cldenseVector *y, const clsparseControl control) |
Double precision CSR sparse matrix times dense vector. More... | |
CLSPARSE_EXPORT clsparseStatus | clsparseScoomv (const clsparseScalar *alpha, const clsparseCooMatrix *matx, const cldenseVector *x, const clsparseScalar *beta, cldenseVector *y, const clsparseControl control) |
Single precision COO sparse matrix times dense vector. More... | |
CLSPARSE_EXPORT clsparseStatus | clsparseDcoomv (const clsparseScalar *alpha, const clsparseCooMatrix *matx, const cldenseVector *x, const clsparseScalar *beta, cldenseVector *y, const clsparseControl control) |
Double precision COO sparse matrix times dense vector. More... | |
Sparse BLAS level 2 routines for sparse matrix dense vector.
Level 2 BLAS operations are defined by order \( N^2 \) operations, usually in the form of a matrix times a vector.
CLSPARSE_EXPORT clsparseStatus clsparseDcoomv | ( | const clsparseScalar * | alpha, |
const clsparseCooMatrix * | matx, | ||
const cldenseVector * | x, | ||
const clsparseScalar * | beta, | ||
cldenseVector * | y, | ||
const clsparseControl | control | ||
) |
Double precision COO sparse matrix times dense vector.
\( y \leftarrow \alpha \ast A \ast x + \beta \ast y \)
[in] | alpha | Scalar value to multiply against sparse matrix |
[in] | matx | Input COO sparse matrix |
[in] | x | Input dense vector |
[in] | beta | Scalar value to multiply against sparse vector |
[out] | y | Output dense vector |
[in] | control | A valid clsparseControl created with clsparseCreateControl |
CLSPARSE_EXPORT clsparseStatus clsparseDcsrmv | ( | const clsparseScalar * | alpha, |
const clsparseCsrMatrix * | matx, | ||
const cldenseVector * | x, | ||
const clsparseScalar * | beta, | ||
cldenseVector * | y, | ||
const clsparseControl | control | ||
) |
Double precision CSR sparse matrix times dense vector.
\( y \leftarrow \alpha \ast A \ast x + \beta \ast y \) If the CSR sparse matrix structure has rowBlocks information included, then the csr-adaptive algorithm is used. Otherwise, the csr-vector algorithm is used.
[in] | alpha | Scalar value to multiply against sparse matrix |
[in] | matx | Input CSR sparse matrix |
[in] | x | Input dense vector |
[in] | beta | Scalar value to multiply against sparse vector |
[out] | y | Output dense vector |
[in] | control | A valid clsparseControl created with clsparseCreateControl |
CLSPARSE_EXPORT clsparseStatus clsparseScoomv | ( | const clsparseScalar * | alpha, |
const clsparseCooMatrix * | matx, | ||
const cldenseVector * | x, | ||
const clsparseScalar * | beta, | ||
cldenseVector * | y, | ||
const clsparseControl | control | ||
) |
Single precision COO sparse matrix times dense vector.
\( y \leftarrow \alpha \ast A \ast x + \beta \ast y \)
[in] | alpha | Scalar value to multiply against sparse matrix |
[in] | matx | Input COO sparse matrix |
[in] | x | Input dense vector |
[in] | beta | Scalar value to multiply against sparse vector |
[out] | y | Output dense vector |
[in] | control | A valid clsparseControl created with clsparseCreateControl |
CLSPARSE_EXPORT clsparseStatus clsparseScsrmv | ( | const clsparseScalar * | alpha, |
const clsparseCsrMatrix * | matx, | ||
const cldenseVector * | x, | ||
const clsparseScalar * | beta, | ||
cldenseVector * | y, | ||
const clsparseControl | control | ||
) |
Single precision CSR sparse matrix times dense vector.
\( y \leftarrow \alpha \ast A \ast x + \beta \ast y \) If the CSR sparse matrix structure has rowBlocks information included, then the csr-adaptive algorithm is used. Otherwise, the csr-vector algorithm is used.
[in] | alpha | Scalar value to multiply against sparse matrix |
[in] | matx | Input CSR sparse matrix |
[in] | x | Input dense vector |
[in] | beta | Scalar value to multiply against sparse vector |
[out] | y | Output dense vector |
[in] | control | A valid clsparseControl created with clsparseCreateControl |