Sparse Generic Functions

Sparse Generic Functions#

This module holds all sparse generic routines.

The sparse generic routines describe operations that manipulate sparse matrices.

hipsparseAxpby()#

hipsparseStatus_t hipsparseAxpby(hipsparseHandle_t handle, const void *alpha, hipsparseSpVecDescr_t vecX, const void *beta, hipsparseDnVecDescr_t vecY)#

Description: Scale a sparse vector and add it to a scaled dense vector.

hipsparseAxpby multiplies the sparse vector $x$ with scalar $α$ and adds the result to the dense vector $y$ that is multiplied with scalar $β$ , such that

y := α \cdot x + β \cdot y

for(i = 0; i < nnz; ++i)
{
    y[x_ind[i]] = alpha * x_val[i] + beta * y[x_ind[i]]
}

hipsparseGather()#

hipsparseStatus_t hipsparseGather(hipsparseHandle_t handle, hipsparseDnVecDescr_t vecY, hipsparseSpVecDescr_t vecX)#

Description: Gather elements from a dense vector and store them into a sparse vector.

hipsparseGather gathers the elements from the dense vector $y$ and stores them in the sparse vector $x$ .

for(i = 0; i < nnz; ++i)
{
    x_val[i] = y[x_ind[i]];
}

hipsparseScatter()#

hipsparseStatus_t hipsparseScatter(hipsparseHandle_t handle, hipsparseSpVecDescr_t vecX, hipsparseDnVecDescr_t vecY)#

Description: Scatter elements from a sparse vector into a dense vector.

hipsparseScatter scatters the elements from the sparse vector $x$ in the dense vector $y$ .

for(i = 0; i < nnz; ++i)
{
    y[x_ind[i]] = x_val[i];
}

hipsparseRot()#

hipsparseStatus_t hipsparseRot(hipsparseHandle_t handle, const void *c_coeff, const void *s_coeff, hipsparseSpVecDescr_t vecX, hipsparseDnVecDescr_t vecY)#

Description: Apply Givens rotation to a dense and a sparse vector.

hipsparseRot applies the Givens rotation matrix $G$ to the sparse vector $x$ and the dense vector $y$ , where

\begin{array}{r} G = (\begin{array}{c} c & s \\ - s & c \end{array}) \end{array}

for(i = 0; i < nnz; ++i)
{
    x_tmp = x_val[i];
    y_tmp = y[x_ind[i]];

    x_val[i]    = c * x_tmp + s * y_tmp;
    y[x_ind[i]] = c * y_tmp - s * x_tmp;
}

hipsparseSparseToDense_bufferSize()#

hipsparseStatus_t hipsparseSparseToDense_bufferSize(hipsparseHandle_t handle, hipsparseSpMatDescr_t matA, hipsparseDnMatDescr_t matB, hipsparseSparseToDenseAlg_t alg, size_t *bufferSize)#

Description: Sparse matrix to dense matrix conversion.

hipsparseSparseToDense_bufferSize computes the required user allocated buffer size needed when converting a sparse matrix to a dense matrix.

hipsparseSparseToDense()#

hipsparseStatus_t hipsparseSparseToDense(hipsparseHandle_t handle, hipsparseSpMatDescr_t matA, hipsparseDnMatDescr_t matB, hipsparseSparseToDenseAlg_t alg, void *externalBuffer)#

Description: Sparse matrix to dense matrix conversion.

hipsparseSparseToDense converts a sparse matrix to a dense matrix. This routine takes a user allocated buffer whose size must first be computed by calling hipsparseSparseToDense_bufferSize

hipsparseDenseToSparse_bufferSize()#

hipsparseStatus_t hipsparseDenseToSparse_bufferSize(hipsparseHandle_t handle, hipsparseDnMatDescr_t matA, hipsparseSpMatDescr_t matB, hipsparseDenseToSparseAlg_t alg, size_t *bufferSize)#

Description: Dense matrix to sparse matrix conversion.

hipsparseDenseToSparse_bufferSize computes the required user allocated buffer size needed when converting a dense matrix to a sparse matrix.

hipsparseDenseToSparse_analysis()#

hipsparseStatus_t hipsparseDenseToSparse_analysis(hipsparseHandle_t handle, hipsparseDnMatDescr_t matA, hipsparseSpMatDescr_t matB, hipsparseDenseToSparseAlg_t alg, void *externalBuffer)#

Description: Dense matrix to sparse matrix conversion.

hipsparseDenseToSparse_analysis performs analysis that is later used in hipsparseDenseToSparse_convert when converting a dense matrix to sparse matrix. This routine takes a user allocated buffer whose size must first be computed using hipsparseDenseToSparse_bufferSize.

hipsparseDenseToSparse_convert()#

hipsparseStatus_t hipsparseDenseToSparse_convert(hipsparseHandle_t handle, hipsparseDnMatDescr_t matA, hipsparseSpMatDescr_t matB, hipsparseDenseToSparseAlg_t alg, void *externalBuffer)#

Description: Dense matrix to sparse matrix conversion.

hipsparseDenseToSparse_convert converts a dense matrix to a sparse matrix. This routine requires a user allocated buffer whose size must be determined by first calling hipsparseDenseToSparse_bufferSize.

hipsparseSpVV_bufferSize()#

hipsparseStatus_t hipsparseSpVV_bufferSize(hipsparseHandle_t handle, hipsparseOperation_t opX, hipsparseSpVecDescr_t vecX, hipsparseDnVecDescr_t vecY, void *result, hipDataType computeType, size_t *bufferSize)#

Description: Compute the inner dot product of a sparse vector with a dense vector.

hipsparseSpVV_bufferSize computes the required user allocated buffer size needed when computing the inner dot product of a sparse vector with a dense vector

hipsparseSpVV()#

hipsparseStatus_t hipsparseSpVV(hipsparseHandle_t handle, hipsparseOperation_t opX, hipsparseSpVecDescr_t vecX, hipsparseDnVecDescr_t vecY, void *result, hipDataType computeType, void *externalBuffer)#

Description: Compute the inner dot product of a sparse vector with a dense vector.

hipsparseSpVV computes the inner dot product of a sparse vector with a dense vector. This routine takes a user allocated buffer whose size must first be computed by calling hipsparseSpVV_bufferSize

hipsparseSpMV_bufferSize()#

hipsparseStatus_t hipsparseSpMV_bufferSize(hipsparseHandle_t handle, hipsparseOperation_t opA, const void *alpha, const hipsparseSpMatDescr_t matA, const hipsparseDnVecDescr_t vecX, const void *beta, const hipsparseDnVecDescr_t vecY, hipDataType computeType, hipsparseSpMVAlg_t alg, size_t *bufferSize)#

Description: Buffer size step of the sparse matrix multiplication with a dense vector.

hipsparseSpMV_bufferSize computes the required user allocated buffer size needed when computing the sparse matrix multiplication with a dense vector

hipsparseSpMV()#

hipsparseStatus_t hipsparseSpMV(hipsparseHandle_t handle, hipsparseOperation_t opA, const void *alpha, const hipsparseSpMatDescr_t matA, const hipsparseDnVecDescr_t vecX, const void *beta, const hipsparseDnVecDescr_t vecY, hipDataType computeType, hipsparseSpMVAlg_t alg, void *externalBuffer)#

Description: Compute the sparse matrix multiplication with a dense vector.

hipsparseSpMV computes sparse matrix multiplication with a dense vector

hipsparseSpMM_bufferSize()#

hipsparseStatus_t hipsparseSpMM_bufferSize(hipsparseHandle_t handle, hipsparseOperation_t opA, hipsparseOperation_t opB, const void *alpha, const hipsparseSpMatDescr_t matA, const hipsparseDnMatDescr_t matB, const void *beta, const hipsparseDnMatDescr_t matC, hipDataType computeType, hipsparseSpMMAlg_t alg, size_t *bufferSize)#

Description: Calculate the buffer size required for the sparse matrix multiplication with a dense matrix.

hipsparseSpMM_bufferSize computes the required user allocated buffer size needed when computing the sparse matrix multiplication with a dense matrix

hipsparseSpMM_preprocess()#

hipsparseStatus_t hipsparseSpMM_preprocess(hipsparseHandle_t handle, hipsparseOperation_t opA, hipsparseOperation_t opB, const void *alpha, const hipsparseSpMatDescr_t matA, const hipsparseDnMatDescr_t matB, const void *beta, const hipsparseDnMatDescr_t matC, hipDataType computeType, hipsparseSpMMAlg_t alg, void *externalBuffer)#

Description: Preprocess step of the sparse matrix multiplication with a dense matrix.

hipsparseSpMM_preprocess performs the required preprocessing used when computing the sparse matrix multiplication with a dense matrix

hipsparseSpMM()#

hipsparseStatus_t hipsparseSpMM(hipsparseHandle_t handle, hipsparseOperation_t opA, hipsparseOperation_t opB, const void *alpha, const hipsparseSpMatDescr_t matA, const hipsparseDnMatDescr_t matB, const void *beta, const hipsparseDnMatDescr_t matC, hipDataType computeType, hipsparseSpMMAlg_t alg, void *externalBuffer)#

Description: Compute the sparse matrix multiplication with a dense matrix.

hipsparseSpMM computes sparse matrix multiplication with a dense matrix

hipsparseSpGEMM_createDescr()#

hipsparseStatus_t hipsparseSpGEMM_createDescr(hipsparseSpGEMMDescr_t *descr)#

Description: Create sparse matrix sparse matrix product descriptor.

hipsparseSpGEMM_createDescr creates a sparse matrix sparse matrix product descriptor. It should be destroyed at the end using hipsparseSpGEMM_destroyDescr().

hipsparseSpGEMM_destroyDescr()#

hipsparseStatus_t hipsparseSpGEMM_destroyDescr(hipsparseSpGEMMDescr_t descr)#

Description: Destroy sparse matrix sparse matrix product descriptor.

hipsparseSpGEMM_destroyDescr destroys a sparse matrix sparse matrix product descriptor and releases all resources used by the descriptor.

hipsparseSpGEMM_workEstimation()#

hipsparseStatus_t hipsparseSpGEMM_workEstimation(hipsparseHandle_t handle, hipsparseOperation_t opA, hipsparseOperation_t opB, const void *alpha, hipsparseSpMatDescr_t matA, hipsparseSpMatDescr_t matB, const void *beta, hipsparseSpMatDescr_t matC, hipDataType computeType, hipsparseSpGEMMAlg_t alg, hipsparseSpGEMMDescr_t spgemmDescr, size_t *bufferSize1, void *externalBuffer1)#: Description: Work estimation step of the sparse matrix sparse matrix product.

hipsparseSpGEMM_compute()#

hipsparseStatus_t hipsparseSpGEMM_compute(hipsparseHandle_t handle, hipsparseOperation_t opA, hipsparseOperation_t opB, const void *alpha, hipsparseSpMatDescr_t matA, hipsparseSpMatDescr_t matB, const void *beta, hipsparseSpMatDescr_t matC, hipDataType computeType, hipsparseSpGEMMAlg_t alg, hipsparseSpGEMMDescr_t spgemmDescr, size_t *bufferSize2, void *externalBuffer2)#: Description: Compute step of the sparse matrix sparse matrix product.

hipsparseSpGEMM_copy()#

hipsparseStatus_t hipsparseSpGEMM_copy(hipsparseHandle_t handle, hipsparseOperation_t opA, hipsparseOperation_t opB, const void *alpha, hipsparseSpMatDescr_t matA, hipsparseSpMatDescr_t matB, const void *beta, hipsparseSpMatDescr_t matC, hipDataType computeType, hipsparseSpGEMMAlg_t alg, hipsparseSpGEMMDescr_t spgemmDescr)#

hipsparseSDDMM_bufferSize()#

hipsparseStatus_t hipsparseSDDMM_bufferSize(hipsparseHandle_t handle, hipsparseOperation_t opA, hipsparseOperation_t opB, const void *alpha, const hipsparseDnMatDescr_t A, const hipsparseDnMatDescr_t B, const void *beta, hipsparseSpMatDescr_t C, hipDataType computeType, hipsparseSDDMMAlg_t alg, size_t *bufferSize)#

Description: Calculate the buffer size required for the sampled dense dense matrix multiplication.

hipsparseSDDMM_bufferSize computes the required user allocated buffer size needed when computing the sampled dense dense matrix multiplication

hipsparseSDDMM_preprocess()#

hipsparseStatus_t hipsparseSDDMM_preprocess(hipsparseHandle_t handle, hipsparseOperation_t opA, hipsparseOperation_t opB, const void *alpha, const hipsparseDnMatDescr_t A, const hipsparseDnMatDescr_t B, const void *beta, hipsparseSpMatDescr_t C, hipDataType computeType, hipsparseSDDMMAlg_t alg, void *tempBuffer)#

Description: Preprocess step of the sampled dense dense matrix multiplication.

hipsparseSDDMM_preprocess performs the required preprocessing used when computing the sampled dense dense matrix multiplication

hipsparseSDDMM()#

hipsparseStatus_t hipsparseSDDMM(hipsparseHandle_t handle, hipsparseOperation_t opA, hipsparseOperation_t opB, const void *alpha, const hipsparseDnMatDescr_t A, const hipsparseDnMatDescr_t B, const void *beta, hipsparseSpMatDescr_t C, hipDataType computeType, hipsparseSDDMMAlg_t alg, void *tempBuffer)#

Description: Sampled Dense-Dense Matrix Multiplication.

hipsparseSDDMM multiplies the scalar $α$ with the dense $m \times k$ matrix $A$ , the dense $k \times n$ matrix $B$ , filtered by the sparsity pattern of the $m \times n$ sparse matrix $C$ and adds the result to $C$ scaled by $β$ . The final result is stored in the sparse $m \times n$ matrix $C$ , such that

C := α (o p A (A) \cdot o p B (B)) \cdot s p y (C) + β C,

with

\begin{array}{r} o p (A) = {\begin{cases} A, & if opA == HIPSPARSE_OPERATION_NON_TRANSPOSE \\ A^{T}, & if opA == HIPSPARSE_OPERATION_TRANSPOSE \end{cases} \end{array}

,

\begin{array}{r} o p (B) = {\begin{cases} B, & if opB == HIPSPARSE_OPERATION_NON_TRANSPOSE \\ B^{T}, & if opB == HIPSPARSE_OPERATION_TRANSPOSE \end{cases} \end{array}

and

\begin{array}{r} s p y (C)_{i} j = {\begin{cases} 1 if i == j, & 0 if i != j \end{cases} \end{array}

hipsparseSpSV_createDescr()#

hipsparseStatus_t hipsparseSpSV_createDescr(hipsparseSpSVDescr_t *descr)#

Description: Create sparse matrix triangular solve descriptor.

hipsparseSpGEMM_createDescr creates a sparse matrix triangular solve descriptor. It should be destroyed at the end using hipsparseSpSV_destroyDescr().

hipsparseSpSV_destroyDescr()#

hipsparseStatus_t hipsparseSpSV_destroyDescr(hipsparseSpSVDescr_t descr)#

Description: Destroy sparse matrix triangular solve descriptor.

hipsparseSpSV_destroyDescr destroys a sparse matrix triangular solve descriptor and releases all resources used by the descriptor.

hipsparseSpSV_bufferSize()#

hipsparseStatus_t hipsparseSpSV_bufferSize(hipsparseHandle_t handle, hipsparseOperation_t opA, const void *alpha, const hipsparseSpMatDescr_t matA, const hipsparseDnVecDescr_t x, const hipsparseDnVecDescr_t y, hipDataType computeType, hipsparseSpSVAlg_t alg, hipsparseSpSVDescr_t spsvDescr, size_t *bufferSize)#

Description: Buffer size step of solution of triangular linear system op(A) * Y = alpha * X, where A is a sparse matrix in CSR storage format, x and Y are dense vectors.

hipsparseSpSV_bufferSize computes the required user allocated buffer size needed when computing the solution of triangular linear system op(A) * Y = alpha * X, where A is a sparse matrix in CSR storage format, x and Y are dense vectors.

hipsparseSpSV_analysis()#

hipsparseStatus_t hipsparseSpSV_analysis(hipsparseHandle_t handle, hipsparseOperation_t opA, const void *alpha, const hipsparseSpMatDescr_t matA, const hipsparseDnVecDescr_t x, const hipsparseDnVecDescr_t y, hipDataType computeType, hipsparseSpSVAlg_t alg, hipsparseSpSVDescr_t spsvDescr, void *externalBuffer)#

Description: Analysis step of solution of triangular linear system op(A) * Y = alpha * X, where A is a sparse matrix in CSR storage format, x and Y are dense vectors.

hipsparseSpSV_analysis performs the required analysis used when computing the solution of triangular linear system op(A) * Y = alpha * X, where A is a sparse matrix in CSR storage format, x and Y are dense vectors.

hipsparseSpSV_solve()#

hipsparseStatus_t hipsparseSpSV_solve(hipsparseHandle_t handle, hipsparseOperation_t opA, const void *alpha, const hipsparseSpMatDescr_t matA, const hipsparseDnVecDescr_t x, const hipsparseDnVecDescr_t y, hipDataType computeType, hipsparseSpSVAlg_t alg, hipsparseSpSVDescr_t spsvDescr)#

Description: Sparse triangular solve.

hipsparseSpSV_solve solves a sparse triangular linear system of a sparse $m \times m$ matrix, defined in CSR or COO storage format, a dense solution vector $y$ and the right-hand side $x$ that is multiplied by $α$ , such that

o p (A) \cdot y = α \cdot x,

with

\begin{array}{r} o p (A) = {\begin{cases} A, & if trans == HIPSPARSE_OPERATION_NON_TRANSPOSE \\ A^{T}, & if trans == HIPSPARSE_OPERATION_TRANSPOSE \\ A^{H}, & if trans == HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE \end{cases} \end{array}

hipsparseSpSM_createDescr()#

hipsparseStatus_t hipsparseSpSM_createDescr(hipsparseSpSMDescr_t *descr)#

Description: Create sparse matrix triangular solve with multiple rhs descriptor.

hipsparseSpSM_createDescr creates a sparse matrix triangular solve with multiple rhs descriptor. It should be destroyed at the end using hipsparseSpSM_destroyDescr().

hipsparseSpSM_destroyDescr()#

hipsparseStatus_t hipsparseSpSM_destroyDescr(hipsparseSpSMDescr_t descr)#

Description: Destroy sparse matrix triangular solve with multiple rhs descriptor.

hipsparseSpSM_destroyDescr destroys a sparse matrix triangular solve with multiple rhs descriptor and releases all resources used by the descriptor.

hipsparseSpSM_bufferSize()#

hipsparseStatus_t hipsparseSpSM_bufferSize(hipsparseHandle_t handle, hipsparseOperation_t opA, hipsparseOperation_t opB, const void *alpha, const hipsparseSpMatDescr_t matA, const hipsparseDnMatDescr_t matB, const hipsparseDnMatDescr_t matC, hipDataType computeType, hipsparseSpSMAlg_t alg, hipsparseSpSMDescr_t spsmDescr, size_t *bufferSize)#

Description: Buffer size step of solution of triangular linear system op(A) * C = alpha * op(B), where A is a sparse matrix in CSR storage format, B and C are dense matrices.

hipsparseSpSV_bufferSize computes the required user allocated buffer size needed when computing the solution of triangular linear system op(A) * C = alpha * op(B), where A is a sparse matrix in CSR storage format, B and C are dense matrices.

hipsparseSpSM_analysis()#

hipsparseStatus_t hipsparseSpSM_analysis(hipsparseHandle_t handle, hipsparseOperation_t opA, hipsparseOperation_t opB, const void *alpha, const hipsparseSpMatDescr_t matA, const hipsparseDnMatDescr_t matB, const hipsparseDnMatDescr_t matC, hipDataType computeType, hipsparseSpSMAlg_t alg, hipsparseSpSMDescr_t spsmDescr, void *externalBuffer)#

Description: Analysis step of solution of triangular linear system op(A) * C = alpha * op(B), where A is a sparse matrix in CSR storage format, B and C are dense vectors.

hipsparseSpSV_analysis performs the required analysis used when computing the solution of triangular linear system op(A) * C = alpha * op(B), where A is a sparse matrix in CSR storage format, B and C are dense vectors.

hipsparseSpSM_solve()#

hipsparseStatus_t hipsparseSpSM_solve(hipsparseHandle_t handle, hipsparseOperation_t opA, hipsparseOperation_t opB, const void *alpha, const hipsparseSpMatDescr_t matA, const hipsparseDnMatDescr_t matB, const hipsparseDnMatDescr_t matC, hipDataType computeType, hipsparseSpSMAlg_t alg, hipsparseSpSMDescr_t spsmDescr, void *externalBuffer)#

Description: Sparse triangular system solve.

hipsparseSpSM_solve solves a sparse triangular linear system of a sparse $m \times m$ matrix, defined in CSR or COO storage format, a dense solution matrix $C$ and the right-hand side $B$ that is multiplied by $α$ , such that

o p (A) \cdot C = α \cdot o p (B),

with

\begin{array}{r} o p (A) = {\begin{cases} A, & if trans == HIPSPARSE_OPERATION_NON_TRANSPOSE \\ A^{T}, & if trans == HIPSPARSE_OPERATION_TRANSPOSE \\ A^{H}, & if trans == HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE \end{cases} \end{array}

and

\begin{array}{r} o p (B) = {\begin{cases} B, & if trans_B == HIPSPARSE_OPERATION_NON_TRANSPOSE \\ B^{T}, & if trans_B == HIPSPARSE_OPERATION_TRANSPOSE \\ B^{H}, & if trans_B == HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE \end{cases} \end{array}

Sparse Generic Functions

Contents

Sparse Generic Functions#

hipsparseAxpby()#

hipsparseGather()#

hipsparseScatter()#

hipsparseRot()#

hipsparseSparseToDense_bufferSize()#

hipsparseSparseToDense()#

hipsparseDenseToSparse_bufferSize()#

hipsparseDenseToSparse_analysis()#

hipsparseDenseToSparse_convert()#

hipsparseSpVV_bufferSize()#

hipsparseSpVV()#

hipsparseSpMV_bufferSize()#

hipsparseSpMV()#

hipsparseSpMM_bufferSize()#

hipsparseSpMM_preprocess()#

hipsparseSpMM()#

hipsparseSpGEMM_createDescr()#

hipsparseSpGEMM_destroyDescr()#

hipsparseSpGEMM_workEstimation()#

hipsparseSpGEMM_compute()#

hipsparseSpGEMM_copy()#

hipsparseSDDMM_bufferSize()#

hipsparseSDDMM_preprocess()#

hipsparseSDDMM()#

hipsparseSpSV_createDescr()#

hipsparseSpSV_destroyDescr()#

hipsparseSpSV_bufferSize()#

hipsparseSpSV_analysis()#

hipsparseSpSV_solve()#

hipsparseSpSM_createDescr()#

hipsparseSpSM_destroyDescr()#

hipsparseSpSM_bufferSize()#

hipsparseSpSM_analysis()#

hipsparseSpSM_solve()#