Sparse Level 1 Functions

The sparse level 1 routines describe operations between a vector in sparse format and a vector in dense format. This section describes all hipSPARSE level 1 sparse linear algebra functions.

hipsparseXaxpyi()

hipsparseStatus_t hipsparseSaxpyi(hipsparseHandle_t handle, int nnz, const float *alpha, const float *xVal, const int *xInd, float *y, hipsparseIndexBase_t idxBase)

hipsparseStatus_t hipsparseDaxpyi(hipsparseHandle_t handle, int nnz, const double *alpha, const double *xVal, const int *xInd, double *y, hipsparseIndexBase_t idxBase)

hipsparseStatus_t hipsparseCaxpyi(hipsparseHandle_t handle, int nnz, const hipComplex *alpha, const hipComplex *xVal, const int *xInd, hipComplex *y, hipsparseIndexBase_t idxBase)

hipsparseStatus_t hipsparseZaxpyi(hipsparseHandle_t handle, int nnz, const hipDoubleComplex *alpha, const hipDoubleComplex *xVal, const int *xInd, hipDoubleComplex *y, hipsparseIndexBase_t idxBase)

Scale a sparse vector and add it to a dense vector.

hipsparseXaxpyi multiplies the sparse vector \(x\) with scalar \(\alpha\) and adds the result to the dense vector \(y\), such that

\[ y := y + \alpha \cdot x \]

for(i = 0; i < nnz; ++i)
{
    y[xInd[i]] = y[xInd[i]] + alpha * xVal[i];
}

Example

// Number of non-zeros of the sparse vector
int nnz = 3;

// Sparse index vector
int hxInd[3] = {0, 3, 5};

// Sparse value vector
double hxVal[3] = {1.0, 2.0, 3.0};

// Dense vector
double hy[9] = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};

// Scalar alpha
double alpha = 3.7;

// Index base
hipsparseIndexBase_t idxBase = HIPSPARSE_INDEX_BASE_ZERO;

// Offload data to device
int* dxInd;
double*        dxVal;
double*        dy;

hipMalloc((void**)&dxInd, sizeof(int) * nnz);
hipMalloc((void**)&dxVal, sizeof(double) * nnz);
hipMalloc((void**)&dy, sizeof(double) * 9);

hipMemcpy(dxInd, hxInd, sizeof(int) * nnz, hipMemcpyHostToDevice);
hipMemcpy(dxVal, hxVal, sizeof(double) * nnz, hipMemcpyHostToDevice);
hipMemcpy(dy, hy, sizeof(double) * 9, hipMemcpyHostToDevice);

// hipSPARSE handle
hipsparseHandle_t handle;
hipsparseCreate(&handle);

// Call daxpyi to perform y = y + alpha * x
hipsparseDaxpyi(handle, nnz, &alpha, dxVal, dxInd, dy, idxBase);

// Copy result back to host
hipMemcpy(hy, dy, sizeof(double) * 9, hipMemcpyDeviceToHost);

// Clear hipSPARSE 
hipsparseDestroy(handle);

// Clear device memory
hipFree(dxInd);
hipFree(dxVal);
hipFree(dy);

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

Parameters:

• handle – [in] handle to the hipsparse library context queue.

• nnz – [in] number of non-zero entries of vector \(x\).

• alpha – [in] scalar \(\alpha\).

• xVal – [in] array of nnz elements containing the values of \(x\).

• xInd – [in] array of nnz elements containing the indices of the non-zero values of \(x\).

• y – [inout] array of values in dense format.

• idxBase – [in] HIPSPARSE_INDEX_BASE_ZERO or HIPSPARSE_INDEX_BASE_ONE.

Return values:

• HIPSPARSE_STATUS_SUCCESS – the operation completed successfully.

• HIPSPARSE_STATUS_INVALID_VALUE – handle, idxBase, nnz, alpha, xVal, xInd or y is invalid.

hipsparseXdoti()

hipsparseStatus_t hipsparseSdoti(hipsparseHandle_t handle, int nnz, const float *xVal, const int *xInd, const float *y, float *result, hipsparseIndexBase_t idxBase)

hipsparseStatus_t hipsparseDdoti(hipsparseHandle_t handle, int nnz, const double *xVal, const int *xInd, const double *y, double *result, hipsparseIndexBase_t idxBase)

hipsparseStatus_t hipsparseCdoti(hipsparseHandle_t handle, int nnz, const hipComplex *xVal, const int *xInd, const hipComplex *y, hipComplex *result, hipsparseIndexBase_t idxBase)

hipsparseStatus_t hipsparseZdoti(hipsparseHandle_t handle, int nnz, const hipDoubleComplex *xVal, const int *xInd, const hipDoubleComplex *y, hipDoubleComplex *result, hipsparseIndexBase_t idxBase)

Compute the dot product of a sparse vector with a dense vector.

hipsparseXdoti computes the dot product of the sparse vector \(x\) with the dense vector \(y\), such that

\[ result := y^T x \]

result = 0
for(i = 0; i < nnz; ++i)
{
    result += xVal[i] * y[xInd[i]];
}

Example

// Number of non-zeros of the sparse vector
int nnz = 3;

// Sparse index vector
int hxInd[3] = {0, 3, 5};

// Sparse value vector
float hxVal[3] = {1.0f, 2.0f, 3.0f};

// Dense vector
float hy[9] = {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f};

// Index base
hipsparseIndexBase_t idxBase = HIPSPARSE_INDEX_BASE_ZERO;

// Offload data to device
int* dxInd;
float*        dxVal;
float*        dy;

hipMalloc((void**)&dxInd, sizeof(int) * nnz);
hipMalloc((void**)&dxVal, sizeof(float) * nnz);
hipMalloc((void**)&dy, sizeof(float) * 9);

hipMemcpy(dxInd, hxInd, sizeof(int) * nnz, hipMemcpyHostToDevice);
hipMemcpy(dxVal, hxVal, sizeof(float) * nnz, hipMemcpyHostToDevice);
hipMemcpy(dy, hy, sizeof(float) * 9, hipMemcpyHostToDevice);

// hipSPARSE handle
hipsparseHandle_t handle;
hipsparseCreate(&handle);

// Call sdoti to compute the dot product
float dot;
hipsparseSdoti(handle, nnz, dxVal, dxInd, dy, &dot, idxBase);

// Clear hipSPARSE
hipsparseDestroy(handle);

// Clear device memory
hipFree(dxInd);
hipFree(dxVal);
hipFree(dy);

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

Parameters:

• handle – [in] handle to the hipsparse library context queue.

• nnz – [in] number of non-zero entries of vector \(x\).

• xVal – [in] array of nnz values.

• xInd – [in] array of nnz elements containing the indices of the non-zero values of \(x\).

• y – [in] array of values in dense format.

• result – [out] pointer to the result, can be host or device memory

• idxBase – [in] HIPSPARSE_INDEX_BASE_ZERO or HIPSPARSE_INDEX_BASE_ONE.

Return values:

• HIPSPARSE_STATUS_SUCCESS – the operation completed successfully.

• HIPSPARSE_STATUS_INVALID_VALUE – handle, idxBase, nnz, xVal, xInd, y or result is invalid.

• HIPSPARSE_STATUS_ALLOC_FAILED – the buffer for the dot product reduction could not be allocated.

• HIPSPARSE_STATUS_INTERNAL_ERROR – an internal error occurred.

hipsparseXdotci()

hipsparseStatus_t hipsparseCdotci(hipsparseHandle_t handle, int nnz, const hipComplex *xVal, const int *xInd, const hipComplex *y, hipComplex *result, hipsparseIndexBase_t idxBase)

hipsparseStatus_t hipsparseZdotci(hipsparseHandle_t handle, int nnz, const hipDoubleComplex *xVal, const int *xInd, const hipDoubleComplex *y, hipDoubleComplex *result, hipsparseIndexBase_t idxBase)

Compute the dot product of a complex conjugate sparse vector with a dense vector.

hipsparseXdotci computes the dot product of the complex conjugate sparse vector \(x\) with the dense vector \(y\), such that

\[ result := \bar{x}^H y \]

result = 0
for(i = 0; i < nnz; ++i)
{
    result += conj(xVal[i]) * y[xInd[i]];
}

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

Parameters:

• handle – [in] handle to the hipsparse library context queue.

• nnz – [in] number of non-zero entries of vector \(x\).

• xVal – [in] array of nnz values.

• xInd – [in] array of nnz elements containing the indices of the non-zero values of \(x\).

• y – [in] array of values in dense format.

• result – [out] pointer to the result, can be host or device memory

• idxBase – [in] HIPSPARSE_INDEX_BASE_ZERO or HIPSPARSE_INDEX_BASE_ONE.

Return values:

• HIPSPARSE_STATUS_SUCCESS – the operation completed successfully.

• HIPSPARSE_STATUS_INVALID_VALUE – handle, idxBase, nnz, xVal, xInd, y or result is invalid.

• HIPSPARSE_STATUS_ALLOC_FAILED – the buffer for the dot product reduction could not be allocated.

• HIPSPARSE_STATUS_INTERNAL_ERROR – an internal error occurred.

hipsparseXgthr()

hipsparseStatus_t hipsparseSgthr(hipsparseHandle_t handle, int nnz, const float *y, float *xVal, const int *xInd, hipsparseIndexBase_t idxBase)

hipsparseStatus_t hipsparseDgthr(hipsparseHandle_t handle, int nnz, const double *y, double *xVal, const int *xInd, hipsparseIndexBase_t idxBase)

hipsparseStatus_t hipsparseCgthr(hipsparseHandle_t handle, int nnz, const hipComplex *y, hipComplex *xVal, const int *xInd, hipsparseIndexBase_t idxBase)

hipsparseStatus_t hipsparseZgthr(hipsparseHandle_t handle, int nnz, const hipDoubleComplex *y, hipDoubleComplex *xVal, const int *xInd, hipsparseIndexBase_t idxBase)

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

hipsparseXgthr gathers the elements that are listed in xInd from the dense vector \(y\) and stores them in the sparse vector \(x\).

for(i = 0; i < nnz; ++i)
{
    xVal[i] = y[xInd[i]];
}

Example

// Number of non-zeros of the sparse vector
int nnz = 3;

// Sparse index vector
int hxInd[3] = {0, 3, 5};

// Sparse value vector
float hxVal[3];

// Dense vector
float hy[9] = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};

// Index base
hipsparseIndexBase_t idxBase = HIPSPARSE_INDEX_BASE_ZERO;

// Offload data to device
int* dxInd;
float*         dxVal;
float*         dy;

hipMalloc((void**)&dxInd, sizeof(int) * nnz);
hipMalloc((void**)&dxVal, sizeof(float) * nnz);
hipMalloc((void**)&dy, sizeof(float) * 9);

hipMemcpy(dxInd, hxInd, sizeof(int) * nnz, hipMemcpyHostToDevice);
hipMemcpy(dy, hy, sizeof(float) * 9, hipMemcpyHostToDevice);

// hipSPARSE handle
hipsparseHandle_t handle;
hipsparseCreate(&handle);

// Call sgthr
hipsparseSgthr(handle, nnz, dy, dxVal, dxInd, idxBase);

// Copy result back to host
hipMemcpy(hxVal, dxVal, sizeof(float) * nnz, hipMemcpyDeviceToHost);

// Clear hipSPARSE
hipsparseDestroy(handle);

// Clear device memory
hipFree(dxInd);
hipFree(dxVal);
hipFree(dy);

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

Parameters:

• handle – [in] handle to the hipsparse library context queue.

• nnz – [in] number of non-zero entries of \(x\).

• y – [in] array of values in dense format.

• xVal – [out] array of nnz elements containing the values of \(x\).

• xInd – [in] array of nnz elements containing the indices of the non-zero values of \(x\).

• idxBase – [in] HIPSPARSE_INDEX_BASE_ZERO or HIPSPARSE_INDEX_BASE_ONE.

Return values:

• HIPSPARSE_STATUS_SUCCESS – the operation completed successfully.

• HIPSPARSE_STATUS_INVALID_VALUE – handle, idxBase, nnz, y, xVal or xInd is invalid.

hipsparseXgthrz()

hipsparseStatus_t hipsparseSgthrz(hipsparseHandle_t handle, int nnz, float *y, float *xVal, const int *xInd, hipsparseIndexBase_t idxBase)

hipsparseStatus_t hipsparseDgthrz(hipsparseHandle_t handle, int nnz, double *y, double *xVal, const int *xInd, hipsparseIndexBase_t idxBase)

hipsparseStatus_t hipsparseCgthrz(hipsparseHandle_t handle, int nnz, hipComplex *y, hipComplex *xVal, const int *xInd, hipsparseIndexBase_t idxBase)

hipsparseStatus_t hipsparseZgthrz(hipsparseHandle_t handle, int nnz, hipDoubleComplex *y, hipDoubleComplex *xVal, const int *xInd, hipsparseIndexBase_t idxBase)

Gather and zero out elements from a dense vector and store them into a sparse vector.

hipsparseXgthrz gathers the elements that are listed in xInd from the dense vector \(y\) and stores them in the sparse vector \(x\). The gathered elements in \(y\) are replaced by zero.

for(i = 0; i < nnz; ++i)
{
    xVal[i]    = y[xInd[i]];
    y[xInd[i]] = 0;
}

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

Parameters:

• handle – [in] handle to the hipsparse library context queue.

• nnz – [in] number of non-zero entries of \(x\).

• y – [inout] array of values in dense format.

• xVal – [out] array of nnz elements containing the non-zero values of \(x\).

• xInd – [in] array of nnz elements containing the indices of the non-zero values of \(x\).

• idxBase – [in] HIPSPARSE_INDEX_BASE_ZERO or HIPSPARSE_INDEX_BASE_ONE.

Return values:

• HIPSPARSE_STATUS_SUCCESS – the operation completed successfully.

• HIPSPARSE_STATUS_INVALID_VALUE – handle, idxBase, nnz, y, xVal or xInd is invalid.

hipsparseXroti()

hipsparseStatus_t hipsparseSroti(hipsparseHandle_t handle, int nnz, float *xVal, const int *xInd, float *y, const float *c, const float *s, hipsparseIndexBase_t idxBase)

hipsparseStatus_t hipsparseDroti(hipsparseHandle_t handle, int nnz, double *xVal, const int *xInd, double *y, const double *c, const double *s, hipsparseIndexBase_t idxBase)

Apply Givens rotation to a dense and a sparse vector.

hipsparseXroti applies the Givens rotation matrix \(G\) to the sparse vector \(x\) and the dense vector \(y\), where

\[\begin{split} G = \begin{pmatrix} c & s \\ -s & c \end{pmatrix} \end{split}\]

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

    xVal[i]    = c * x_tmp + s * y_tmp;
    y[xInd[i]] = c * y_tmp - s * x_tmp;
}

Example

// Number of non-zeros of the sparse vector
int nnz = 3;

// Sparse index vector
int hxInd[3] = {0, 3, 5};

// Sparse value vector
float hxVal[3] = {1.0f, 2.0f, 3.0f};

// Dense vector
float hy[9] = {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f};

// c and s
float c = 3.7;
float s = 1.3;

// Index base
hipsparseIndexBase_t idxBase = HIPSPARSE_INDEX_BASE_ZERO;

// Offload data to device
int* dxInd;
float*        dxVal;
float*        dy;

hipMalloc((void**)&dxInd, sizeof(int) * nnz);
hipMalloc((void**)&dxVal, sizeof(float) * nnz);
hipMalloc((void**)&dy, sizeof(float) * 9);

hipMemcpy(dxInd, hxInd, sizeof(int) * nnz, hipMemcpyHostToDevice);
hipMemcpy(dxVal, hxVal, sizeof(float) * nnz, hipMemcpyHostToDevice);
hipMemcpy(dy, hy, sizeof(float) * 9, hipMemcpyHostToDevice);

// hipSPARSE handle
hipsparseHandle_t handle;
hipsparseCreate(&handle);

// Call sroti
hipsparseSroti(handle, nnz, dxVal, dxInd, dy, &c, &s, idxBase);

// Copy result back to host
hipMemcpy(hxVal, dxVal, sizeof(float) * nnz, hipMemcpyDeviceToHost);
hipMemcpy(hy, dy, sizeof(float) * 9, hipMemcpyDeviceToHost);

// Clear hipSPARSE
hipsparseDestroy(handle);

// Clear device memory
hipFree(dxInd);
hipFree(dxVal);
hipFree(dy);

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

Parameters:

• handle – [in] handle to the hipsparse library context queue.

• nnz – [in] number of non-zero entries of \(x\).

• xVal – [inout] array of nnz elements containing the non-zero values of \(x\).

• xInd – [in] array of nnz elements containing the indices of the non-zero values of \(x\).

• y – [inout] array of values in dense format.

• c – [in] pointer to the cosine element of \(G\), can be on host or device.

• s – [in] pointer to the sine element of \(G\), can be on host or device.

• idxBase – [in] HIPSPARSE_INDEX_BASE_ZERO or HIPSPARSE_INDEX_BASE_ONE.

Return values:

• HIPSPARSE_STATUS_SUCCESS – the operation completed successfully.

• HIPSPARSE_STATUS_INVALID_VALUE – handle, idxBase, nnz, c, s, xVal, xInd or y is invalid.

hipsparseXsctr()

hipsparseStatus_t hipsparseSsctr(hipsparseHandle_t handle, int nnz, const float *xVal, const int *xInd, float *y, hipsparseIndexBase_t idxBase)

hipsparseStatus_t hipsparseDsctr(hipsparseHandle_t handle, int nnz, const double *xVal, const int *xInd, double *y, hipsparseIndexBase_t idxBase)

hipsparseStatus_t hipsparseCsctr(hipsparseHandle_t handle, int nnz, const hipComplex *xVal, const int *xInd, hipComplex *y, hipsparseIndexBase_t idxBase)

hipsparseStatus_t hipsparseZsctr(hipsparseHandle_t handle, int nnz, const hipDoubleComplex *xVal, const int *xInd, hipDoubleComplex *y, hipsparseIndexBase_t idxBase)

Scatter elements from a dense vector across a sparse vector.

hipsparseXsctr scatters the elements that are listed in xInd from the sparse vector \(x\) into the dense vector \(y\). Indices of \(y\) that are not listed in xInd remain unchanged.

for(i = 0; i < nnz; ++i)
{
    y[xInd[i]] = xVal[i];
}

Example

// Number of non-zeros of the sparse vector
int nnz = 3;

// Sparse index vector
int hxInd[3] = {0, 3, 5};

// Sparse value vector
float hxVal[3] = {9.0, 2.0, 3.0};

// Dense vector
float hy[9] = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};

// Index base
hipsparseIndexBase_t idxBase = HIPSPARSE_INDEX_BASE_ZERO;

// Offload data to device
int* dxInd;
float*         dxVal;
float*         dy;

hipMalloc((void**)&dxInd, sizeof(int) * nnz);
hipMalloc((void**)&dxVal, sizeof(float) * nnz);
hipMalloc((void**)&dy, sizeof(float) * 9);

hipMemcpy(dxInd, hxInd, sizeof(int) * nnz, hipMemcpyHostToDevice);
hipMemcpy(dxVal, hxVal, sizeof(float) * nnz, hipMemcpyHostToDevice);
hipMemcpy(dy, hy, sizeof(float) * 9, hipMemcpyHostToDevice);

// hipSPARSE handle
hipsparseHandle_t handle;
hipsparseCreate(&handle);

// Call ssctr
hipsparseSsctr(handle, nnz, dxVal, dxInd, dy, idxBase);

// Copy result back to host
hipMemcpy(hy, dy, sizeof(float) * 9, hipMemcpyDeviceToHost);

// Clear hipSPARSE
hipsparseDestroy(handle);

// Clear device memory
hipFree(dxInd);
hipFree(dxVal);
hipFree(dy);

Note

This function is non blocking and executed asynchronously with respect to the host. It may return before the actual computation has finished.

Parameters:

• handle – [in] handle to the hipsparse library context queue.

• nnz – [in] number of non-zero entries of \(x\).

• xVal – [in] array of nnz elements containing the non-zero values of \(x\).

• xInd – [in] array of nnz elements containing the indices of the non-zero values of x.

• y – [inout] array of values in dense format.

• idxBase – [in] HIPSPARSE_INDEX_BASE_ZERO or HIPSPARSE_INDEX_BASE_ONE.

Return values:

• HIPSPARSE_STATUS_SUCCESS – the operation completed successfully.

• HIPSPARSE_STATUS_INVALID_VALUE – handle, idxBase, nnz, xVal, xInd or y is invalid.