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  3. Template Function Pennylane::LightningGPU::Util::SparseMV_cuSparse(const index_type *, const int64_t, const index_type *, const std::complex<Precision> *, const int64_t, CFP_t *, CFP_t *, DevTypeID, cudaStream_t, cusparseHandle_t)

Template Function Pennylane::LightningGPU::Util::SparseMV_cuSparse(const index_type *, const int64_t, const index_type *, const std::complex<Precision> *, const int64_t, CFP_t *, CFP_t *, DevTypeID, cudaStream_t, cusparseHandle_t)

Function Documentation

template<class index_type, class Precision, class CFP_t, class DevTypeID = int>
inline void Pennylane::LightningGPU::Util::SparseMV_cuSparse(const index_type *csrOffsets_ptr, const int64_t csrOffsets_size, const index_type *columns_ptr, const std::complex<Precision> *values_ptr, const int64_t numNNZ, CFP_t *X, CFP_t *Y, DevTypeID device_id, cudaStream_t stream_id, cusparseHandle_t handle)

Sparse matrix vector multiply offloaded to cuSparse (Y = alpha*SparseMat*X + beta)

Template Parameters

  • index_type – Integer type for offsets, indices and number of elements (std::size_t for the moment).

  • Precision – Floating data-type.

  • DevTypeID – Integer type of device id.

Parameters

  • csrOffsets_ptr – Pointer to offsets in CSR format.

  • csrOffsets_size – Number of elements of offsets.

  • columns_ptr – Pointer to column indices in CSR format.

  • values_ptr – Pointer to value of each non-zero elements in CSR format.

  • numNNZ – Number of non-zero elements.

  • X – Pointer to vector.

  • Y – Pointer to vector.

  • device_id – Device id.

  • cudaStream_t – Stream id.

  • handle – cuSparse handle.

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