apply_matrix_batched_get_workspace_size#

cuquantum.bindings.custatevec.apply_matrix_batched_get_workspace_size(
intptr_t handle,
int sv_data_type,
uint32_t n_index_bits,
uint32_t n_svs,
int64_t sv_stride,
int map_type,
matrix_indices,
intptr_t matrices,
int matrix_data_type,
int layout,
int32_t adjoint,
uint32_t n_matrices,
uint32_t n_targets,
uint32_t n_controls,
int compute_type,
) → size_t[source]#

This function gets the required workspace size for apply_matrix_batched().

Parameters:

  • handle (intptr_t) – the handle to the cuStateVec context.

  • sv_data_type (int) – Data type of the state vector.

  • n_index_bits (uint32_t) – the number of index bits of the state vector.

  • n_svs (uint32_t) – the number of state vectors.

  • sv_stride (int64_t) – distance of two consecutive state vectors.

  • map_type (MatrixMapType) – enumerator specifying the way to assign matrices.

  • matrix_indices (object) –

    pointer to a host or device array of matrix indices. It can be:

    • an int as the pointer address to the array, or

    • a Python sequence of int32_t.

  • matrices (intptr_t) – pointer to allocated matrices in one contiguous memory chunk on host or device.

  • matrix_data_type (int) – data type of matrix.

  • layout (MatrixLayout) – enumerator specifying the memory layout of matrix.

  • adjoint (int32_t) – apply adjoint of matrix.

  • n_matrices (uint32_t) – the number of matrices.

  • n_targets (uint32_t) – the number of target bits.

  • n_controls (uint32_t) – the number of control bits.

  • compute_type (ComputeType) – compute_type of matrix multiplication.

Returns:

workspace size.

Return type:

size_t

See also

custatevecApplyMatrixBatchedGetWorkspaceSize()