Library/ManagedCuda/CudaSolve/CudaSolveSparse.cs
/// <summary>
/// The batched sparse QR factorization is used to solve either a set of least-squares
/// problems or a set of linear systems
/// </summary>
/// <param name="m">number of rows of each matrix Aj.</param>
/// <param name="n">number of columns of each matrix Aj.</param>
/// <param name="nnzA">number of nonzeros of each matrix Aj. It is the size csrColIndA.</param>
/// <param name="descrA">the descriptor of matrix A. The supported matrix type is
/// CUSPARSE_MATRIX_TYPE_GENERAL. Also, the supported index bases are CUSPARSE_INDEX_BASE_ZERO and CUSPARSE_INDEX_BASE_ONE.</param>
/// <param name="csrRowPtrA">integer array of m+1 elements that contains the
/// start of every row and the end of the last row plus one.</param>
/// <param name="csrColIndA">integer array of nnzAcolumn indices of the nonzero elements of each matrix Aj.</param>
/// <param name="info">opaque structure for QR factorization.</param>
The batched sparse QR factorization is used to solve either a set of least-squares
problems or a set of linear systems
The batched sparse QR factorization is used to solve either a set of least - squares problems or a set of linear systems
public void CsrqrAnalysisBatched(int m, int n, int nnzA, CudaSparseMatrixDescriptor descrA, CudaDeviceVariable<int> csrRowPtrA, CudaDeviceVariable<int> csrColIndA, CsrQrInfo info)
		{
			res = CudaSolveNativeMethods.Sparse.cusolverSpXcsrqrAnalysisBatched(_handle, m, n, nnzA, descrA.Descriptor, csrRowPtrA.DevicePointer, csrColIndA.DevicePointer, info.Info);
			Debug.WriteLine(String.Format("{0:G}, {1}: {2}", DateTime.Now, "cusolverSpXcsrqrAnalysisBatched", res));
			if (res != cusolverStatus.Success) throw new CudaSolveException(res);
		}
public void CsrqrAnalysisBatched ( int m , int n , int nnzA , CudaSparseMatrixDescriptor descrA , CudaDeviceVariable < int > csrRowPtrA , CudaDeviceVariable < int > csrColIndA , CsrQrInfo info ) { res = CudaSolveNativeMethods . Sparse . cusolverSpXcsrqrAnalysisBatched ( _handle , m , n , nnzA , descrA . Descriptor , csrRowPtrA . DevicePointer , csrColIndA . DevicePointer , info . Info ) ; Debug . WriteLine ( String . Format ( " " , DateTime . Now , " " , res ) ) ; if ( res != cusolverStatus . Success ) throw new CudaSolveException ( res ) ; }
The batched sparse QR factorization is used to solve either a set of least-squares
problems or a set of linear systems
The batched sparse QR factorization is used to solve either a set of least - squares problems or a set of linear systems
m
int
number of rows of each matrix Aj.
number of rows of each matrix Aj .
n
int
number of columns of each matrix Aj.
number of columns of each matrix Aj .
nnzA
int
number of nonzeros of each matrix Aj. It is the size csrColIndA.
number of nonzeros of each matrix Aj . It is the size csrColIndA .
descrA
CudaSparseMatrixDescriptor
the descriptor of matrix A. The supported matrix type is
CUSPARSE_MATRIX_TYPE_GENERAL. Also, the supported index bases are CUSPARSE_INDEX_BASE_ZERO and CUSPARSE_INDEX_BASE_ONE.
the descriptor of matrix A . The supported matrix type is CUSPARSE_MATRIX_TYPE_GENERAL . Also the supported index bases are CUSPARSE_INDEX_BASE_ZERO and CUSPARSE_INDEX_BASE_ONE .
csrRowPtrA
CudaDeviceVariable<int>
integer array of m+1 elements that contains the
start of every row and the end of the last row plus one.
integer array of m + 1 elements that contains the start of every row and the end of the last row plus one .
csrColIndA
CudaDeviceVariable<int>
integer array of nnzAcolumn indices of the nonzero elements of each matrix Aj.
integer array of nnzAcolumn indices of the nonzero elements of each matrix Aj .
info
CsrQrInfo
opaque structure for QR factorization.
opaque structure for QR factorization .