Class CudaSolveSparse

CudaSolvSparse: The cuSolverSP library was mainly designed to a solve sparse linear system AxB and the least-squares problem x = argmin||A*z-b||

Inheritance

System.Object

CudaSolveSparse

Implements

System.IDisposable

Inherited Members

System.Object.Equals(System.Object)

System.Object.Equals(System.Object, System.Object)

System.Object.GetHashCode()

System.Object.GetType()

System.Object.MemberwiseClone()

System.Object.ReferenceEquals(System.Object, System.Object)

System.Object.ToString()

Namespace: ManagedCuda.CudaSolve

Assembly: CudaSolve.dll

Syntax

public class CudaSolveSparse : IDisposable

Constructors

CudaSolveSparse()

Create new sparse solve instance

Declaration

public CudaSolveSparse()

CudaSolveSparse(CudaStream)

Create new sparse solve instance using stream stream

Declaration

public CudaSolveSparse(CudaStream stream)

Parameters

Type	Name	Description
CudaStream	stream

Methods

CsreigsHost(Int32, Int32, CudaSparseMatrixDescriptor, cuDoubleComplex[], Int32[], Int32[], cuDoubleComplex, cuDoubleComplex, ref Int32)

Declaration

public void CsreigsHost(int m, int nnz, CudaSparseMatrixDescriptor descrA, cuDoubleComplex[] csrValA, int[] csrRowPtrA, int[] csrColIndA, cuDoubleComplex left_bottom_corner, cuDoubleComplex right_upper_corner, ref int num_eigs)

Parameters

Type	Name	Description
System.Int32	m
System.Int32	nnz
CudaSparseMatrixDescriptor	descrA
cuDoubleComplex[]	csrValA
System.Int32[]	csrRowPtrA
System.Int32[]	csrColIndA
cuDoubleComplex	left_bottom_corner
cuDoubleComplex	right_upper_corner
System.Int32	num_eigs

CsreigsHost(Int32, Int32, CudaSparseMatrixDescriptor, cuFloatComplex[], Int32[], Int32[], cuFloatComplex, cuFloatComplex, ref Int32)

Declaration

public void CsreigsHost(int m, int nnz, CudaSparseMatrixDescriptor descrA, cuFloatComplex[] csrValA, int[] csrRowPtrA, int[] csrColIndA, cuFloatComplex left_bottom_corner, cuFloatComplex right_upper_corner, ref int num_eigs)

Parameters

Type	Name	Description
System.Int32	m
System.Int32	nnz
CudaSparseMatrixDescriptor	descrA
cuFloatComplex[]	csrValA
System.Int32[]	csrRowPtrA
System.Int32[]	csrColIndA
cuFloatComplex	left_bottom_corner
cuFloatComplex	right_upper_corner
System.Int32	num_eigs

CsreigsHost(Int32, Int32, CudaSparseMatrixDescriptor, Double[], Int32[], Int32[], cuDoubleComplex, cuDoubleComplex, ref Int32)

Declaration

public void CsreigsHost(int m, int nnz, CudaSparseMatrixDescriptor descrA, double[] csrValA, int[] csrRowPtrA, int[] csrColIndA, cuDoubleComplex left_bottom_corner, cuDoubleComplex right_upper_corner, ref int num_eigs)

Parameters

Type	Name	Description
System.Int32	m
System.Int32	nnz
CudaSparseMatrixDescriptor	descrA
System.Double[]	csrValA
System.Int32[]	csrRowPtrA
System.Int32[]	csrColIndA
cuDoubleComplex	left_bottom_corner
cuDoubleComplex	right_upper_corner
System.Int32	num_eigs

CsreigsHost(Int32, Int32, CudaSparseMatrixDescriptor, Single[], Int32[], Int32[], cuFloatComplex, cuFloatComplex, ref Int32)

Declaration

public void CsreigsHost(int m, int nnz, CudaSparseMatrixDescriptor descrA, float[] csrValA, int[] csrRowPtrA, int[] csrColIndA, cuFloatComplex left_bottom_corner, cuFloatComplex right_upper_corner, ref int num_eigs)

Parameters

Type	Name	Description
System.Int32	m
System.Int32	nnz
CudaSparseMatrixDescriptor	descrA
System.Single[]	csrValA
System.Int32[]	csrRowPtrA
System.Int32[]	csrColIndA
cuFloatComplex	left_bottom_corner
cuFloatComplex	right_upper_corner
System.Int32	num_eigs

Csreigvsi(Int32, Int32, CudaSparseMatrixDescriptor, CudaDeviceVariable<cuDoubleComplex>, CudaDeviceVariable<Int32>, CudaDeviceVariable<Int32>, cuDoubleComplex, CudaDeviceVariable<cuDoubleComplex>, Int32, Double, ref cuDoubleComplex, CudaDeviceVariable<cuDoubleComplex>)

This function solves the simple eigenvalue problem Ax=lambdax by shift-inverse method.

Declaration

public void Csreigvsi(int m, int nnz, CudaSparseMatrixDescriptor descrA, CudaDeviceVariable<cuDoubleComplex> csrValA, CudaDeviceVariable<int> csrRowPtrA, CudaDeviceVariable<int> csrColIndA, cuDoubleComplex mu0, CudaDeviceVariable<cuDoubleComplex> x0, int maxite, double tol, ref cuDoubleComplex mu, CudaDeviceVariable<cuDoubleComplex> x)

Parameters

Type	Name	Description
System.Int32	m	number of rows and columns of matrix A.
System.Int32	nnz	number of nonzeros of matrix A.
CudaSparseMatrixDescriptor	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.
CudaDeviceVariable<cuDoubleComplex>	csrValA	array of nnz (= csrRowPtrA(n) * csrRowPtrA(0)) nonzero elements of matrix A.
CudaDeviceVariable<System.Int32>	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
CudaDeviceVariable<System.Int32>	csrColIndA	integer array of nnz (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
cuDoubleComplex	mu0	initial guess of eigenvalue.
CudaDeviceVariable<cuDoubleComplex>	x0	initial guess of eigenvector, a vecotr of size m.
System.Int32	maxite	maximum iterations in shift-inverse method.
System.Double	tol	tolerance for convergence.
cuDoubleComplex	mu	approximated eigenvalue nearest mu0 under tolerance.
CudaDeviceVariable<cuDoubleComplex>	x	approximated eigenvector of size m.

Csreigvsi(Int32, Int32, CudaSparseMatrixDescriptor, CudaDeviceVariable<cuFloatComplex>, CudaDeviceVariable<Int32>, CudaDeviceVariable<Int32>, cuFloatComplex, CudaDeviceVariable<cuFloatComplex>, Int32, Single, ref cuFloatComplex, CudaDeviceVariable<cuFloatComplex>)

This function solves the simple eigenvalue problem Ax=lambdax by shift-inverse method.

Declaration

public void Csreigvsi(int m, int nnz, CudaSparseMatrixDescriptor descrA, CudaDeviceVariable<cuFloatComplex> csrValA, CudaDeviceVariable<int> csrRowPtrA, CudaDeviceVariable<int> csrColIndA, cuFloatComplex mu0, CudaDeviceVariable<cuFloatComplex> x0, int maxite, float tol, ref cuFloatComplex mu, CudaDeviceVariable<cuFloatComplex> x)

Parameters

Type	Name	Description
System.Int32	m	number of rows and columns of matrix A.
System.Int32	nnz	number of nonzeros of matrix A.
CudaSparseMatrixDescriptor	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.
CudaDeviceVariable<cuFloatComplex>	csrValA	array of nnz (= csrRowPtrA(n) * csrRowPtrA(0)) nonzero elements of matrix A.
CudaDeviceVariable<System.Int32>	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
CudaDeviceVariable<System.Int32>	csrColIndA	integer array of nnz (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
cuFloatComplex	mu0	initial guess of eigenvalue.
CudaDeviceVariable<cuFloatComplex>	x0	initial guess of eigenvector, a vecotr of size m.
System.Int32	maxite	maximum iterations in shift-inverse method.
System.Single	tol	tolerance for convergence.
cuFloatComplex	mu	approximated eigenvalue nearest mu0 under tolerance.
CudaDeviceVariable<cuFloatComplex>	x	approximated eigenvector of size m.

Csreigvsi(Int32, Int32, CudaSparseMatrixDescriptor, CudaDeviceVariable<Double>, CudaDeviceVariable<Int32>, CudaDeviceVariable<Int32>, Double, CudaDeviceVariable<Double>, Int32, Double, ref Double, CudaDeviceVariable<Double>)

This function solves the simple eigenvalue problem Ax=lambdax by shift-inverse method.

Declaration

public void Csreigvsi(int m, int nnz, CudaSparseMatrixDescriptor descrA, CudaDeviceVariable<double> csrValA, CudaDeviceVariable<int> csrRowPtrA, CudaDeviceVariable<int> csrColIndA, double mu0, CudaDeviceVariable<double> x0, int maxite, double tol, ref double mu, CudaDeviceVariable<double> x)

Parameters

Type	Name	Description
System.Int32	m	number of rows and columns of matrix A.
System.Int32	nnz	number of nonzeros of matrix A.
CudaSparseMatrixDescriptor	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.
CudaDeviceVariable<System.Double>	csrValA	array of nnz (= csrRowPtrA(n) * csrRowPtrA(0)) nonzero elements of matrix A.
CudaDeviceVariable<System.Int32>	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
CudaDeviceVariable<System.Int32>	csrColIndA	integer array of nnz (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
System.Double	mu0	initial guess of eigenvalue.
CudaDeviceVariable<System.Double>	x0	initial guess of eigenvector, a vecotr of size m.
System.Int32	maxite	maximum iterations in shift-inverse method.
System.Double	tol	tolerance for convergence.
System.Double	mu	approximated eigenvalue nearest mu0 under tolerance.
CudaDeviceVariable<System.Double>	x	approximated eigenvector of size m.

Csreigvsi(Int32, Int32, CudaSparseMatrixDescriptor, CudaDeviceVariable<Single>, CudaDeviceVariable<Int32>, CudaDeviceVariable<Int32>, Single, CudaDeviceVariable<Single>, Int32, Single, ref Single, CudaDeviceVariable<Single>)

This function solves the simple eigenvalue problem Ax=lambdax by shift-inverse method.

Declaration

public void Csreigvsi(int m, int nnz, CudaSparseMatrixDescriptor descrA, CudaDeviceVariable<float> csrValA, CudaDeviceVariable<int> csrRowPtrA, CudaDeviceVariable<int> csrColIndA, float mu0, CudaDeviceVariable<float> x0, int maxite, float tol, ref float mu, CudaDeviceVariable<float> x)

Parameters

Type	Name	Description
System.Int32	m	number of rows and columns of matrix A.
System.Int32	nnz	number of nonzeros of matrix A.
CudaSparseMatrixDescriptor	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.
CudaDeviceVariable<System.Single>	csrValA	array of nnz (= csrRowPtrA(n) * csrRowPtrA(0)) nonzero elements of matrix A.
CudaDeviceVariable<System.Int32>	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
CudaDeviceVariable<System.Int32>	csrColIndA	integer array of nnz (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
System.Single	mu0	initial guess of eigenvalue.
CudaDeviceVariable<System.Single>	x0	initial guess of eigenvector, a vecotr of size m.
System.Int32	maxite	maximum iterations in shift-inverse method.
System.Single	tol	tolerance for convergence.
System.Single	mu	approximated eigenvalue nearest mu0 under tolerance.
CudaDeviceVariable<System.Single>	x	approximated eigenvector of size m.

CsreigvsiHost(Int32, Int32, CudaSparseMatrixDescriptor, cuDoubleComplex[], Int32[], Int32[], cuDoubleComplex, cuDoubleComplex[], Int32, Double, ref cuDoubleComplex, cuDoubleComplex[])

This function solves the simple eigenvalue problem Ax=lambdax by shift-inverse method.

Declaration

public void CsreigvsiHost(int m, int nnz, CudaSparseMatrixDescriptor descrA, cuDoubleComplex[] csrValA, int[] csrRowPtrA, int[] csrColIndA, cuDoubleComplex mu0, cuDoubleComplex[] x0, int maxite, double tol, ref cuDoubleComplex mu, cuDoubleComplex[] x)

Parameters

Type	Name	Description
System.Int32	m	number of rows and columns of matrix A.
System.Int32	nnz	number of nonzeros of matrix A.
CudaSparseMatrixDescriptor	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.
cuDoubleComplex[]	csrValA	array of nnz (= csrRowPtrA(n) * csrRowPtrA(0)) nonzero elements of matrix A.
System.Int32[]	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
System.Int32[]	csrColIndA	integer array of nnz (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
cuDoubleComplex	mu0	initial guess of eigenvalue.
cuDoubleComplex[]	x0	initial guess of eigenvector, a vecotr of size m.
System.Int32	maxite	maximum iterations in shift-inverse method.
System.Double	tol	tolerance for convergence.
cuDoubleComplex	mu	approximated eigenvalue nearest mu0 under tolerance.
cuDoubleComplex[]	x	approximated eigenvector of size m.

CsreigvsiHost(Int32, Int32, CudaSparseMatrixDescriptor, cuFloatComplex[], Int32[], Int32[], cuFloatComplex, cuFloatComplex[], Int32, Single, ref cuFloatComplex, cuFloatComplex[])

This function solves the simple eigenvalue problem Ax=lambdax by shift-inverse method.

Declaration

public void CsreigvsiHost(int m, int nnz, CudaSparseMatrixDescriptor descrA, cuFloatComplex[] csrValA, int[] csrRowPtrA, int[] csrColIndA, cuFloatComplex mu0, cuFloatComplex[] x0, int maxite, float tol, ref cuFloatComplex mu, cuFloatComplex[] x)

Parameters

Type	Name	Description
System.Int32	m	number of rows and columns of matrix A.
System.Int32	nnz	number of nonzeros of matrix A.
CudaSparseMatrixDescriptor	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.
cuFloatComplex[]	csrValA	array of nnz (= csrRowPtrA(n) * csrRowPtrA(0)) nonzero elements of matrix A.
System.Int32[]	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
System.Int32[]	csrColIndA	integer array of nnz (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
cuFloatComplex	mu0	initial guess of eigenvalue.
cuFloatComplex[]	x0	initial guess of eigenvector, a vecotr of size m.
System.Int32	maxite	maximum iterations in shift-inverse method.
System.Single	tol	tolerance for convergence.
cuFloatComplex	mu	approximated eigenvalue nearest mu0 under tolerance.
cuFloatComplex[]	x	approximated eigenvector of size m.

CsreigvsiHost(Int32, Int32, CudaSparseMatrixDescriptor, Double[], Int32[], Int32[], Double, Double[], Int32, Double, ref Double, Double[])

This function solves the simple eigenvalue problem Ax=lambdax by shift-inverse method.

Declaration

public void CsreigvsiHost(int m, int nnz, CudaSparseMatrixDescriptor descrA, double[] csrValA, int[] csrRowPtrA, int[] csrColIndA, double mu0, double[] x0, int maxite, double tol, ref double mu, double[] x)

Parameters

Type	Name	Description
System.Int32	m	number of rows and columns of matrix A.
System.Int32	nnz	number of nonzeros of matrix A.
CudaSparseMatrixDescriptor	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.
System.Double[]	csrValA	array of nnz (= csrRowPtrA(n) * csrRowPtrA(0)) nonzero elements of matrix A.
System.Int32[]	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
System.Int32[]	csrColIndA	integer array of nnz (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
System.Double	mu0	initial guess of eigenvalue.
System.Double[]	x0	initial guess of eigenvector, a vecotr of size m.
System.Int32	maxite	maximum iterations in shift-inverse method.
System.Double	tol	tolerance for convergence.
System.Double	mu	approximated eigenvalue nearest mu0 under tolerance.
System.Double[]	x	approximated eigenvector of size m.

CsreigvsiHost(Int32, Int32, CudaSparseMatrixDescriptor, Single[], Int32[], Int32[], Single, Single[], Int32, Single, ref Single, Single[])

This function solves the simple eigenvalue problem Ax=lambdax by shift-inverse method.

Declaration

public void CsreigvsiHost(int m, int nnz, CudaSparseMatrixDescriptor descrA, float[] csrValA, int[] csrRowPtrA, int[] csrColIndA, float mu0, float[] x0, int maxite, float tol, ref float mu, float[] x)

Parameters

Type	Name	Description
System.Int32	m	number of rows and columns of matrix A.
System.Int32	nnz	number of nonzeros of matrix A.
CudaSparseMatrixDescriptor	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.
System.Single[]	csrValA	array of nnz (= csrRowPtrA(n) * csrRowPtrA(0)) nonzero elements of matrix A.
System.Int32[]	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
System.Int32[]	csrColIndA	integer array of nnz (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
System.Single	mu0	initial guess of eigenvalue.
System.Single[]	x0	initial guess of eigenvector, a vecotr of size m.
System.Int32	maxite	maximum iterations in shift-inverse method.
System.Single	tol	tolerance for convergence.
System.Single	mu	approximated eigenvalue nearest mu0 under tolerance.
System.Single[]	x	approximated eigenvector of size m.

CsrissymHost(Int32, Int32, CudaSparseMatrixDescriptor, Int32[], Int32[], Int32[])

This function checks if A has symmetric pattern or not. The output parameter issym reports 1 if A is symmetric; otherwise, it reports 0.

Declaration

public int CsrissymHost(int m, int nnzA, CudaSparseMatrixDescriptor descrA, int[] csrRowPtrA, int[] csrEndPtrA, int[] csrColIndA)

Parameters

Type	Name	Description
System.Int32	m	number of rows and columns of matrix A.
System.Int32	nnzA	number of nonzeros of matrix A. It is the size of csrValA and csrColIndA.
CudaSparseMatrixDescriptor	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.
System.Int32[]	csrRowPtrA	integer array of m elements that contains the start of every row.
System.Int32[]	csrEndPtrA	integer array of m elements that contains the end of the last row plus one.
System.Int32[]	csrColIndA	integer array of nnzAcolumn indices of the nonzero elements of matrix A.

Returns

Type	Description
System.Int32	1 if A is symmetric; 0 otherwise.

CsrlsqvqrHost(Int32, Int32, Int32, CudaSparseMatrixDescriptor, cuDoubleComplex[], Int32[], Int32[], cuDoubleComplex[], Double, ref Int32, cuDoubleComplex[], Int32[], ref Double)

This function solves the following least-square problem x = argmin||A*z-b||

Declaration

public void CsrlsqvqrHost(int m, int n, int nnz, CudaSparseMatrixDescriptor descrA, cuDoubleComplex[] csrValA, int[] csrRowPtrA, int[] csrColIndA, cuDoubleComplex[] b, double tol, ref int rankA, cuDoubleComplex[] x, int[] p, ref double min_norm)

Parameters

Type	Name	Description
System.Int32	m	number of rows of matrix A.
System.Int32	n	number of columns of matrix A.
System.Int32	nnz	number of nonzeros of matrix A.
CudaSparseMatrixDescriptor	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.
cuDoubleComplex[]	csrValA	array of nnz (= csrRowPtrA(n) * csrRowPtrA(0)) nonzero elements of matrix A.
System.Int32[]	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
System.Int32[]	csrColIndA	integer array of nnz (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
cuDoubleComplex[]	b	right hand side vector of size m.
System.Double	tol	tolerance to decide rank of A.
System.Int32	rankA	numerical rank of A.
cuDoubleComplex[]	x	solution vector of size n, x=pinv(A)*b.
System.Int32[]	p	a vector of size n, which represents the permuation matrix P satisfying AP^T=QR.
System.Double	min_norm	||A*x-b||, x=pinv(A)*b.

CsrlsqvqrHost(Int32, Int32, Int32, CudaSparseMatrixDescriptor, cuFloatComplex[], Int32[], Int32[], cuFloatComplex[], Single, ref Int32, cuFloatComplex[], Int32[], ref Single)

This function solves the following least-square problem x = argmin||A*z-b||

Declaration

public void CsrlsqvqrHost(int m, int n, int nnz, CudaSparseMatrixDescriptor descrA, cuFloatComplex[] csrValA, int[] csrRowPtrA, int[] csrColIndA, cuFloatComplex[] b, float tol, ref int rankA, cuFloatComplex[] x, int[] p, ref float min_norm)

Parameters

Type	Name	Description
System.Int32	m	number of rows of matrix A.
System.Int32	n	number of columns of matrix A.
System.Int32	nnz	number of nonzeros of matrix A.
CudaSparseMatrixDescriptor	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.
cuFloatComplex[]	csrValA	array of nnz (= csrRowPtrA(n) * csrRowPtrA(0)) nonzero elements of matrix A.
System.Int32[]	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
System.Int32[]	csrColIndA	integer array of nnz (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
cuFloatComplex[]	b	right hand side vector of size m.
System.Single	tol	tolerance to decide rank of A.
System.Int32	rankA	numerical rank of A.
cuFloatComplex[]	x	solution vector of size n, x=pinv(A)*b.
System.Int32[]	p	a vector of size n, which represents the permuation matrix P satisfying AP^T=QR.
System.Single	min_norm	||A*x-b||, x=pinv(A)*b.

CsrlsqvqrHost(Int32, Int32, Int32, CudaSparseMatrixDescriptor, Double[], Int32[], Int32[], Double[], Double, ref Int32, Double[], Int32[], ref Double)

This function solves the following least-square problem x = argmin||A*z-b||

Declaration

public void CsrlsqvqrHost(int m, int n, int nnz, CudaSparseMatrixDescriptor descrA, double[] csrValA, int[] csrRowPtrA, int[] csrColIndA, double[] b, double tol, ref int rankA, double[] x, int[] p, ref double min_norm)

Parameters

Type	Name	Description
System.Int32	m	number of rows of matrix A.
System.Int32	n	number of columns of matrix A.
System.Int32	nnz	number of nonzeros of matrix A.
CudaSparseMatrixDescriptor	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.
System.Double[]	csrValA	array of nnz (= csrRowPtrA(n) * csrRowPtrA(0)) nonzero elements of matrix A.
System.Int32[]	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
System.Int32[]	csrColIndA	integer array of nnz (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
System.Double[]	b	right hand side vector of size m.
System.Double	tol	tolerance to decide rank of A.
System.Int32	rankA	numerical rank of A.
System.Double[]	x	solution vector of size n, x=pinv(A)*b.
System.Int32[]	p	a vector of size n, which represents the permuation matrix P satisfying AP^T=QR.
System.Double	min_norm	||A*x-b||, x=pinv(A)*b.

CsrlsqvqrHost(Int32, Int32, Int32, CudaSparseMatrixDescriptor, Single[], Int32[], Int32[], Single[], Single, ref Int32, Single[], Int32[], ref Single)

This function solves the following least-square problem x = argmin||A*z-b||

Declaration

public void CsrlsqvqrHost(int m, int n, int nnz, CudaSparseMatrixDescriptor descrA, float[] csrValA, int[] csrRowPtrA, int[] csrColIndA, float[] b, float tol, ref int rankA, float[] x, int[] p, ref float min_norm)

Parameters

Type	Name	Description
System.Int32	m	number of rows of matrix A.
System.Int32	n	number of columns of matrix A.
System.Int32	nnz	number of nonzeros of matrix A.
CudaSparseMatrixDescriptor	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.
System.Single[]	csrValA	array of nnz (= csrRowPtrA(n) * csrRowPtrA(0)) nonzero elements of matrix A.
System.Int32[]	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
System.Int32[]	csrColIndA	integer array of nnz (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
System.Single[]	b	right hand side vector of size m.
System.Single	tol	tolerance to decide rank of A.
System.Int32	rankA	numerical rank of A.
System.Single[]	x	solution vector of size n, x=pinv(A)*b.
System.Int32[]	p	a vector of size n, which represents the permuation matrix P satisfying AP^T=QR.
System.Single	min_norm	||A*x-b||, x=pinv(A)*b.

Csrlsvchol(Int32, Int32, CudaSparseMatrixDescriptor, CudaDeviceVariable<cuDoubleComplex>, CudaDeviceVariable<Int32>, CudaDeviceVariable<Int32>, CudaDeviceVariable<cuDoubleComplex>, Single, Int32, CudaDeviceVariable<cuDoubleComplex>)

This function solves the linear system A*x=b

Declaration

public int Csrlsvchol(int m, int nnz, CudaSparseMatrixDescriptor descrA, CudaDeviceVariable<cuDoubleComplex> csrValA, CudaDeviceVariable<int> csrRowPtrA, CudaDeviceVariable<int> csrColIndA, CudaDeviceVariable<cuDoubleComplex> b, float tol, int reorder, CudaDeviceVariable<cuDoubleComplex> x)

Parameters

Type	Name	Description
System.Int32	m	number of rows and columns of matrix A.
System.Int32	nnz	number of nonzeros of matrix A.
CudaSparseMatrixDescriptor	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.
CudaDeviceVariable<cuDoubleComplex>	csrValA	array of nnz (= csrRowPtrA(n) * csrRowPtrA(0)) nonzero elements of matrix A.
CudaDeviceVariable<System.Int32>	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
CudaDeviceVariable<System.Int32>	csrColIndA	integer array of nnz (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
CudaDeviceVariable<cuDoubleComplex>	b	right hand side vector of size m.
System.Single	tol	tolerance to decide singularity.
System.Int32	reorder	no effect.
CudaDeviceVariable<cuDoubleComplex>	x	solution vector of size m, x = inv(A)*b.

Returns

Type	Description
System.Int32	-1 if A is invertible. Otherwise, first index j such that U(j,j)≈0

Csrlsvchol(Int32, Int32, CudaSparseMatrixDescriptor, CudaDeviceVariable<cuFloatComplex>, CudaDeviceVariable<Int32>, CudaDeviceVariable<Int32>, CudaDeviceVariable<cuFloatComplex>, Single, Int32, CudaDeviceVariable<cuFloatComplex>)

This function solves the linear system A*x=b

Declaration

public int Csrlsvchol(int m, int nnz, CudaSparseMatrixDescriptor descrA, CudaDeviceVariable<cuFloatComplex> csrValA, CudaDeviceVariable<int> csrRowPtrA, CudaDeviceVariable<int> csrColIndA, CudaDeviceVariable<cuFloatComplex> b, float tol, int reorder, CudaDeviceVariable<cuFloatComplex> x)

Parameters

Type	Name	Description
System.Int32	m	number of rows and columns of matrix A.
System.Int32	nnz	number of nonzeros of matrix A.
CudaSparseMatrixDescriptor	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.
CudaDeviceVariable<cuFloatComplex>	csrValA	array of nnz (= csrRowPtrA(n) * csrRowPtrA(0)) nonzero elements of matrix A.
CudaDeviceVariable<System.Int32>	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
CudaDeviceVariable<System.Int32>	csrColIndA	integer array of nnz (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
CudaDeviceVariable<cuFloatComplex>	b	right hand side vector of size m.
System.Single	tol	tolerance to decide singularity.
System.Int32	reorder	no effect.
CudaDeviceVariable<cuFloatComplex>	x	solution vector of size m, x = inv(A)*b.

Returns

Type	Description
System.Int32	-1 if A is invertible. Otherwise, first index j such that U(j,j)≈0

Csrlsvchol(Int32, Int32, CudaSparseMatrixDescriptor, CudaDeviceVariable<Double>, CudaDeviceVariable<Int32>, CudaDeviceVariable<Int32>, CudaDeviceVariable<Double>, Single, Int32, CudaDeviceVariable<Double>)

This function solves the linear system A*x=b

Declaration

public int Csrlsvchol(int m, int nnz, CudaSparseMatrixDescriptor descrA, CudaDeviceVariable<double> csrValA, CudaDeviceVariable<int> csrRowPtrA, CudaDeviceVariable<int> csrColIndA, CudaDeviceVariable<double> b, float tol, int reorder, CudaDeviceVariable<double> x)

Parameters

Type	Name	Description
System.Int32	m	number of rows and columns of matrix A.
System.Int32	nnz	number of nonzeros of matrix A.
CudaSparseMatrixDescriptor	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.
CudaDeviceVariable<System.Double>	csrValA	array of nnz (= csrRowPtrA(n) * csrRowPtrA(0)) nonzero elements of matrix A.
CudaDeviceVariable<System.Int32>	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
CudaDeviceVariable<System.Int32>	csrColIndA	integer array of nnz (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
CudaDeviceVariable<System.Double>	b	right hand side vector of size m.
System.Single	tol	tolerance to decide singularity.
System.Int32	reorder	no effect.
CudaDeviceVariable<System.Double>	x	solution vector of size m, x = inv(A)*b.

Returns

Type	Description
System.Int32	-1 if A is invertible. Otherwise, first index j such that U(j,j)≈0

Csrlsvchol(Int32, Int32, CudaSparseMatrixDescriptor, CudaDeviceVariable<Single>, CudaDeviceVariable<Int32>, CudaDeviceVariable<Int32>, CudaDeviceVariable<Single>, Single, Int32, CudaDeviceVariable<Single>)

This function solves the linear system A*x=b

Declaration

public int Csrlsvchol(int m, int nnz, CudaSparseMatrixDescriptor descrA, CudaDeviceVariable<float> csrValA, CudaDeviceVariable<int> csrRowPtrA, CudaDeviceVariable<int> csrColIndA, CudaDeviceVariable<float> b, float tol, int reorder, CudaDeviceVariable<float> x)

Parameters

Type	Name	Description
System.Int32	m	number of rows and columns of matrix A.
System.Int32	nnz	number of nonzeros of matrix A.
CudaSparseMatrixDescriptor	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.
CudaDeviceVariable<System.Single>	csrValA	array of nnz (= csrRowPtrA(n) * csrRowPtrA(0)) nonzero elements of matrix A.
CudaDeviceVariable<System.Int32>	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
CudaDeviceVariable<System.Int32>	csrColIndA	integer array of nnz (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
CudaDeviceVariable<System.Single>	b	right hand side vector of size m.
System.Single	tol	tolerance to decide singularity.
System.Int32	reorder	no effect.
CudaDeviceVariable<System.Single>	x	solution vector of size m, x = inv(A)*b.

Returns

Type	Description
System.Int32	-1 if A is invertible. Otherwise, first index j such that U(j,j)≈0

CsrlsvcholHost(Int32, Int32, CudaSparseMatrixDescriptor, cuDoubleComplex[], Int32[], Int32[], cuDoubleComplex[], Single, Int32, cuDoubleComplex[])

This function solves the linear system A*x=b

Declaration

public int CsrlsvcholHost(int m, int nnz, CudaSparseMatrixDescriptor descrA, cuDoubleComplex[] csrValA, int[] csrRowPtrA, int[] csrColIndA, cuDoubleComplex[] b, float tol, int reorder, cuDoubleComplex[] x)

Parameters

Type	Name	Description
System.Int32	m	number of rows and columns of matrix A.
System.Int32	nnz	number of nonzeros of matrix A.
CudaSparseMatrixDescriptor	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.
cuDoubleComplex[]	csrValA	array of nnz (= csrRowPtrA(n) * csrRowPtrA(0)) nonzero elements of matrix A.
System.Int32[]	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
System.Int32[]	csrColIndA	integer array of nnz (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
cuDoubleComplex[]	b	right hand side vector of size m.
System.Single	tol	tolerance to decide singularity.
System.Int32	reorder	no effect.
cuDoubleComplex[]	x	solution vector of size m, x = inv(A)*b.

Returns

Type	Description
System.Int32	-1 if A is invertible. Otherwise, first index j such that U(j,j)≈0

CsrlsvcholHost(Int32, Int32, CudaSparseMatrixDescriptor, cuFloatComplex[], Int32[], Int32[], cuFloatComplex[], Single, Int32, cuFloatComplex[])

This function solves the linear system A*x=b

Declaration

public int CsrlsvcholHost(int m, int nnz, CudaSparseMatrixDescriptor descrA, cuFloatComplex[] csrValA, int[] csrRowPtrA, int[] csrColIndA, cuFloatComplex[] b, float tol, int reorder, cuFloatComplex[] x)

Parameters

Type	Name	Description
System.Int32	m	number of rows and columns of matrix A.
System.Int32	nnz	number of nonzeros of matrix A.
CudaSparseMatrixDescriptor	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.
cuFloatComplex[]	csrValA	array of nnz (= csrRowPtrA(n) * csrRowPtrA(0)) nonzero elements of matrix A.
System.Int32[]	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
System.Int32[]	csrColIndA	integer array of nnz (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
cuFloatComplex[]	b	right hand side vector of size m.
System.Single	tol	tolerance to decide singularity.
System.Int32	reorder	no effect.
cuFloatComplex[]	x	solution vector of size m, x = inv(A)*b.

Returns

Type	Description
System.Int32	-1 if A is invertible. Otherwise, first index j such that U(j,j)≈0

CsrlsvcholHost(Int32, Int32, CudaSparseMatrixDescriptor, Double[], Int32[], Int32[], Double[], Single, Int32, Double[])

This function solves the linear system A*x=b

Declaration

public int CsrlsvcholHost(int m, int nnz, CudaSparseMatrixDescriptor descrA, double[] csrValA, int[] csrRowPtrA, int[] csrColIndA, double[] b, float tol, int reorder, double[] x)

Parameters

Type	Name	Description
System.Int32	m	number of rows and columns of matrix A.
System.Int32	nnz	number of nonzeros of matrix A.
CudaSparseMatrixDescriptor	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.
System.Double[]	csrValA	array of nnz (= csrRowPtrA(n) * csrRowPtrA(0)) nonzero elements of matrix A.
System.Int32[]	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
System.Int32[]	csrColIndA	integer array of nnz (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
System.Double[]	b	right hand side vector of size m.
System.Single	tol	tolerance to decide singularity.
System.Int32	reorder	no effect.
System.Double[]	x	solution vector of size m, x = inv(A)*b.

Returns

Type	Description
System.Int32	-1 if A is invertible. Otherwise, first index j such that U(j,j)≈0

CsrlsvcholHost(Int32, Int32, CudaSparseMatrixDescriptor, Single[], Int32[], Int32[], Single[], Single, Int32, Single[])

This function solves the linear system A*x=b

Declaration

public int CsrlsvcholHost(int m, int nnz, CudaSparseMatrixDescriptor descrA, float[] csrValA, int[] csrRowPtrA, int[] csrColIndA, float[] b, float tol, int reorder, float[] x)

Parameters

Type	Name	Description
System.Int32	m	number of rows and columns of matrix A.
System.Int32	nnz	number of nonzeros of matrix A.
CudaSparseMatrixDescriptor	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.
System.Single[]	csrValA	array of nnz (= csrRowPtrA(n) * csrRowPtrA(0)) nonzero elements of matrix A.
System.Int32[]	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
System.Int32[]	csrColIndA	integer array of nnz (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
System.Single[]	b	right hand side vector of size m.
System.Single	tol	tolerance to decide singularity.
System.Int32	reorder	no effect.
System.Single[]	x	solution vector of size m, x = inv(A)*b.

Returns

Type	Description
System.Int32	-1 if A is invertible. Otherwise, first index j such that U(j,j)≈0

CsrlsvluHost(Int32, Int32, CudaSparseMatrixDescriptor, cuDoubleComplex[], Int32[], Int32[], cuDoubleComplex[], Double, Int32, cuDoubleComplex[])

This function solves the linear system A*x=b

Declaration

public int CsrlsvluHost(int n, int nnzA, CudaSparseMatrixDescriptor descrA, cuDoubleComplex[] csrValA, int[] csrRowPtrA, int[] csrColIndA, cuDoubleComplex[] b, double tol, int reorder, cuDoubleComplex[] x)

Parameters

Type	Name	Description
System.Int32	n	number of rows and columns of matrix A.
System.Int32	nnzA	number of nonzeros of matrix A.
CudaSparseMatrixDescriptor	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.
cuDoubleComplex[]	csrValA	array of nnzA (= csrRowPtrA(n) * csrRowPtrA(0)) nonzero elements of matrix A.
System.Int32[]	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
System.Int32[]	csrColIndA	integer array of nnzA (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
cuDoubleComplex[]	b	right hand side vector of size n.
System.Double	tol	tolerance to decide if singular or not.
System.Int32	reorder	no ordering if reorder=0. Otherwise, symrcm is used to reduce zero fill-in.
cuDoubleComplex[]	x	solution vector of size n, x = inv(A)*b.

Returns

Type	Description
System.Int32	-1 if A is invertible. Otherwise, first index j such that U(j,j)≈0

CsrlsvluHost(Int32, Int32, CudaSparseMatrixDescriptor, cuFloatComplex[], Int32[], Int32[], cuFloatComplex[], Single, Int32, cuFloatComplex[])

This function solves the linear system A*x=b

Declaration

public int CsrlsvluHost(int n, int nnzA, CudaSparseMatrixDescriptor descrA, cuFloatComplex[] csrValA, int[] csrRowPtrA, int[] csrColIndA, cuFloatComplex[] b, float tol, int reorder, cuFloatComplex[] x)

Parameters

Type	Name	Description
System.Int32	n	number of rows and columns of matrix A.
System.Int32	nnzA	number of nonzeros of matrix A.
CudaSparseMatrixDescriptor	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.
cuFloatComplex[]	csrValA	array of nnzA (= csrRowPtrA(n) * csrRowPtrA(0)) nonzero elements of matrix A.
System.Int32[]	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
System.Int32[]	csrColIndA	integer array of nnzA (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
cuFloatComplex[]	b	right hand side vector of size n.
System.Single	tol	tolerance to decide if singular or not.
System.Int32	reorder	no ordering if reorder=0. Otherwise, symrcm is used to reduce zero fill-in.
cuFloatComplex[]	x	solution vector of size n, x = inv(A)*b.

Returns

Type	Description
System.Int32	-1 if A is invertible. Otherwise, first index j such that U(j,j)≈0

CsrlsvluHost(Int32, Int32, CudaSparseMatrixDescriptor, Double[], Int32[], Int32[], Double[], Double, Int32, Double[])

This function solves the linear system A*x=b

Declaration

public int CsrlsvluHost(int n, int nnzA, CudaSparseMatrixDescriptor descrA, double[] csrValA, int[] csrRowPtrA, int[] csrColIndA, double[] b, double tol, int reorder, double[] x)

Parameters

Type	Name	Description
System.Int32	n	number of rows and columns of matrix A.
System.Int32	nnzA	number of nonzeros of matrix A.
CudaSparseMatrixDescriptor	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.
System.Double[]	csrValA	array of nnzA (= csrRowPtrA(n) * csrRowPtrA(0)) nonzero elements of matrix A.
System.Int32[]	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
System.Int32[]	csrColIndA	integer array of nnzA (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
System.Double[]	b	right hand side vector of size n.
System.Double	tol	tolerance to decide if singular or not.
System.Int32	reorder	no ordering if reorder=0. Otherwise, symrcm is used to reduce zero fill-in.
System.Double[]	x	solution vector of size n, x = inv(A)*b.

Returns

Type	Description
System.Int32	-1 if A is invertible. Otherwise, first index j such that U(j,j)≈0

CsrlsvluHost(Int32, Int32, CudaSparseMatrixDescriptor, Single[], Int32[], Int32[], Single[], Single, Int32, Single[])

This function solves the linear system A*x=b

Declaration

public int CsrlsvluHost(int n, int nnzA, CudaSparseMatrixDescriptor descrA, float[] csrValA, int[] csrRowPtrA, int[] csrColIndA, float[] b, float tol, int reorder, float[] x)

Parameters

Type	Name	Description
System.Int32	n	number of rows and columns of matrix A.
System.Int32	nnzA	number of nonzeros of matrix A.
CudaSparseMatrixDescriptor	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.
System.Single[]	csrValA	array of nnzA (= csrRowPtrA(n) * csrRowPtrA(0)) nonzero elements of matrix A.
System.Int32[]	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
System.Int32[]	csrColIndA	integer array of nnzA (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
System.Single[]	b	right hand side vector of size n.
System.Single	tol	tolerance to decide if singular or not.
System.Int32	reorder	no ordering if reorder=0. Otherwise, symrcm is used to reduce zero fill-in.
System.Single[]	x	solution vector of size n, x = inv(A)*b.

Returns

Type	Description
System.Int32	-1 if A is invertible. Otherwise, first index j such that U(j,j)≈0

Csrlsvqr(Int32, Int32, CudaSparseMatrixDescriptor, CudaDeviceVariable<cuDoubleComplex>, CudaDeviceVariable<Int32>, CudaDeviceVariable<Int32>, CudaDeviceVariable<cuDoubleComplex>, Single, Int32, CudaDeviceVariable<cuDoubleComplex>)

This function solves the linear system A*x=b

Declaration

public int Csrlsvqr(int m, int nnz, CudaSparseMatrixDescriptor descrA, CudaDeviceVariable<cuDoubleComplex> csrValA, CudaDeviceVariable<int> csrRowPtrA, CudaDeviceVariable<int> csrColIndA, CudaDeviceVariable<cuDoubleComplex> b, float tol, int reorder, CudaDeviceVariable<cuDoubleComplex> x)

Parameters

Type	Name	Description
System.Int32	m	number of rows and columns of matrix A.
System.Int32	nnz	number of nonzeros of matrix A.
CudaSparseMatrixDescriptor	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.
CudaDeviceVariable<cuDoubleComplex>	csrValA	array of nnz (= csrRowPtrA(n) * csrRowPtrA(0)) nonzero elements of matrix A.
CudaDeviceVariable<System.Int32>	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
CudaDeviceVariable<System.Int32>	csrColIndA	integer array of nnz (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
CudaDeviceVariable<cuDoubleComplex>	b	right hand side vector of size m.
System.Single	tol	tolerance to decide if singular or not.
System.Int32	reorder	no effect.
CudaDeviceVariable<cuDoubleComplex>	x	solution vector of size m, x = inv(A)*b.

Returns

Type	Description
System.Int32	-1 if A is invertible. Otherwise, first index j such that U(j,j)≈0

Csrlsvqr(Int32, Int32, CudaSparseMatrixDescriptor, CudaDeviceVariable<cuFloatComplex>, CudaDeviceVariable<Int32>, CudaDeviceVariable<Int32>, CudaDeviceVariable<cuFloatComplex>, Single, Int32, CudaDeviceVariable<cuFloatComplex>)

This function solves the linear system A*x=b

Declaration

public int Csrlsvqr(int m, int nnz, CudaSparseMatrixDescriptor descrA, CudaDeviceVariable<cuFloatComplex> csrValA, CudaDeviceVariable<int> csrRowPtrA, CudaDeviceVariable<int> csrColIndA, CudaDeviceVariable<cuFloatComplex> b, float tol, int reorder, CudaDeviceVariable<cuFloatComplex> x)

Parameters

Type	Name	Description
System.Int32	m	number of rows and columns of matrix A.
System.Int32	nnz	number of nonzeros of matrix A.
CudaSparseMatrixDescriptor	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.
CudaDeviceVariable<cuFloatComplex>	csrValA	array of nnz (= csrRowPtrA(n) * csrRowPtrA(0)) nonzero elements of matrix A.
CudaDeviceVariable<System.Int32>	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
CudaDeviceVariable<System.Int32>	csrColIndA	integer array of nnz (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
CudaDeviceVariable<cuFloatComplex>	b	right hand side vector of size m.
System.Single	tol	tolerance to decide if singular or not.
System.Int32	reorder	no effect.
CudaDeviceVariable<cuFloatComplex>	x	solution vector of size m, x = inv(A)*b.

Returns

Type	Description
System.Int32	-1 if A is invertible. Otherwise, first index j such that U(j,j)≈0

Csrlsvqr(Int32, Int32, CudaSparseMatrixDescriptor, CudaDeviceVariable<Double>, CudaDeviceVariable<Int32>, CudaDeviceVariable<Int32>, CudaDeviceVariable<Double>, Single, Int32, CudaDeviceVariable<Double>)

This function solves the linear system A*x=b

Declaration

public int Csrlsvqr(int m, int nnz, CudaSparseMatrixDescriptor descrA, CudaDeviceVariable<double> csrValA, CudaDeviceVariable<int> csrRowPtrA, CudaDeviceVariable<int> csrColIndA, CudaDeviceVariable<double> b, float tol, int reorder, CudaDeviceVariable<double> x)

Parameters

Type	Name	Description
System.Int32	m	number of rows and columns of matrix A.
System.Int32	nnz	number of nonzeros of matrix A.
CudaSparseMatrixDescriptor	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.
CudaDeviceVariable<System.Double>	csrValA	array of nnz (= csrRowPtrA(n) * csrRowPtrA(0)) nonzero elements of matrix A.
CudaDeviceVariable<System.Int32>	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
CudaDeviceVariable<System.Int32>	csrColIndA	integer array of nnz (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
CudaDeviceVariable<System.Double>	b	right hand side vector of size m.
System.Single	tol	tolerance to decide if singular or not.
System.Int32	reorder	no effect.
CudaDeviceVariable<System.Double>	x	solution vector of size m, x = inv(A)*b.

Returns

Type	Description
System.Int32	-1 if A is invertible. Otherwise, first index j such that U(j,j)≈0

Csrlsvqr(Int32, Int32, CudaSparseMatrixDescriptor, CudaDeviceVariable<Single>, CudaDeviceVariable<Int32>, CudaDeviceVariable<Int32>, CudaDeviceVariable<Single>, Single, Int32, CudaDeviceVariable<Single>)

This function solves the linear system A*x=b

Declaration

public int Csrlsvqr(int m, int nnz, CudaSparseMatrixDescriptor descrA, CudaDeviceVariable<float> csrValA, CudaDeviceVariable<int> csrRowPtrA, CudaDeviceVariable<int> csrColIndA, CudaDeviceVariable<float> b, float tol, int reorder, CudaDeviceVariable<float> x)

Parameters

Type	Name	Description
System.Int32	m	number of rows and columns of matrix A.
System.Int32	nnz	number of nonzeros of matrix A.
CudaSparseMatrixDescriptor	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.
CudaDeviceVariable<System.Single>	csrValA	array of nnz (= csrRowPtrA(n) * csrRowPtrA(0)) nonzero elements of matrix A.
CudaDeviceVariable<System.Int32>	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
CudaDeviceVariable<System.Int32>	csrColIndA	integer array of nnz (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
CudaDeviceVariable<System.Single>	b	right hand side vector of size m.
System.Single	tol	tolerance to decide if singular or not.
System.Int32	reorder	no effect.
CudaDeviceVariable<System.Single>	x	solution vector of size m, x = inv(A)*b.

Returns

Type	Description
System.Int32	-1 if A is invertible. Otherwise, first index j such that U(j,j)≈0

CsrlsvqrHost(Int32, Int32, CudaSparseMatrixDescriptor, cuDoubleComplex[], Int32[], Int32[], cuDoubleComplex[], Single, Int32, cuDoubleComplex[])

This function solves the linear system A*x=b

Declaration

public int CsrlsvqrHost(int m, int nnz, CudaSparseMatrixDescriptor descrA, cuDoubleComplex[] csrValA, int[] csrRowPtrA, int[] csrColIndA, cuDoubleComplex[] b, float tol, int reorder, cuDoubleComplex[] x)

Parameters

Type	Name	Description
System.Int32	m	number of rows and columns of matrix A.
System.Int32	nnz	number of nonzeros of matrix A.
CudaSparseMatrixDescriptor	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.
cuDoubleComplex[]	csrValA	array of nnz (= csrRowPtrA(n) * csrRowPtrA(0)) nonzero elements of matrix A.
System.Int32[]	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
System.Int32[]	csrColIndA	integer array of nnz (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
cuDoubleComplex[]	b	right hand side vector of size m.
System.Single	tol	tolerance to decide if singular or not.
System.Int32	reorder	no effect.
cuDoubleComplex[]	x	solution vector of size m, x = inv(A)*b.

Returns

Type	Description
System.Int32	-1 if A is invertible. Otherwise, first index j such that U(j,j)≈0

CsrlsvqrHost(Int32, Int32, CudaSparseMatrixDescriptor, cuFloatComplex[], Int32[], Int32[], cuFloatComplex[], Single, Int32, cuFloatComplex[])

This function solves the linear system A*x=b

Declaration

public int CsrlsvqrHost(int m, int nnz, CudaSparseMatrixDescriptor descrA, cuFloatComplex[] csrValA, int[] csrRowPtrA, int[] csrColIndA, cuFloatComplex[] b, float tol, int reorder, cuFloatComplex[] x)

Parameters

Type	Name	Description
System.Int32	m	number of rows and columns of matrix A.
System.Int32	nnz	number of nonzeros of matrix A.
CudaSparseMatrixDescriptor	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.
cuFloatComplex[]	csrValA	array of nnz (= csrRowPtrA(n) * csrRowPtrA(0)) nonzero elements of matrix A.
System.Int32[]	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
System.Int32[]	csrColIndA	integer array of nnz (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
cuFloatComplex[]	b	right hand side vector of size m.
System.Single	tol	tolerance to decide if singular or not.
System.Int32	reorder	no effect.
cuFloatComplex[]	x	solution vector of size m, x = inv(A)*b.

Returns

Type	Description
System.Int32	-1 if A is invertible. Otherwise, first index j such that U(j,j)≈0

CsrlsvqrHost(Int32, Int32, CudaSparseMatrixDescriptor, Double[], Int32[], Int32[], Double[], Single, Int32, Double[])

This function solves the linear system A*x=b

Declaration

public int CsrlsvqrHost(int m, int nnz, CudaSparseMatrixDescriptor descrA, double[] csrValA, int[] csrRowPtrA, int[] csrColIndA, double[] b, float tol, int reorder, double[] x)

Parameters

Type	Name	Description
System.Int32	m	number of rows and columns of matrix A.
System.Int32	nnz	number of nonzeros of matrix A.
CudaSparseMatrixDescriptor	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.
System.Double[]	csrValA	array of nnz (= csrRowPtrA(n) * csrRowPtrA(0)) nonzero elements of matrix A.
System.Int32[]	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
System.Int32[]	csrColIndA	integer array of nnz (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
System.Double[]	b	right hand side vector of size m.
System.Single	tol	tolerance to decide if singular or not.
System.Int32	reorder	no effect.
System.Double[]	x	solution vector of size m, x = inv(A)*b.

Returns

Type	Description
System.Int32	-1 if A is invertible. Otherwise, first index j such that U(j,j)≈0

CsrlsvqrHost(Int32, Int32, CudaSparseMatrixDescriptor, Single[], Int32[], Int32[], Single[], Single, Int32, Single[])

This function solves the linear system A*x=b

Declaration

public int CsrlsvqrHost(int m, int nnz, CudaSparseMatrixDescriptor descrA, float[] csrValA, int[] csrRowPtrA, int[] csrColIndA, float[] b, float tol, int reorder, float[] x)

Parameters

Type	Name	Description
System.Int32	m	number of rows and columns of matrix A.
System.Int32	nnz	number of nonzeros of matrix A.
CudaSparseMatrixDescriptor	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.
System.Single[]	csrValA	array of nnz (= csrRowPtrA(n) * csrRowPtrA(0)) nonzero elements of matrix A.
System.Int32[]	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
System.Int32[]	csrColIndA	integer array of nnz (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
System.Single[]	b	right hand side vector of size m.
System.Single	tol	tolerance to decide if singular or not.
System.Int32	reorder	no effect.
System.Single[]	x	solution vector of size m, x = inv(A)*b.

Returns

Type	Description
System.Int32	-1 if A is invertible. Otherwise, first index j such that U(j,j)≈0

Csrperm_bufferSizeHost(Int32, Int32, Int32, CudaSparseMatrixDescriptor, Int32[], Int32[], Int32[], Int32[])

Given a left permutation vector p which corresponds to permutation matrix P and a right permutation vector q which corresponds to permutation matrix Q, this function computes permutation of matrix A by B = PAQ^T

Declaration

public SizeT Csrperm_bufferSizeHost(int m, int n, int nnzA, CudaSparseMatrixDescriptor descrA, int[] csrRowPtrA, int[] csrColIndA, int[] p, int[] q)

Parameters

Type	Name	Description
System.Int32	m	number of rows of matrix A.
System.Int32	n	number of columns of matrix A.
System.Int32	nnzA	number of nonzeros of matrix A. It is the size of csrValA and csrColIndA.
CudaSparseMatrixDescriptor	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.
System.Int32[]	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
System.Int32[]	csrColIndA	integer array of nnz (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
System.Int32[]	p	left permutation vector of size m.
System.Int32[]	q	right permutation vector of size n.

Returns

Type	Description
SizeT	number of bytes of the buffer.

CsrpermHost(Int32, Int32, Int32, CudaSparseMatrixDescriptor, Int32[], Int32[], Int32[], Int32[], Int32[], Byte[])

Given a left permutation vector p which corresponds to permutation matrix P and a right permutation vector q which corresponds to permutation matrix Q, this function computes permutation of matrix A by B = PAQ^T

Declaration

public void CsrpermHost(int m, int n, int nnzA, CudaSparseMatrixDescriptor descrA, int[] csrRowPtrA, int[] csrColIndA, int[] p, int[] q, int[] map, byte[] pBuffer)

Parameters

Type	Name	Description
System.Int32	m	number of rows of matrix A.
System.Int32	n	number of columns of matrix A.
System.Int32	nnzA	number of nonzeros of matrix A. It is the size of csrValA and csrColIndA.
CudaSparseMatrixDescriptor	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.
System.Int32[]	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
System.Int32[]	csrColIndA	integer array of nnz (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
System.Int32[]	p	left permutation vector of size m.
System.Int32[]	q	right permutation vector of size n.
System.Int32[]	map	integer array of nnzA indices. If the user wants to get relationship between A and B, map must be set 0:1:(nnzA-1).
System.Byte[]	pBuffer	buffer allocated by the user, the size is returned by csrperm_bufferSize().

CsrqrAnalysisBatched(Int32, Int32, Int32, CudaSparseMatrixDescriptor, CudaDeviceVariable<Int32>, CudaDeviceVariable<Int32>, CsrQrInfo)

The batched sparse QR factorization is used to solve either a set of least-squares problems or a set of linear systems

Declaration

public void CsrqrAnalysisBatched(int m, int n, int nnzA, CudaSparseMatrixDescriptor descrA, CudaDeviceVariable<int> csrRowPtrA, CudaDeviceVariable<int> csrColIndA, CsrQrInfo info)

Parameters

Type	Name	Description
System.Int32	m	number of rows of each matrix Aj.
System.Int32	n	number of columns of each matrix Aj.
System.Int32	nnzA	number of nonzeros of each matrix Aj. It is the size csrColIndA.
CudaSparseMatrixDescriptor	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.
CudaDeviceVariable<System.Int32>	csrRowPtrA	integer array of m+1 elements that contains the start of every row and the end of the last row plus one.
CudaDeviceVariable<System.Int32>	csrColIndA	integer array of nnzAcolumn indices of the nonzero elements of each matrix Aj.
CsrQrInfo	info	opaque structure for QR factorization.

CsrqrBufferInfoBatched(Int32, Int32, Int32, CudaSparseMatrixDescriptor, CudaDeviceVariable<cuDoubleComplex>, CudaDeviceVariable<Int32>, CudaDeviceVariable<Int32>, Int32, CsrQrInfo, ref SizeT, ref SizeT)

The batched sparse QR factorization is used to solve either a set of least-squares problems or a set of linear systems

Declaration

public void CsrqrBufferInfoBatched(int m, int n, int nnz, CudaSparseMatrixDescriptor descrA, CudaDeviceVariable<cuDoubleComplex> csrVal, CudaDeviceVariable<int> csrRowPtr, CudaDeviceVariable<int> csrColInd, int batchSize, CsrQrInfo info, ref SizeT internalDataInBytes, ref SizeT workspaceInBytes)

Parameters

Type	Name	Description
System.Int32	m	number of rows of each matrix Aj.
System.Int32	n	number of columns of each matrix Aj.
System.Int32	nnz	number of nonzeros of each matrix Aj. It is the size csrColIndA.
CudaSparseMatrixDescriptor	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.
CudaDeviceVariable<cuDoubleComplex>	csrVal	array of nnzA*batchSize nonzero elements of matrices A0, A1, .... All matrices are aggregated one after another.
CudaDeviceVariable<System.Int32>	csrRowPtr	integer array of m+1 elements that contains the start of every row and the end of the last row plus one.
CudaDeviceVariable<System.Int32>	csrColInd	integer array of nnzAcolumn indices of the nonzero elements of each matrix Aj.
System.Int32	batchSize	number of systems to be solved.
CsrQrInfo	info	opaque structure for QR factorization.
SizeT	internalDataInBytes	number of bytes of the internal data.
SizeT	workspaceInBytes	number of bytes of the buffer in numerical factorization.

CsrqrBufferInfoBatched(Int32, Int32, Int32, CudaSparseMatrixDescriptor, CudaDeviceVariable<cuFloatComplex>, CudaDeviceVariable<Int32>, CudaDeviceVariable<Int32>, Int32, CsrQrInfo, ref SizeT, ref SizeT)

The batched sparse QR factorization is used to solve either a set of least-squares problems or a set of linear systems

Declaration

public void CsrqrBufferInfoBatched(int m, int n, int nnz, CudaSparseMatrixDescriptor descrA, CudaDeviceVariable<cuFloatComplex> csrVal, CudaDeviceVariable<int> csrRowPtr, CudaDeviceVariable<int> csrColInd, int batchSize, CsrQrInfo info, ref SizeT internalDataInBytes, ref SizeT workspaceInBytes)

Parameters

Type	Name	Description
System.Int32	m	number of rows of each matrix Aj.
System.Int32	n	number of columns of each matrix Aj.
System.Int32	nnz	number of nonzeros of each matrix Aj. It is the size csrColIndA.
CudaSparseMatrixDescriptor	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.
CudaDeviceVariable<cuFloatComplex>	csrVal	array of nnzA*batchSize nonzero elements of matrices A0, A1, .... All matrices are aggregated one after another.
CudaDeviceVariable<System.Int32>	csrRowPtr	integer array of m+1 elements that contains the start of every row and the end of the last row plus one.
CudaDeviceVariable<System.Int32>	csrColInd	integer array of nnzAcolumn indices of the nonzero elements of each matrix Aj.
System.Int32	batchSize	number of systems to be solved.
CsrQrInfo	info	opaque structure for QR factorization.
SizeT	internalDataInBytes	number of bytes of the internal data.
SizeT	workspaceInBytes	number of bytes of the buffer in numerical factorization.

CsrqrBufferInfoBatched(Int32, Int32, Int32, CudaSparseMatrixDescriptor, CudaDeviceVariable<Double>, CudaDeviceVariable<Int32>, CudaDeviceVariable<Int32>, Int32, CsrQrInfo, ref SizeT, ref SizeT)

The batched sparse QR factorization is used to solve either a set of least-squares problems or a set of linear systems

Declaration

public void CsrqrBufferInfoBatched(int m, int n, int nnz, CudaSparseMatrixDescriptor descrA, CudaDeviceVariable<double> csrVal, CudaDeviceVariable<int> csrRowPtr, CudaDeviceVariable<int> csrColInd, int batchSize, CsrQrInfo info, ref SizeT internalDataInBytes, ref SizeT workspaceInBytes)

Parameters

Type	Name	Description
System.Int32	m	number of rows of each matrix Aj.
System.Int32	n	number of columns of each matrix Aj.
System.Int32	nnz	number of nonzeros of each matrix Aj. It is the size csrColIndA.
CudaSparseMatrixDescriptor	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.
CudaDeviceVariable<System.Double>	csrVal	array of nnzA*batchSize nonzero elements of matrices A0, A1, .... All matrices are aggregated one after another.
CudaDeviceVariable<System.Int32>	csrRowPtr	integer array of m+1 elements that contains the start of every row and the end of the last row plus one.
CudaDeviceVariable<System.Int32>	csrColInd	integer array of nnzAcolumn indices of the nonzero elements of each matrix Aj.
System.Int32	batchSize	number of systems to be solved.
CsrQrInfo	info	opaque structure for QR factorization.
SizeT	internalDataInBytes	number of bytes of the internal data.
SizeT	workspaceInBytes	number of bytes of the buffer in numerical factorization.

CsrqrBufferInfoBatched(Int32, Int32, Int32, CudaSparseMatrixDescriptor, CudaDeviceVariable<Single>, CudaDeviceVariable<Int32>, CudaDeviceVariable<Int32>, Int32, CsrQrInfo, ref SizeT, ref SizeT)

The batched sparse QR factorization is used to solve either a set of least-squares problems or a set of linear systems

Declaration

public void CsrqrBufferInfoBatched(int m, int n, int nnz, CudaSparseMatrixDescriptor descrA, CudaDeviceVariable<float> csrVal, CudaDeviceVariable<int> csrRowPtr, CudaDeviceVariable<int> csrColInd, int batchSize, CsrQrInfo info, ref SizeT internalDataInBytes, ref SizeT workspaceInBytes)

Parameters

Type	Name	Description
System.Int32	m	number of rows of each matrix Aj.
System.Int32	n	number of columns of each matrix Aj.
System.Int32	nnz	number of nonzeros of each matrix Aj. It is the size csrColIndA.
CudaSparseMatrixDescriptor	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.
CudaDeviceVariable<System.Single>	csrVal	array of nnzA*batchSize nonzero elements of matrices A0, A1, .... All matrices are aggregated one after another.
CudaDeviceVariable<System.Int32>	csrRowPtr	integer array of m+1 elements that contains the start of every row and the end of the last row plus one.
CudaDeviceVariable<System.Int32>	csrColInd	integer array of nnzAcolumn indices of the nonzero elements of each matrix Aj.
System.Int32	batchSize	number of systems to be solved.
CsrQrInfo	info	opaque structure for QR factorization.
SizeT	internalDataInBytes	number of bytes of the internal data.
SizeT	workspaceInBytes	number of bytes of the buffer in numerical factorization.

CsrqrsvBatched(Int32, Int32, Int32, CudaSparseMatrixDescriptor, CudaDeviceVariable<cuDoubleComplex>, CudaDeviceVariable<Int32>, CudaDeviceVariable<Int32>, CudaDeviceVariable<cuDoubleComplex>, CudaDeviceVariable<cuDoubleComplex>, Int32, CsrQrInfo, CudaDeviceVariable<Byte>)

The batched sparse QR factorization is used to solve either a set of least-squares problems or a set of linear systems

Declaration

public void CsrqrsvBatched(int m, int n, int nnz, CudaSparseMatrixDescriptor descrA, CudaDeviceVariable<cuDoubleComplex> csrValA, CudaDeviceVariable<int> csrRowPtrA, CudaDeviceVariable<int> csrColIndA, CudaDeviceVariable<cuDoubleComplex> b, CudaDeviceVariable<cuDoubleComplex> x, int batchSize, CsrQrInfo info, CudaDeviceVariable<byte> pBuffer)

Parameters

Type	Name	Description
System.Int32	m	number of rows of each matrix Aj.
System.Int32	n	number of columns of each matrix Aj.
System.Int32	nnz	number of nonzeros of each matrix Aj. It is the size csrColIndA.
CudaSparseMatrixDescriptor	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.
CudaDeviceVariable<cuDoubleComplex>	csrValA	array of nnzA*batchSize nonzero elements of matrices A0, A1, .... All matrices are aggregated one after another.
CudaDeviceVariable<System.Int32>	csrRowPtrA	integer array of m+1 elements that contains the start of every row and the end of the last row plus one.
CudaDeviceVariable<System.Int32>	csrColIndA	integer array of nnzAcolumn indices of the nonzero elements of each matrix Aj.
CudaDeviceVariable<cuDoubleComplex>	b	array of m*batchSize of right-hand-side vectors b0, b1, .... All vectors are aggregated one after another.
CudaDeviceVariable<cuDoubleComplex>	x	array of m*batchSize of solution vectors x0, x1, .... All vectors are aggregated one after another.
System.Int32	batchSize	number of systems to be solved.
CsrQrInfo	info	opaque structure for QR factorization.
CudaDeviceVariable<System.Byte>	pBuffer	buffer allocated by the user, the size is returned by cusolverSpXcsrqrBufferInfoBatched().

CsrqrsvBatched(Int32, Int32, Int32, CudaSparseMatrixDescriptor, CudaDeviceVariable<cuFloatComplex>, CudaDeviceVariable<Int32>, CudaDeviceVariable<Int32>, CudaDeviceVariable<cuFloatComplex>, CudaDeviceVariable<cuFloatComplex>, Int32, CsrQrInfo, CudaDeviceVariable<Byte>)

The batched sparse QR factorization is used to solve either a set of least-squares problems or a set of linear systems

Declaration

public void CsrqrsvBatched(int m, int n, int nnz, CudaSparseMatrixDescriptor descrA, CudaDeviceVariable<cuFloatComplex> csrValA, CudaDeviceVariable<int> csrRowPtrA, CudaDeviceVariable<int> csrColIndA, CudaDeviceVariable<cuFloatComplex> b, CudaDeviceVariable<cuFloatComplex> x, int batchSize, CsrQrInfo info, CudaDeviceVariable<byte> pBuffer)

Parameters

Type	Name	Description
System.Int32	m	number of rows of each matrix Aj.
System.Int32	n	number of columns of each matrix Aj.
System.Int32	nnz	number of nonzeros of each matrix Aj. It is the size csrColIndA.
CudaSparseMatrixDescriptor	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.
CudaDeviceVariable<cuFloatComplex>	csrValA	array of nnzA*batchSize nonzero elements of matrices A0, A1, .... All matrices are aggregated one after another.
CudaDeviceVariable<System.Int32>	csrRowPtrA	integer array of m+1 elements that contains the start of every row and the end of the last row plus one.
CudaDeviceVariable<System.Int32>	csrColIndA	integer array of nnzAcolumn indices of the nonzero elements of each matrix Aj.
CudaDeviceVariable<cuFloatComplex>	b	array of m*batchSize of right-hand-side vectors b0, b1, .... All vectors are aggregated one after another.
CudaDeviceVariable<cuFloatComplex>	x	array of m*batchSize of solution vectors x0, x1, .... All vectors are aggregated one after another.
System.Int32	batchSize	number of systems to be solved.
CsrQrInfo	info	opaque structure for QR factorization.
CudaDeviceVariable<System.Byte>	pBuffer	buffer allocated by the user, the size is returned by cusolverSpXcsrqrBufferInfoBatched().

CsrqrsvBatched(Int32, Int32, Int32, CudaSparseMatrixDescriptor, CudaDeviceVariable<Double>, CudaDeviceVariable<Int32>, CudaDeviceVariable<Int32>, CudaDeviceVariable<Double>, CudaDeviceVariable<Double>, Int32, CsrQrInfo, CudaDeviceVariable<Byte>)

The batched sparse QR factorization is used to solve either a set of least-squares problems or a set of linear systems

Declaration

public void CsrqrsvBatched(int m, int n, int nnz, CudaSparseMatrixDescriptor descrA, CudaDeviceVariable<double> csrValA, CudaDeviceVariable<int> csrRowPtrA, CudaDeviceVariable<int> csrColIndA, CudaDeviceVariable<double> b, CudaDeviceVariable<double> x, int batchSize, CsrQrInfo info, CudaDeviceVariable<byte> pBuffer)

Parameters

Type	Name	Description
System.Int32	m	number of rows of each matrix Aj.
System.Int32	n	number of columns of each matrix Aj.
System.Int32	nnz	number of nonzeros of each matrix Aj. It is the size csrColIndA.
CudaSparseMatrixDescriptor	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.
CudaDeviceVariable<System.Double>	csrValA	array of nnzA*batchSize nonzero elements of matrices A0, A1, .... All matrices are aggregated one after another.
CudaDeviceVariable<System.Int32>	csrRowPtrA	integer array of m+1 elements that contains the start of every row and the end of the last row plus one.
CudaDeviceVariable<System.Int32>	csrColIndA	integer array of nnzAcolumn indices of the nonzero elements of each matrix Aj.
CudaDeviceVariable<System.Double>	b	array of m*batchSize of right-hand-side vectors b0, b1, .... All vectors are aggregated one after another.
CudaDeviceVariable<System.Double>	x	array of m*batchSize of solution vectors x0, x1, .... All vectors are aggregated one after another.
System.Int32	batchSize	number of systems to be solved.
CsrQrInfo	info	opaque structure for QR factorization.
CudaDeviceVariable<System.Byte>	pBuffer	buffer allocated by the user, the size is returned by cusolverSpXcsrqrBufferInfoBatched().

CsrqrsvBatched(Int32, Int32, Int32, CudaSparseMatrixDescriptor, CudaDeviceVariable<Single>, CudaDeviceVariable<Int32>, CudaDeviceVariable<Int32>, CudaDeviceVariable<Single>, CudaDeviceVariable<Single>, Int32, CsrQrInfo, CudaDeviceVariable<Byte>)

The batched sparse QR factorization is used to solve either a set of least-squares problems or a set of linear systems

Declaration

public void CsrqrsvBatched(int m, int n, int nnz, CudaSparseMatrixDescriptor descrA, CudaDeviceVariable<float> csrValA, CudaDeviceVariable<int> csrRowPtrA, CudaDeviceVariable<int> csrColIndA, CudaDeviceVariable<float> b, CudaDeviceVariable<float> x, int batchSize, CsrQrInfo info, CudaDeviceVariable<byte> pBuffer)

Parameters

Type	Name	Description
System.Int32	m	number of rows of each matrix Aj.
System.Int32	n	number of columns of each matrix Aj.
System.Int32	nnz	number of nonzeros of each matrix Aj. It is the size csrColIndA.
CudaSparseMatrixDescriptor	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.
CudaDeviceVariable<System.Single>	csrValA	array of nnzA*batchSize nonzero elements of matrices A0, A1, .... All matrices are aggregated one after another.
CudaDeviceVariable<System.Int32>	csrRowPtrA	integer array of m+1 elements that contains the start of every row and the end of the last row plus one.
CudaDeviceVariable<System.Int32>	csrColIndA	integer array of nnzAcolumn indices of the nonzero elements of each matrix Aj.
CudaDeviceVariable<System.Single>	b	array of m*batchSize of right-hand-side vectors b0, b1, .... All vectors are aggregated one after another.
CudaDeviceVariable<System.Single>	x	array of m*batchSize of solution vectors x0, x1, .... All vectors are aggregated one after another.
System.Int32	batchSize	number of systems to be solved.
CsrQrInfo	info	opaque structure for QR factorization.
CudaDeviceVariable<System.Byte>	pBuffer	buffer allocated by the user, the size is returned by cusolverSpXcsrqrBufferInfoBatched().

CsrsymamdHost(Int32, Int32, CudaSparseMatrixDescriptor, Int32[], Int32[], Int32[])

Symmetric Approximate minimum degree algorithm based on quotient graph.

This function implements Symmetric Approximate Minimum Degree Algorithm based on Quotient Graph. It returns a permutation vector p such that A(p,p) would have less zero fill-in during Cholesky factorization.

Declaration

public void CsrsymamdHost(int n, int nnzA, CudaSparseMatrixDescriptor descrA, int[] csrRowPtrA, int[] csrColIndA, int[] p)

Parameters

Type	Name	Description
System.Int32	n	number of rows and columns of matrix A.
System.Int32	nnzA	number of nonzeros of matrix A. It is the size of csrValA and csrColIndA.
CudaSparseMatrixDescriptor	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.
System.Int32[]	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
System.Int32[]	csrColIndA	integer array of nnz (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
System.Int32[]	p	permutation vector of size n.

CsrsymmdqHost(Int32, Int32, CudaSparseMatrixDescriptor, Int32[], Int32[], Int32[])

Symmetric minimum degree algorithm based on quotient graph.

This function implements Symmetric Minimum Degree Algorithm based on Quotient Graph. It returns a permutation vector p such that A(p,p) would have less zero fill-in during Cholesky factorization.

Declaration

public void CsrsymmdqHost(int n, int nnzA, CudaSparseMatrixDescriptor descrA, int[] csrRowPtrA, int[] csrColIndA, int[] p)

Parameters

Type	Name	Description
System.Int32	n	number of rows and columns of matrix A.
System.Int32	nnzA	number of nonzeros of matrix A. It is the size of csrValA and csrColIndA.
CudaSparseMatrixDescriptor	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.
System.Int32[]	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
System.Int32[]	csrColIndA	integer array of nnz (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
System.Int32[]	p	permutation vector of size n.

CsrsymrcmHost(Int32, Int32, CudaSparseMatrixDescriptor, Int32[], Int32[], Int32[])

This function implements Symmetric Reverse Cuthill-McKee permutation. It returns a permutation vector p such that A(p,p) would concentrate nonzeros to diagonal. This is equivalent to symrcm in MATLAB, however the result may not be the same because of different heuristics in the pseudoperipheral finder.

Declaration

public void CsrsymrcmHost(int n, int nnzA, CudaSparseMatrixDescriptor descrA, int[] csrRowPtrA, int[] csrColIndA, int[] p)

Parameters

Type	Name	Description
System.Int32	n	number of rows and columns of matrix A.
System.Int32	nnzA	number of nonzeros of matrix A. It is the size of csrValA and csrColIndA.
CudaSparseMatrixDescriptor	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.
System.Int32[]	csrRowPtrA	integer array of n + 1 elements that contains the start of every row and the end of the last row plus one.
System.Int32[]	csrColIndA	integer array of nnz (=csrRowPtrA(n) * csrRowPtrA(0)) column indices of the nonzero elements of matrix A.
System.Int32[]	p	permutation vector of size n.

Dispose()

Dispose

Declaration

public void Dispose()

Dispose(Boolean)

For IDisposable

Declaration

protected virtual void Dispose(bool fDisposing)

Parameters

Type	Name	Description
System.Boolean	fDisposing

Finalize()

For dispose

Declaration

protected void Finalize()

GetStream()

This function gets the stream to be used by the cuSolverSP library to execute its routines.

Declaration

public CudaStream GetStream()

Returns

Type	Description
CudaStream

SetStream(CudaStream)

This function sets the stream to be used by the cuSolverSP library to execute its routines.

Declaration

public void SetStream(CudaStream stream)

Parameters

Type	Name	Description
CudaStream	stream	the stream to be used by the library.

Implements

System.IDisposable