PARDISO Advanced Factorization VI

Owning Palette: Sparse Linear Algebra VIs

Requires: Multicore Analysis and Sparse Matrix Toolkit

Performs numerical factorization on the specified PARDISO session.

You can perform numerical factorization either on the sparse matrix specified in PARDISO Advanced Initialization VI or on a sparse matrix which has identical size and sparsity pattern. You must initialize the PARDISO session using the PARDISO Advanced Initialization VI before performing numerical factorization.

Details  

PARDISO Advanced Factorization (DBL)

	solver ID in specifies the identification number associated with the PARDISO session.
	Input Matrix specifies a square sparse matrix to perform numerical factorization. If Input Matrix is not wired, LabVIEW performs numerical factorization on the sparse matrix specified in PARDISO Advanced Initialization VI. If Input Matrix is wired, LabVIEW performs numerical factorization on this sparse matrix using the analysis result from PARDISO Advanced Initialization VI. Input Matrix must have the same size and sparsity pattern as the sparse matrix specified in PARDISO Advanced Initialization VI.
	error in describes error conditions that occur before this node runs. This input provides standard error in functionality.
	solver ID out returns solver ID in.
	Diagnostic Info returns diagnostic information. Permutation returns the permutation vector that PARDISO actually used. LabVIEW returns the permutation vector only when output permutation? is TRUE. # of iterative refinement returns the number of iterative refinement that PARDISO actually performed. # of nonzeros in LU returns the number of nonzeros in the factorization. peak memory [KB] on symbolic LU returns the peak memory in kilobytes that PARDISO needed on symbolic factorization. allocated memory [KB] on symbolic LU returns the memory, in kilobytes, that PARDISO actually allocated on symbolic factorization. allocated memory [KB] on LU returns the memory, in kilobytes, that PARDISO actually allocated on numerical factorization. MFlops on LU returns the number of floating-point operations, in MFlops, on factorization. LabVIEW returns MFlops only when output MFlops on LU? is TRUE. # of positive eigenvalues returns the number of positive eigenvalues when the Input Matrix is symmetric. # of negative eigenvalues returns the number of negative eigenvalues when the Input Matrix is symmetric.
	error out contains error information. This output provides standard error out functionality.

PARDISO Advanced Factorization (SGL)

	solver ID in specifies the identification number associated with the PARDISO session.
	Input Matrix specifies a square sparse matrix to perform numerical factorization. If Input Matrix is not wired, LabVIEW performs numerical factorization on the sparse matrix specified in PARDISO Advanced Initialization VI. If Input Matrix is wired, LabVIEW performs numerical factorization on this sparse matrix using the analysis result from PARDISO Advanced Initialization VI. Input Matrix must have the same size and sparsity pattern as the sparse matrix specified in PARDISO Advanced Initialization VI.
	error in describes error conditions that occur before this node runs. This input provides standard error in functionality.
	solver ID out returns solver ID in.
	Diagnostic Info returns diagnostic information. Permutation returns the permutation vector that PARDISO actually used. LabVIEW returns the permutation vector only when output permutation? is TRUE. # of iterative refinement returns the number of iterative refinement that PARDISO actually performed. # of nonzeros in LU returns the number of nonzeros in the factorization. peak memory [KB] on symbolic LU returns the peak memory in kilobytes that PARDISO needed on symbolic factorization. allocated memory [KB] on symbolic LU returns the memory, in kilobytes, that PARDISO actually allocated on symbolic factorization. allocated memory [KB] on LU returns the memory, in kilobytes, that PARDISO actually allocated on numerical factorization. MFlops on LU returns the number of floating-point operations, in MFlops, on factorization. LabVIEW returns MFlops only when output MFlops on LU? is TRUE. # of positive eigenvalues returns the number of positive eigenvalues when the Input Matrix is symmetric. # of negative eigenvalues returns the number of negative eigenvalues when the Input Matrix is symmetric.
	error out contains error information. This output provides standard error out functionality.

PARDISO Advanced Factorization (CDB)

	solver ID in specifies the identification number associated with the PARDISO session.
	Input Matrix specifies a square sparse matrix to perform numerical factorization. If Input Matrix is not wired, LabVIEW performs numerical factorization on the sparse matrix specified in PARDISO Advanced Initialization VI. If Input Matrix is wired, LabVIEW performs numerical factorization on this sparse matrix using the analysis result from PARDISO Advanced Initialization VI. Input Matrix must have the same size and sparsity pattern as the sparse matrix specified in PARDISO Advanced Initialization VI.
	error in describes error conditions that occur before this node runs. This input provides standard error in functionality.
	solver ID out returns solver ID in.
	Diagnostic Info returns diagnostic information. Permutation returns the permutation vector that PARDISO actually used. LabVIEW returns the permutation vector only when output permutation? is TRUE. # of iterative refinement returns the number of iterative refinement that PARDISO actually performed. # of nonzeros in LU returns the number of nonzeros in the factorization. peak memory [KB] on symbolic LU returns the peak memory in kilobytes that PARDISO needed on symbolic factorization. allocated memory [KB] on symbolic LU returns the memory, in kilobytes, that PARDISO actually allocated on symbolic factorization. allocated memory [KB] on LU returns the memory, in kilobytes, that PARDISO actually allocated on numerical factorization. MFlops on LU returns the number of floating-point operations, in MFlops, on factorization. LabVIEW returns MFlops only when output MFlops on LU? is TRUE. # of positive eigenvalues returns the number of positive eigenvalues when the Input Matrix is symmetric. # of negative eigenvalues returns the number of negative eigenvalues when the Input Matrix is symmetric.
	error out contains error information. This output provides standard error out functionality.

PARDISO Advanced Factorization (CSG)

	solver ID in specifies the identification number associated with the PARDISO session.
	Input Matrix specifies a square sparse matrix to perform numerical factorization. If Input Matrix is not wired, LabVIEW performs numerical factorization on the sparse matrix specified in PARDISO Advanced Initialization VI. If Input Matrix is wired, LabVIEW performs numerical factorization on this sparse matrix using the analysis result from PARDISO Advanced Initialization VI. Input Matrix must have the same size and sparsity pattern as the sparse matrix specified in PARDISO Advanced Initialization VI.
	error in describes error conditions that occur before this node runs. This input provides standard error in functionality.
	solver ID out returns solver ID in.
	Diagnostic Info returns diagnostic information. Permutation returns the permutation vector that PARDISO actually used. LabVIEW returns the permutation vector only when output permutation? is TRUE. # of iterative refinement returns the number of iterative refinement that PARDISO actually performed. # of nonzeros in LU returns the number of nonzeros in the factorization. peak memory [KB] on symbolic LU returns the peak memory in kilobytes that PARDISO needed on symbolic factorization. allocated memory [KB] on symbolic LU returns the memory, in kilobytes, that PARDISO actually allocated on symbolic factorization. allocated memory [KB] on LU returns the memory, in kilobytes, that PARDISO actually allocated on numerical factorization. MFlops on LU returns the number of floating-point operations, in MFlops, on factorization. LabVIEW returns MFlops only when output MFlops on LU? is TRUE. # of positive eigenvalues returns the number of positive eigenvalues when the Input Matrix is symmetric. # of negative eigenvalues returns the number of negative eigenvalues when the Input Matrix is symmetric.
	error out contains error information. This output provides standard error out functionality.

PARDISO Advanced Factorization Details

The following table lists the support characteristics of this VI.

Supported on RT targets	Yes
Suitable for bounded execution times on RT	No