lapack.h File Reference

interface methods for eigenvector computation and matrix multiplication using different versions of LAPACK and BLAS More...

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Functions
EXTERN SCIP_RETCODE	SCIPlapackComputeIthEigenvalue (BMS_BUFMEM *bufmem, SCIP_Bool geteigenvectors, int n, SCIP_Real *A, int i, SCIP_Real *eigenvalue, SCIP_Real *eigenvector)
EXTERN SCIP_RETCODE	SCIPlapackComputeEigenvectorDecomposition (BMS_BUFMEM *bufmem, int n, SCIP_Real *A, SCIP_Real *eigenvalues, SCIP_Real *eigenvectors)
EXTERN SCIP_RETCODE	SCIPlapackMatrixVectorMult (int nrows, int ncols, SCIP_Real *matrix, SCIP_Real *vector, SCIP_Real *result)
EXTERN SCIP_RETCODE	SCIPlapackMatrixMatrixMult (int nrowsA, int ncolsA, SCIP_Real *matrixA, SCIP_Bool transposeA, int nrowsB, int ncolsB, SCIP_Real *matrixB, SCIP_Bool transposeB, SCIP_Real *result)

Detailed Description

interface methods for eigenvector computation and matrix multiplication using different versions of LAPACK and BLAS

Author

Tristan Gally

This file is used to call the LAPACK routine DSYEVR (double-symmetric-eigenvector computation) and the BLAS routine DGEMV (double-general-matrix-vector multiplication). It is needed because different SDP-solvers need different BLAS/LAPACK-versions with different data types (for example long long int for Openblas/SDPA vs. int for ATLAS/DSDP).

Definition in file lapack.h.

Function Documentation

EXTERN SCIP_RETCODE SCIPlapackComputeIthEigenvalue	(	BMS_BUFMEM *	bufmem,
		SCIP_Bool	geteigenvectors,
		int	n,
		SCIP_Real *	A,
		int	i,
		SCIP_Real *	eigenvalue,
		SCIP_Real *	eigenvector
	)

computes the i-th eigenvalue of a symmetric matrix using LAPACK, where 1 is the smallest and n the largest, matrix has to be given with all entries

Parameters

bufmem	buffer memory
geteigenvectors	should also the eigenvectors be computed?
n	size of matrix
A	matrix for which eigenvalues should be computed
i	index of eigenvalue to be computed
eigenvalue	pointer to store eigenvalue
eigenvector	pointer to store eigenvector

Referenced by checkFixedFeasibilitySdp(), cutUsingEigenvector(), SCIP_DECL_CONSLOCK(), SCIPconsSdpCheckSdpCons(), and SCIPsdpSolcheckerCheck().

EXTERN SCIP_RETCODE SCIPlapackComputeEigenvectorDecomposition	(	BMS_BUFMEM *	bufmem,
		int	n,
		SCIP_Real *	A,
		SCIP_Real *	eigenvalues,
		SCIP_Real *	eigenvectors
	)

computes the eigenvector decomposition of a symmetric matrix using LAPACK

Parameters

bufmem	buffer memory
n	size of matrix
A	matrix for which the decomposition should be computed
eigenvalues	pointer to store eigenvalues (should be length n)
eigenvectors	pointer to store eigenvectors (should be length n*n), eigenvectors are given as rows

Definition at line 220 of file lapack_dsdp.c.

References BMS_CALL, F77_FUNC, and SCIP_RealTOINT.

Referenced by calcRelax().

EXTERN SCIP_RETCODE SCIPlapackMatrixVectorMult	(	int	nrows,
		int	ncols,
		SCIP_Real *	matrix,
		SCIP_Real *	vector,
		SCIP_Real *	result
	)

performs matrix-vector-multiplication using BLAS

Parameters

nrows	number of rows in matrix
ncols	number of cols in matrix
matrix	the matrix we want to multiply
vector	vector we want to multiply with the matrix
result	pointer to store the resulting vector

Definition at line 322 of file lapack_dsdp.c.

References F77_FUNC.

Referenced by cutUsingEigenvector().

EXTERN SCIP_RETCODE SCIPlapackMatrixMatrixMult	(	int	nrowsA,
		int	ncolsA,
		SCIP_Real *	matrixA,
		SCIP_Bool	transposeA,
		int	nrowsB,
		int	ncolsB,
		SCIP_Real *	matrixB,
		SCIP_Bool	transposeB,
		SCIP_Real *	result
	)

performs matrix-matrix-multiplication A*B using BLAS

Parameters

nrowsA	number of rows in matrix A
ncolsA	number of cols in matrix A
matrixA	matrix A given as nrowsA * ncolsA array
transposeA	should matrix A be transposed before multiplication?
nrowsB	number of rows in matrix B
ncolsB	number of cols in matrix B
matrixB	matrix B given as ncolsA * ncolsB array
transposeB	should matrix B be transposed before multiplication?
result	pointer to nrowsA * nrowsB array to store the resulting matrix

Definition at line 360 of file lapack_dsdp.c.

References F77_FUNC.

Referenced by calcRelax().