SpM Handbook: Spm_dev

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Norm computation routines. More...

Files
file	c_spm_norm.c

file	s_spm_norm.c

file	z_spm_norm.c

file	d_spm_norm.c

Functions
float	s_spmNorm (spm_normtype_t ntype, const spmatrix_t *spm)
	Compute the norm of an spm matrix.

float	s_spmNormMat (spm_normtype_t ntype, const spmatrix_t spm, spm_int_t n, const float A, spm_int_t lda)
	Compute the norm of a dense matrix that follows the distribution of an spm matrix.

double	d_spmNorm (spm_normtype_t ntype, const spmatrix_t *spm)
	Compute the norm of an spm matrix.

double	d_spmNormMat (spm_normtype_t ntype, const spmatrix_t spm, spm_int_t n, const double A, spm_int_t lda)
	Compute the norm of a dense matrix that follows the distribution of an spm matrix.

float	c_spmNorm (spm_normtype_t ntype, const spmatrix_t *spm)
	Compute the norm of an spm matrix.

float	c_spmNormMat (spm_normtype_t ntype, const spmatrix_t spm, spm_int_t n, const spm_complex32_t A, spm_int_t lda)
	Compute the norm of a dense matrix that follows the distribution of an spm matrix.

double	z_spmNorm (spm_normtype_t ntype, const spmatrix_t *spm)
	Compute the norm of an spm matrix.

double	z_spmNormMat (spm_normtype_t ntype, const spmatrix_t spm, spm_int_t n, const spm_complex64_t A, spm_int_t lda)
	Compute the norm of a dense matrix that follows the distribution of an spm matrix.

Detailed Description

Norm computation routines.

Function Documentation

◆ s_spmNorm()

float s_spmNorm	(	spm_normtype_t	ntype,
		const spmatrix_t *	spm
	)

Compute the norm of an spm matrix.

Parameters

[in]	ntype	= SpmMaxNorm: Max norm = SpmOneNorm: One norm = SpmInfNorm: Infinity norm = SpmFrobeniusNorm: Frobenius norm
[in]	spm	The spm structure describing the matrix.

Returns: The norm of the spm matrix -1 when error occurs or with pattern only

Definition at line 1214 of file s_spm_norm.c.

References s_spmFrobeniusNorm(), s_spmMaxNorm(), s_spmOneInfNorm(), SpmFrobeniusNorm, SpmInfNorm, SpmMaxNorm, and SpmOneNorm.

Referenced by s_spmGenRHS(), and spmNorm().

◆ s_spmNormMat()

float s_spmNormMat	(	spm_normtype_t	ntype,
		const spmatrix_t *	spm,
		spm_int_t	n,
		const float *	A,
		spm_int_t	lda
	)

Compute the norm of a dense matrix that follows the distribution of an spm matrix.

Parameters

[in]	ntype	= SpmMaxNorm: Max norm = SpmOneNorm: One norm = SpmInfNorm: Infinity norm = SpmFrobeniusNorm: Frobenius norm
[in]	spm	The spm structure describing the matrix.
[in]	n	The number of columns of the matrix A.
[in]	A	The matrix A of size lda-by-n.
[in]	lda	The leading dimension of the matrix A. Must be >= max(1, spm->nexp).

Returns: The norm of the spm matrix -1 when error occurs or with pattern only

Definition at line 1278 of file s_spm_norm.c.

References spmatrix_s::clustnbr, spmatrix_s::comm, LAPACKE_slassq_work, spmatrix_s::nexp, spmatrix_s::replicated, SpmFrobeniusNorm, SpmInfNorm, SpmMaxNorm, and SpmOneNorm.

Referenced by s_spmCheckAxb(), spmNormMat(), and spmNormVec().

◆ d_spmNorm()

double d_spmNorm	(	spm_normtype_t	ntype,
		const spmatrix_t *	spm
	)

Compute the norm of an spm matrix.

Parameters

[in]	ntype	= SpmMaxNorm: Max norm = SpmOneNorm: One norm = SpmInfNorm: Infinity norm = SpmFrobeniusNorm: Frobenius norm
[in]	spm	The spm structure describing the matrix.

Returns: The norm of the spm matrix -1 when error occurs or with pattern only

Definition at line 1214 of file d_spm_norm.c.

References d_spmFrobeniusNorm(), d_spmMaxNorm(), d_spmOneInfNorm(), SpmFrobeniusNorm, SpmInfNorm, SpmMaxNorm, and SpmOneNorm.

Referenced by d_spmGenRHS(), and spmNorm().

◆ d_spmNormMat()

double d_spmNormMat	(	spm_normtype_t	ntype,
		const spmatrix_t *	spm,
		spm_int_t	n,
		const double *	A,
		spm_int_t	lda
	)

Compute the norm of a dense matrix that follows the distribution of an spm matrix.

Parameters

[in]	ntype	= SpmMaxNorm: Max norm = SpmOneNorm: One norm = SpmInfNorm: Infinity norm = SpmFrobeniusNorm: Frobenius norm
[in]	spm	The spm structure describing the matrix.
[in]	n	The number of columns of the matrix A.
[in]	A	The matrix A of size lda-by-n.
[in]	lda	The leading dimension of the matrix A. Must be >= max(1, spm->nexp).

Returns: The norm of the spm matrix -1 when error occurs or with pattern only

Definition at line 1278 of file d_spm_norm.c.

References spmatrix_s::clustnbr, spmatrix_s::comm, LAPACKE_dlassq_work, spmatrix_s::nexp, spmatrix_s::replicated, SpmFrobeniusNorm, SpmInfNorm, SpmMaxNorm, and SpmOneNorm.

Referenced by d_spmCheckAxb(), spmNormMat(), and spmNormVec().

◆ c_spmNorm()

float c_spmNorm	(	spm_normtype_t	ntype,
		const spmatrix_t *	spm
	)

Compute the norm of an spm matrix.

Parameters

[in]	ntype	= SpmMaxNorm: Max norm = SpmOneNorm: One norm = SpmInfNorm: Infinity norm = SpmFrobeniusNorm: Frobenius norm
[in]	spm	The spm structure describing the matrix.

Returns: The norm of the spm matrix -1 when error occurs or with pattern only

Definition at line 1214 of file c_spm_norm.c.

References c_spmFrobeniusNorm(), c_spmMaxNorm(), c_spmOneInfNorm(), SpmFrobeniusNorm, SpmInfNorm, SpmMaxNorm, and SpmOneNorm.

Referenced by c_spmGenRHS(), and spmNorm().

◆ c_spmNormMat()

float c_spmNormMat	(	spm_normtype_t	ntype,
		const spmatrix_t *	spm,
		spm_int_t	n,
		const spm_complex32_t *	A,
		spm_int_t	lda
	)

Compute the norm of a dense matrix that follows the distribution of an spm matrix.

Parameters

[in]	ntype	= SpmMaxNorm: Max norm = SpmOneNorm: One norm = SpmInfNorm: Infinity norm = SpmFrobeniusNorm: Frobenius norm
[in]	spm	The spm structure describing the matrix.
[in]	n	The number of columns of the matrix A.
[in]	A	The matrix A of size lda-by-n.
[in]	lda	The leading dimension of the matrix A. Must be >= max(1, spm->nexp).

Returns: The norm of the spm matrix -1 when error occurs or with pattern only

Definition at line 1278 of file c_spm_norm.c.

References spmatrix_s::clustnbr, spmatrix_s::comm, LAPACKE_classq_work, spmatrix_s::nexp, spmatrix_s::replicated, SpmFrobeniusNorm, SpmInfNorm, SpmMaxNorm, and SpmOneNorm.

Referenced by c_spmCheckAxb(), spmNormMat(), and spmNormVec().

◆ z_spmNorm()

double z_spmNorm	(	spm_normtype_t	ntype,
		const spmatrix_t *	spm
	)

Compute the norm of an spm matrix.

Parameters

[in]	ntype	= SpmMaxNorm: Max norm = SpmOneNorm: One norm = SpmInfNorm: Infinity norm = SpmFrobeniusNorm: Frobenius norm
[in]	spm	The spm structure describing the matrix.

Returns: The norm of the spm matrix -1 when error occurs or with pattern only

Definition at line 1214 of file z_spm_norm.c.

References SpmFrobeniusNorm, SpmInfNorm, SpmMaxNorm, SpmOneNorm, z_spmFrobeniusNorm(), z_spmMaxNorm(), and z_spmOneInfNorm().

Referenced by spmNorm(), and z_spmGenRHS().

◆ z_spmNormMat()

double z_spmNormMat	(	spm_normtype_t	ntype,
		const spmatrix_t *	spm,
		spm_int_t	n,
		const spm_complex64_t *	A,
		spm_int_t	lda
	)

Compute the norm of a dense matrix that follows the distribution of an spm matrix.

Parameters

[in]	ntype	= SpmMaxNorm: Max norm = SpmOneNorm: One norm = SpmInfNorm: Infinity norm = SpmFrobeniusNorm: Frobenius norm
[in]	spm	The spm structure describing the matrix.
[in]	n	The number of columns of the matrix A.
[in]	A	The matrix A of size lda-by-n.
[in]	lda	The leading dimension of the matrix A. Must be >= max(1, spm->nexp).

Returns: The norm of the spm matrix -1 when error occurs or with pattern only

Definition at line 1278 of file z_spm_norm.c.

References spmatrix_s::clustnbr, spmatrix_s::comm, LAPACKE_zlassq_work, spmatrix_s::nexp, spmatrix_s::replicated, SpmFrobeniusNorm, SpmInfNorm, SpmMaxNorm, and SpmOneNorm.

Referenced by spmNormMat(), spmNormVec(), and z_spmCheckAxb().

Files

Functions

Detailed Description

Function Documentation

◆ s_spmNorm()

◆ s_spmNormMat()

◆ d_spmNorm()

◆ d_spmNormMat()

◆ c_spmNorm()

◆ c_spmNormMat()

◆ z_spmNorm()

◆ z_spmNormMat()