la_lapack_solve_aux Module Reference

Linear solve helpers: condition estimation, componentwise backward error. More...

Functions/Subroutines
pure subroutine, public	la_slacn2 (n, v, x, isgn, est, kase, isave)
	SLACN2: estimates the 1-norm of a square, real matrix A. Reverse communication is used for evaluating matrix-vector products.
pure subroutine, public	la_dlacn2 (n, v, x, isgn, est, kase, isave)
	DLACN2: estimates the 1-norm of a square, real matrix A. Reverse communication is used for evaluating matrix-vector products.
pure subroutine, public	la_qlacn2 (n, v, x, isgn, est, kase, isave)
	QLACN2: estimates the 1-norm of a square, real matrix A. Reverse communication is used for evaluating matrix-vector products.
subroutine, public	la_slacon (n, v, x, isgn, est, kase)
	SLACON: estimates the 1-norm of a square, real matrix A. Reverse communication is used for evaluating matrix-vector products.
subroutine, public	la_dlacon (n, v, x, isgn, est, kase)
	DLACON: estimates the 1-norm of a square, real matrix A. Reverse communication is used for evaluating matrix-vector products.
subroutine, public	la_qlacon (n, v, x, isgn, est, kase)
	QLACON: estimates the 1-norm of a square, real matrix A. Reverse communication is used for evaluating matrix-vector products.
pure subroutine, public	la_sla_lin_berr (n, nz, nrhs, res, ayb, berr)
	SLA_LIN_BERR: computes componentwise relative backward error from the formula max(i) ( abs(R(i)) / ( abs(op(A_s))*abs(Y) + abs(B_s) )(i) ) where abs(Z) is the componentwise absolute value of the matrix or vector Z.
pure subroutine, public	la_dla_lin_berr (n, nz, nrhs, res, ayb, berr)
	DLA_LIN_BERR: computes component-wise relative backward error from the formula max(i) ( abs(R(i)) / ( abs(op(A_s))*abs(Y) + abs(B_s) )(i) ) where abs(Z) is the component-wise absolute value of the matrix or vector Z.
pure subroutine, public	la_qla_lin_berr (n, nz, nrhs, res, ayb, berr)
	QLA_LIN_BERR: computes component-wise relative backward error from the formula max(i) ( abs(R(i)) / ( abs(op(A_s))*abs(Y) + abs(B_s) )(i) ) where abs(Z) is the component-wise absolute value of the matrix or vector Z.
pure subroutine, public	la_cla_lin_berr (n, nz, nrhs, res, ayb, berr)
	CLA_LIN_BERR: computes componentwise relative backward error from the formula max(i) ( abs(R(i)) / ( abs(op(A_s))*abs(Y) + abs(B_s) )(i) ) where abs(Z) is the componentwise absolute value of the matrix or vector Z.
pure subroutine, public	la_zla_lin_berr (n, nz, nrhs, res, ayb, berr)
	ZLA_LIN_BERR: computes componentwise relative backward error from the formula max(i) ( abs(R(i)) / ( abs(op(A_s))*abs(Y) + abs(B_s) )(i) ) where abs(Z) is the componentwise absolute value of the matrix or vector Z.
pure subroutine, public	la_wla_lin_berr (n, nz, nrhs, res, ayb, berr)
	WLA_LIN_BERR: computes componentwise relative backward error from the formula max(i) ( abs(R(i)) / ( abs(op(A_s))*abs(Y) + abs(B_s) )(i) ) where abs(Z) is the componentwise absolute value of the matrix or vector Z.
pure subroutine, public	la_clacn2 (n, v, x, est, kase, isave)
	CLACN2: estimates the 1-norm of a square, complex matrix A. Reverse communication is used for evaluating matrix-vector products.
pure subroutine, public	la_zlacn2 (n, v, x, est, kase, isave)
	ZLACN2: estimates the 1-norm of a square, complex matrix A. Reverse communication is used for evaluating matrix-vector products.
pure subroutine, public	la_wlacn2 (n, v, x, est, kase, isave)
	WLACN2: estimates the 1-norm of a square, complex matrix A. Reverse communication is used for evaluating matrix-vector products.
subroutine, public	la_clacon (n, v, x, est, kase)
	CLACON: estimates the 1-norm of a square, complex matrix A. Reverse communication is used for evaluating matrix-vector products.
subroutine, public	la_zlacon (n, v, x, est, kase)
	ZLACON: estimates the 1-norm of a square, complex matrix A. Reverse communication is used for evaluating matrix-vector products.
subroutine, public	la_wlacon (n, v, x, est, kase)
	WLACON: estimates the 1-norm of a square, complex matrix A. Reverse communication is used for evaluating matrix-vector products.

Detailed Description

Linear solve helpers: condition estimation, componentwise backward error.

Function/Subroutine Documentation

la_cla_lin_berr()

pure subroutine, public la_lapack_solve_aux::la_cla_lin_berr	(	integer(ilp), intent(in)	n,
		integer(ilp), intent(in)	nz,
		integer(ilp), intent(in)	nrhs,
		complex(sp), dimension(n,nrhs), intent(in)	res,
		real(sp), dimension(n,nrhs), intent(in)	ayb,
		real(sp), dimension(nrhs), intent(out)	berr )

CLA_LIN_BERR: computes componentwise relative backward error from the formula max(i) ( abs(R(i)) / ( abs(op(A_s))*abs(Y) + abs(B_s) )(i) ) where abs(Z) is the componentwise absolute value of the matrix or vector Z.

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la_clacn2()

pure subroutine, public la_lapack_solve_aux::la_clacn2	(	integer(ilp), intent(in)	n,
		complex(sp), dimension(*), intent(out)	v,
		complex(sp), dimension(*), intent(inout)	x,
		real(sp), intent(inout)	est,
		integer(ilp), intent(inout)	kase,
		integer(ilp), dimension(3), intent(inout)	isave )

CLACN2: estimates the 1-norm of a square, complex matrix A. Reverse communication is used for evaluating matrix-vector products.

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la_clacon()

subroutine, public la_lapack_solve_aux::la_clacon	(	integer(ilp), intent(in)	n,
		complex(sp), dimension(n), intent(out)	v,
		complex(sp), dimension(n), intent(inout)	x,
		real(sp), intent(inout)	est,
		integer(ilp), intent(inout)	kase )

CLACON: estimates the 1-norm of a square, complex matrix A. Reverse communication is used for evaluating matrix-vector products.

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la_dla_lin_berr()

pure subroutine, public la_lapack_solve_aux::la_dla_lin_berr	(	integer(ilp), intent(in)	n,
		integer(ilp), intent(in)	nz,
		integer(ilp), intent(in)	nrhs,
		real(dp), dimension(n,nrhs), intent(in)	res,
		real(dp), dimension(n,nrhs), intent(in)	ayb,
		real(dp), dimension(nrhs), intent(out)	berr )

DLA_LIN_BERR: computes component-wise relative backward error from the formula max(i) ( abs(R(i)) / ( abs(op(A_s))*abs(Y) + abs(B_s) )(i) ) where abs(Z) is the component-wise absolute value of the matrix or vector Z.

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la_dlacn2()

pure subroutine, public la_lapack_solve_aux::la_dlacn2	(	integer(ilp), intent(in)	n,
		real(dp), dimension(*), intent(out)	v,
		real(dp), dimension(*), intent(inout)	x,
		integer(ilp), dimension(*), intent(out)	isgn,
		real(dp), intent(inout)	est,
		integer(ilp), intent(inout)	kase,
		integer(ilp), dimension(3), intent(inout)	isave )

DLACN2: estimates the 1-norm of a square, real matrix A. Reverse communication is used for evaluating matrix-vector products.

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la_dlacon()

subroutine, public la_lapack_solve_aux::la_dlacon	(	integer(ilp), intent(in)	n,
		real(dp), dimension(*), intent(out)	v,
		real(dp), dimension(*), intent(inout)	x,
		integer(ilp), dimension(*), intent(out)	isgn,
		real(dp), intent(inout)	est,
		integer(ilp), intent(inout)	kase )

DLACON: estimates the 1-norm of a square, real matrix A. Reverse communication is used for evaluating matrix-vector products.

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la_qla_lin_berr()

pure subroutine, public la_lapack_solve_aux::la_qla_lin_berr	(	integer(ilp), intent(in)	n,
		integer(ilp), intent(in)	nz,
		integer(ilp), intent(in)	nrhs,
		real(qp), dimension(n,nrhs), intent(in)	res,
		real(qp), dimension(n,nrhs), intent(in)	ayb,
		real(qp), dimension(nrhs), intent(out)	berr )

QLA_LIN_BERR: computes component-wise relative backward error from the formula max(i) ( abs(R(i)) / ( abs(op(A_s))*abs(Y) + abs(B_s) )(i) ) where abs(Z) is the component-wise absolute value of the matrix or vector Z.

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la_qlacn2()

pure subroutine, public la_lapack_solve_aux::la_qlacn2	(	integer(ilp), intent(in)	n,
		real(qp), dimension(*), intent(out)	v,
		real(qp), dimension(*), intent(inout)	x,
		integer(ilp), dimension(*), intent(out)	isgn,
		real(qp), intent(inout)	est,
		integer(ilp), intent(inout)	kase,
		integer(ilp), dimension(3), intent(inout)	isave )

QLACN2: estimates the 1-norm of a square, real matrix A. Reverse communication is used for evaluating matrix-vector products.

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la_qlacon()

subroutine, public la_lapack_solve_aux::la_qlacon	(	integer(ilp), intent(in)	n,
		real(qp), dimension(*), intent(out)	v,
		real(qp), dimension(*), intent(inout)	x,
		integer(ilp), dimension(*), intent(out)	isgn,
		real(qp), intent(inout)	est,
		integer(ilp), intent(inout)	kase )

QLACON: estimates the 1-norm of a square, real matrix A. Reverse communication is used for evaluating matrix-vector products.

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la_sla_lin_berr()

pure subroutine, public la_lapack_solve_aux::la_sla_lin_berr	(	integer(ilp), intent(in)	n,
		integer(ilp), intent(in)	nz,
		integer(ilp), intent(in)	nrhs,
		real(sp), dimension(n,nrhs), intent(in)	res,
		real(sp), dimension(n,nrhs), intent(in)	ayb,
		real(sp), dimension(nrhs), intent(out)	berr )

SLA_LIN_BERR: computes componentwise relative backward error from the formula max(i) ( abs(R(i)) / ( abs(op(A_s))*abs(Y) + abs(B_s) )(i) ) where abs(Z) is the componentwise absolute value of the matrix or vector Z.

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la_slacn2()

pure subroutine, public la_lapack_solve_aux::la_slacn2	(	integer(ilp), intent(in)	n,
		real(sp), dimension(*), intent(out)	v,
		real(sp), dimension(*), intent(inout)	x,
		integer(ilp), dimension(*), intent(out)	isgn,
		real(sp), intent(inout)	est,
		integer(ilp), intent(inout)	kase,
		integer(ilp), dimension(3), intent(inout)	isave )

SLACN2: estimates the 1-norm of a square, real matrix A. Reverse communication is used for evaluating matrix-vector products.

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la_slacon()

subroutine, public la_lapack_solve_aux::la_slacon	(	integer(ilp), intent(in)	n,
		real(sp), dimension(*), intent(out)	v,
		real(sp), dimension(*), intent(inout)	x,
		integer(ilp), dimension(*), intent(out)	isgn,
		real(sp), intent(inout)	est,
		integer(ilp), intent(inout)	kase )

SLACON: estimates the 1-norm of a square, real matrix A. Reverse communication is used for evaluating matrix-vector products.

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la_wla_lin_berr()

pure subroutine, public la_lapack_solve_aux::la_wla_lin_berr	(	integer(ilp), intent(in)	n,
		integer(ilp), intent(in)	nz,
		integer(ilp), intent(in)	nrhs,
		complex(qp), dimension(n,nrhs), intent(in)	res,
		real(qp), dimension(n,nrhs), intent(in)	ayb,
		real(qp), dimension(nrhs), intent(out)	berr )

WLA_LIN_BERR: computes componentwise relative backward error from the formula max(i) ( abs(R(i)) / ( abs(op(A_s))*abs(Y) + abs(B_s) )(i) ) where abs(Z) is the componentwise absolute value of the matrix or vector Z.

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la_wlacn2()

pure subroutine, public la_lapack_solve_aux::la_wlacn2	(	integer(ilp), intent(in)	n,
		complex(qp), dimension(*), intent(out)	v,
		complex(qp), dimension(*), intent(inout)	x,
		real(qp), intent(inout)	est,
		integer(ilp), intent(inout)	kase,
		integer(ilp), dimension(3), intent(inout)	isave )

WLACN2: estimates the 1-norm of a square, complex matrix A. Reverse communication is used for evaluating matrix-vector products.

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la_wlacon()

subroutine, public la_lapack_solve_aux::la_wlacon	(	integer(ilp), intent(in)	n,
		complex(qp), dimension(n), intent(out)	v,
		complex(qp), dimension(n), intent(inout)	x,
		real(qp), intent(inout)	est,
		integer(ilp), intent(inout)	kase )

WLACON: estimates the 1-norm of a square, complex matrix A. Reverse communication is used for evaluating matrix-vector products.

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la_zla_lin_berr()

pure subroutine, public la_lapack_solve_aux::la_zla_lin_berr	(	integer(ilp), intent(in)	n,
		integer(ilp), intent(in)	nz,
		integer(ilp), intent(in)	nrhs,
		complex(dp), dimension(n,nrhs), intent(in)	res,
		real(dp), dimension(n,nrhs), intent(in)	ayb,
		real(dp), dimension(nrhs), intent(out)	berr )

ZLA_LIN_BERR: computes componentwise relative backward error from the formula max(i) ( abs(R(i)) / ( abs(op(A_s))*abs(Y) + abs(B_s) )(i) ) where abs(Z) is the componentwise absolute value of the matrix or vector Z.

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la_zlacn2()

pure subroutine, public la_lapack_solve_aux::la_zlacn2	(	integer(ilp), intent(in)	n,
		complex(dp), dimension(*), intent(out)	v,
		complex(dp), dimension(*), intent(inout)	x,
		real(dp), intent(inout)	est,
		integer(ilp), intent(inout)	kase,
		integer(ilp), dimension(3), intent(inout)	isave )

ZLACN2: estimates the 1-norm of a square, complex matrix A. Reverse communication is used for evaluating matrix-vector products.

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la_zlacon()

subroutine, public la_lapack_solve_aux::la_zlacon	(	integer(ilp), intent(in)	n,
		complex(dp), dimension(n), intent(out)	v,
		complex(dp), dimension(n), intent(inout)	x,
		real(dp), intent(inout)	est,
		integer(ilp), intent(inout)	kase )

ZLACON: estimates the 1-norm of a square, complex matrix A. Reverse communication is used for evaluating matrix-vector products.

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