Developer Reference for Intel® oneAPI Math Kernel Library for C

ID 766684
Date 6/24/2024
Public

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?porfs

Refines the solution of a system of linear equations with a symmetric (Hermitian) positive-definite coefficient matrix and estimates its error.

Syntax

lapack_int LAPACKE_sporfs( int matrix_layout, char uplo, lapack_int n, lapack_int nrhs, const float* a, lapack_int lda, const float* af, lapack_int ldaf, const float* b, lapack_int ldb, float* x, lapack_int ldx, float* ferr, float* berr );

lapack_int LAPACKE_dporfs( int matrix_layout, char uplo, lapack_int n, lapack_int nrhs, const double* a, lapack_int lda, const double* af, lapack_int ldaf, const double* b, lapack_int ldb, double* x, lapack_int ldx, double* ferr, double* berr );

lapack_int LAPACKE_cporfs( int matrix_layout, char uplo, lapack_int n, lapack_int nrhs, const lapack_complex_float* a, lapack_int lda, const lapack_complex_float* af, lapack_int ldaf, const lapack_complex_float* b, lapack_int ldb, lapack_complex_float* x, lapack_int ldx, float* ferr, float* berr );

lapack_int LAPACKE_zporfs( int matrix_layout, char uplo, lapack_int n, lapack_int nrhs, const lapack_complex_double* a, lapack_int lda, const lapack_complex_double* af, lapack_int ldaf, const lapack_complex_double* b, lapack_int ldb, lapack_complex_double* x, lapack_int ldx, double* ferr, double* berr );

Include Files

  • mkl.h

Description

The routine performs an iterative refinement of the solution to a system of linear equations A*X = B with a symmetric (Hermitian) positive definite matrix A, with multiple right-hand sides. For each computed solution vector x, the routine computes the component-wise backward errorβ. This error is the smallest relative perturbation in elements of A and b such that x is the exact solution of the perturbed system:

|δaij| β|aij|, |δbi| β|bi| such that (A + δA)x = (b + δb).

Finally, the routine estimates the component-wise forward error in the computed solution ||x - xe||/||x|| (here xe is the exact solution).

Before calling this routine:

  • call the factorization routine ?potrf

  • call the solver routine ?potrs.

Input Parameters

matrix_layout

Specifies whether matrix storage layout is row major (LAPACK_ROW_MAJOR) or column major (LAPACK_COL_MAJOR).

uplo

Must be 'U' or 'L'.

If uplo = 'U', the upper triangle of A is stored.

If uplo = 'L', the lower triangle of A is stored.

n

The order of the matrix A; n 0.

nrhs

The number of right-hand sides; nrhs 0.

a

Array a (size max(1, lda*n)) contains the original matrix A, as supplied to ?potrf.

af

Array af (size max(1, ldaf*n)) contains the factored matrix A, as returned by ?potrf.

b

Array bof size max(1, ldb*nrhs) for column major layout and max(1, ldb*n) for row major layout contains the right-hand side matrix B. The second dimension of b must be at least max(1, nrhs).

x

Array x of size max(1, ldx*nrhs) for column major layout and max(1, ldx*n) for row major layout contains the solution matrix X.

lda

The leading dimension of a; lda max(1, n).

ldaf

The leading dimension of af; ldaf max(1, n).

ldb

The leading dimension of b; ldb max(1, n) for column major layout and ldbnrhs for row major layout.

ldx

The leading dimension of x; ldx max(1, n) for column major layout and ldxnrhs for row major layout.

Output Parameters

x

The refined solution matrix X.

ferr, berr

Arrays, size at least max(1, nrhs). Contain the component-wise forward and backward errors, respectively, for each solution vector.

Return Values

This function returns a value info.

If info = 0, the execution is successful.

If info = -i, parameter i had an illegal value.

Application Notes

The bounds returned in ferr are not rigorous, but in practice they almost always overestimate the actual error.

For each right-hand side, computation of the backward error involves a minimum of 4n2 floating-point operations (for real flavors) or 16n2 operations (for complex flavors). In addition, each step of iterative refinement involves 6n2 operations (for real flavors) or 24n2 operations (for complex flavors); the number of iterations may range from 1 to 5. Estimating the forward error involves solving a number of systems of linear equations A*x = b; the number is usually 4 or 5 and never more than 11. Each solution requires approximately 2n2 floating-point operations for real flavors or 8n2 for complex flavors.