Developer Reference for Intel® oneAPI Math Kernel Library for Fortran
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?la_porpvgrw
Computes the reciprocal pivot growth factor norm(A)/norm(U) for a symmetric or Hermitian positive-definite matrix.
Syntax
call sla_porpvgrw( uplo, ncols, a, lda, af, ldaf, work )
call dla_porpvgrw( uplo, ncols, a, lda, af, ldaf, work )
call cla_porpvgrw( uplo, ncols, a, lda, af, ldaf, work )
call zla_porpvgrw( uplo, ncols, a, lda, af, ldaf, work )
Include Files
- mkl.fi
 
Description
The ?la_porpvgrw routine computes the reciprocal pivot growth factor norm(A)/norm(U). The max absolute element norm is used. If this is much less than 1, the stability of the LU factorization of the equilibrated matrix A could be poor. This also means that the solution X, estimated condition numbers, and error bounds could be unreliable.
Input Parameters
uplo  |  
      CHARACTER*1. Must be 'U' or 'L'. Specifies the triangle of A to store: If uplo = 'U', the upper triangle of A is stored, If uplo = 'L', the lower triangle of A is stored.  |  
     |
ncols  |  
      INTEGER. The number of columns of the matrix A; ncols≥ 0.  |  
     |
a, af  |  
      REAL for sla_porpvgrw DOUBLE PRECISION for dla_porpvgrw COMPLEX for cla_porpvgrw DOUBLE COMPLEX for zla_porpvgrw. Arrays: a(lda,*), af(ldaf,*). The array a contains the input n-by-n matrix A. The second dimension of a must be at least max(1,n). The array af contains the triangular factor L or U from the Cholesky factorization as computed by ?potrf: A = UT*U or A = L*LT for real flavors, A = UH*U or A = L*LH for complex flavors.  |  
      The second dimension of af must be at least max(1,n). | 
lda  |  
      INTEGER. The leading dimension of a; lda≥ max(1,n).  |  
     |
ldaf  |  
      INTEGER. The leading dimension of af; ldaf≥ max(1,n).  |  
     |
work  |  
      REAL for sla_porpvgrw and cla_porpvgrw DOUBLE PRECISION for dla_porpvgrw and zla_porpvgrw. Workspace array, dimension 2*n.  |