HP MLIB User's Guide Vol. 2 7th Ed.

Chapter 14 METIS Routines 995
Computes fill reducing orderings of sparse matrices mlib_METIS_NodeWND
Name mlib_METIS_NodeWND
Computes fill reducing orderings of sparse matrices
Purpose This function computes fill reducing orderings of sparse matrices using the
multilevel nested dissection algorithm. It is similar to mlib_METIS_NodeND,
but it assumes that the compression has been performed prior to calling this
routine. It is particularly suited for ordering very large matrices in which the
compressed matrix is previously known.
Usage VECLIB:
void mlib_METIS_NodeWND (int *n, int *xadj, int *adjncy, int *vwgt, int
*numflag, int *options, int *perm, int *iperm)
VECLIB8:
void mlib_METIS_NodeWND (long long *n, long long *xadj, long long
*adjncy, long long *vwgt, long long *numflag, long long *options, long
long *perm, long long *iperm)
Arguments n The number of vertices in the graph.
xadj,
adjncy
The adjacency structure of the graph.
vwgt The weight of the vertices.
numflag Used to indicate which numbering scheme is used for
the adjacency structure of the graph. numflag can take
the following two values:
0—C-Style numbering is assumed that starts from 0
1—Fortran-style numbering is assumed that starts
from 1
options This is an array of 5 integers that is used to pass
parameters for the various phases of the algorithm. If
options[0]=0 then default values are used. If
options[0]=1 then the remaining 4 elements of options
are interpreted as follows:
options[1] Determines matching type. Possible values
are:
1—Random Matching (RM)
2—Heavy-Edge Matching (HEM)
3—Sorted Heavy-Edge Matching (SHEM)(Default)
Experiments have shown that all three matching
schemes perform quite well. In general, SHEM is faster