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

Chapter 14 METIS Routines 991
Computes fill reducing orderings of sparse matrices mlib_METIS_EdgeND
1—Random Matching (RM)
2—Heavy-Edge Matching (HEM)
3—Sorted Heavy-Edge Matching (SHEM)(Default)
Experiments have shown that both HEM and SHEM
perform quite well.
options[2] Determines the algorithm used during
initial partioning. Possible values are:
1—Region Growing (Default)
options[3] Determines the algorithm used for
refinement. Possible values are:
1—Early-Exit Boundary FM Refinement (Default)
options[4] Used for debugging purposes. Always set it
to 0 (Default)
perm,
iperm
These are vectors, each of size n. Upon successful
completion, they store the fill-reducing permutation
and inverse-permutation. Let A be the original matrix
and A' be the permuted matrix. The arrays perm and
iperm are defined as follows: Row (column) i of A' is the
perm[i] row (column) of A, and row (column) i of A is
the iperm[i] row (column) of A'. The numbering of this
vector starts from either 0 or 1, depending on the value
of numflag.
Notes This function computes the vertex separator from the edge separator using a
minimum cover algorithm. This function should be used only in ordering large
graphs arising in 3D finite element applications. In general, the
mlib_METIS_NodeND routine should be perferred, as it produces better
orderings.