Adaptive cross approximation for MOM matrix fill for PC problem sizes to 157000 unknowns

Abstract

Recent work on sparse MOM codes for PC applications has reduced LU matrix factorization time to significantly less than matrix fill for problem unknowns approaching 200,000. This paper reports on the use and results of applying the recently developed adaptive cross approximation for significantly reducing MOM matrix fill time. Results suggest that when problem sizes approach 500,000 unknowns, matrix fill can be reduced from 100 to 10 hours on a modern PC.