Parallel iterative methods in modern physical applications

Abstract

Solving large sparse linear systems is a computationallyintensive component of many important large-scale applications. We present a few experiments stemming from a number of realistic applications including magneto-hydrodynamics structural mechanics, and ultrasound modeling, which have become possible due to the advances in parallel iterative solution techniques. Among such techniques is a recently developed Parallel Algebraic Recursive Multilevel Solver (pARMS ). This is a distributed-memory iterative method that adopts the general framework of distributed sparse matrices and relies on solving the resulting distributed Schur complement systems. We discuss some issues related to parallel performance for various linear systems which arise in realistic applications. In particular, we consider the effect of different parameters and algorithms on the overall performance. © Springer-Verlag Berlin Heidelberg 2002.