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.
|Original language||English (US)|
|Title of host publication||Computational Science, ICCS 2002 - International Conference, Proceedings|
|Number of pages||10|
|State||Published - 2002|
|Event||International Conference on Computational Science, ICCS 2002 - Amsterdam, Netherlands|
Duration: Apr 21 2002 → Apr 24 2002
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Other||International Conference on Computational Science, ICCS 2002|
|Period||4/21/02 → 4/24/02|
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