Tom Cwik*, Daniel S. Katz1, Cinzia Zuffada, Vahraz Jamnejad
Jet Propulsion Laboratory
California Institute of Technology
Pasadena, CA 91109
1Cray Research, Inc.
El Segundo, CA 90245
In this work an iterative solver for use with out finite element codes was developed for the Cray T3D massively parallel processor located at the Jet Propulsion Laboratory. This development was completed in two stages. First, a matrix decomposition algorithm was constructed, properly decomposing the sparse matrix entries into data sets that were read by the T3D processing elements (PEs). It is noted that this a different strategy that the usual mesh decomposition algorithms developed in the past. The second stage was the construction of a scalable iterative solver on the T3D that efficiently computes a solution of the sparse system. The initial sparse matrix decomposition algorithm was originally developed for a YMP processor and then ported to the T3D.
In this talk we will present an overview of sparse matrix methods for distributed memory machines, as well as the specific implementation of the iterative solver. Example solutions have been obtained for systems with over one-half million unknowns.