Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
9507132 | Applied Mathematics and Computation | 2005 | 23 Pages |
Abstract
In this study we introduce strategies for a load-balanced parallelization of sparse matrix computations on a cluster of PCs with minimum communication overhead. Based on these strategies a parallel sparse Conjugate Gradient Algorithm for CFD computations is evolved. The proposed parallel algorithm is implemented on Anu-cluster, a cluster of eight PCs, under ANULIB message passing environment. The parallel sparse code is tested both on linear and non-linear problems and found to give good performance. Results are compared with those from dense matrix computations.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
B.V. Rathish Kumar, Bipin Kumar,