On the development of parallel sparse CGM solver for CFD computations on Anu-cluster

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.