Iterative Methods for Sparse Linear Systems
Iterative Methods for Sparse Linear Systems
Scientific Computations on Modern Parallel Vector Systems
Proceedings of the 2004 ACM/IEEE conference on Supercomputing
Sparsity: Optimization Framework for Sparse Matrix Kernels
International Journal of High Performance Computing Applications
Network bandwidth measurements and ratio analysis with the HPC challenge benchmark suite (HPCC)
PVM/MPI'05 Proceedings of the 12th European PVM/MPI users' group conference on Recent Advances in Parallel Virtual Machine and Message Passing Interface
Performance improvement of sparse matrix vector product on vector machines
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part I
| Hi-index | 0.01 |
This paper addresses the efficiency issues in solving large sparse linear systems parallely on scalar and vector architectures. Linear systems arise in numerous applications that need to solve PDEs on complex domains. The major time consuming part of large scale implicit Finite Element (FE) or Finite Volume (FV) simulation is solving the assembled global system of equations. First, the performance of widely used public domain solvers which target performance on scalar machines is analyzed on a typical vector machine. Then, a newly developed parallel sparse iterative solver (Block-based Linear Iterative Solver --- BLIS) targeting performance on both scalar and vector systems is introduced and the time needed for solving linear systems is compared on different architectures. Finally, the reasons behind the scaling behaviour of parallel iterative solvers is analysed.