BSP linear solvers for dense matrices

This paper presents a study of four parallel linear system solvers implemented using the Bulk Synchronous Parallel programming model. We show that better performances are achieved by the implicit methods due both to higher exploitation of hardware capabilities and to the lower communication costs. A...

Full description

Saved in:
Bibliographic Details
Published in:Parallel computing 1998-06, Vol.24 (5), p.777-795
Main Authors: Evans, D.J, Barulli, M
Format: Article
Language:English
Subjects:
Bulk synchronous parallel (BSP) model
Cluster of workstations
Gaussian elimination
Gauss–Jordan elimination
Implicit elimination
Linear systems
Shared memory
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper presents a study of four parallel linear system solvers implemented using the Bulk Synchronous Parallel programming model. We show that better performances are achieved by the implicit methods due both to higher exploitation of hardware capabilities and to the lower communication costs. A BSP performance model of all the algorithms has been built and the predictions obtained have been compared with the results of measurements on two different parallel systems: a cluster of workstations and a shared memory multiprocessor machine. The implicit algorithms have proved to be from 20% to 40% faster than their traditional counterparts. The high accuracy of prediction makes the BSP programming paradigm an ideal framework for developing parallel algorithms.
ISSN:0167-8191
1872-7336
DOI:10.1016/S0167-8191(98)00014-3