On the efficient implementation of preconditioned s-step conjugate gradient methods on multiprocessors with memory hierarchy

A. T. Chronopoulos, C. W. Gear

Research output: Contribution to journalArticlepeer-review

36 Scopus citations

Abstract

Multiprocessor architectures combining vector and parallel processing capabilities on a two-level shared memory structure have been implemented. This memory hierarchy structure requires that numerical algorithms possess good data locality in order to achieve high performance rates. The s-step Conjugate Gradient method (s-CG) is a generalization of the standard CG method with improved data locality and parallel properties. Here we show how to implement efficiently the Incomplete Cholesky and Polynomial Preconditioning with s-CG on multiprocessors with memory hierarchy.

Original languageEnglish (US)
Pages (from-to)37-53
Number of pages17
JournalParallel Computing
Volume11
Issue number1
DOIs
StatePublished - Jul 1989

All Science Journal Classification (ASJC) codes

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computer Networks and Communications
  • Computer Graphics and Computer-Aided Design
  • Artificial Intelligence

Keywords

  • ALLIANT FX/8
  • Preconditioned conjugate gradient method
  • implementation features
  • model problem
  • parallelisation of preconditioning

Fingerprint

Dive into the research topics of 'On the efficient implementation of preconditioned s-step conjugate gradient methods on multiprocessors with memory hierarchy'. Together they form a unique fingerprint.

Cite this