Four horizons for enhancing the performance of parallel simulations based on partial differential equations

David E. Keyes*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Scopus citations


Simulations of PDE-based systems, such as flight vehicles, the global climate, petroleum reservoirs, semiconductor devices, and nuclear weapons, typically perform an order of magnitude or more below other scientific simulations (e.g., from chemistry and physics) with dense linear algebra or N-body kernels at their core. In this presentation, we briefly review the algorithmic structure of typical PDE solvers that is responsible for this situation and consider possible architectural and algorithmic sources for performance improvement. Some of these improvements are also applicable to other types of simulations, but we examine their consequences for PDEs: potential to exploit orders of magnitude more processor-memory units, better organization of the simulation for today’s and likely near-future hierarchical memories, alternative formulations of the discrete systems to be solved, and new horizons in adaptivity. Each category is motivated by recent experiences in computational aerodynamics at the 1 Teraflop/s scale.

Original languageEnglish (US)
Title of host publicationEuro-Par 2000 Parallel Processing - 6th International Euro-Par Conference, Proceedings
PublisherSpringer Verlag
Number of pages17
ISBN (Electronic)9783540679561
StatePublished - 2000
Externally publishedYes
Event6th International European Conference on Parallel Computing, Euro-Par 2000 - Munich, Germany
Duration: Aug 29 2000Sep 1 2000

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other6th International European Conference on Parallel Computing, Euro-Par 2000

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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