Modeling the performance of an algebraic multigrid cycle on HPC platforms

Hormozd Gahvari, Allison H. Baker, Martin Schulz, Ulrike Meier Yang, Kirk E. Jordan, William D Gropp

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Now that the performance of individual cores has plateaued, future supercomputers will depend upon increasing parallelism for performance. Processor counts are now in the hundreds of thousands for the largest machines and will soon be in the millions. There is an urgent need to model application performance at these scales and to understand what changes need to be made to ensure continued scalability. This paper considers algebraic multigrid (AMG), a popular and highly efficient iterative solver for large sparse linear systems that is used in many applications. We discuss the challenges for AMG on current parallel computers and future exascale architectures, and we present a performance model for an AMG solve cycle as well as performance measurements on several massively-parallel platforms.

Original languageEnglish (US)
Title of host publicationICS'11 - Proceedings of the 2011 ACM International Conference on Supercomputing
Pages172-181
Number of pages10
DOIs
StatePublished - 2011
Event25th ACM International Conference on Supercomputing, ICS 2011 - Tucson, AZ, United States
Duration: May 31 2011Jun 4 2011

Publication series

NameProceedings of the International Conference on Supercomputing

Other

Other25th ACM International Conference on Supercomputing, ICS 2011
Country/TerritoryUnited States
CityTucson, AZ
Period5/31/116/4/11

Keywords

  • algebraic multigrid
  • massively parallel architectures
  • performance modeling
  • scaling

ASJC Scopus subject areas

  • General Computer Science

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