Poster abstract: Evaluating topology mapping via graph partitioning

Anshu Arya, Todd Gamblin, Bronis R.De Supinski, Laxmikant V. Kale

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

Abstract

Intelligently mapping applications to machine network topologies has been shown to improve performance, but considerable developer effort is required to find good mappings. Techniques from graph partitioning have the potential to automate topology mapping and relieve the developer burden. Graph partitioning is already used for load balancing parallel applications, but can be applied to topology mapping as well. We show performance gains by using a topology-targeting graph partitioner to map sparse matrix-vector and volumetric 3-D FFT kernels onto a 3-D torus network.

Original languageEnglish (US)
Title of host publicationProceedings - 2012 SC Companion
Subtitle of host publicationHigh Performance Computing, Networking Storage and Analysis, SCC 2012
Pages1371-1372
Number of pages2
DOIs
StatePublished - 2012
Externally publishedYes
Event2012 SC Companion: High Performance Computing, Networking Storage and Analysis, SCC 2012 - Salt Lake City, UT, United States
Duration: Nov 10 2012Nov 16 2012

Publication series

NameProceedings - 2012 SC Companion: High Performance Computing, Networking Storage and Analysis, SCC 2012

Other

Other2012 SC Companion: High Performance Computing, Networking Storage and Analysis, SCC 2012
Country/TerritoryUnited States
CitySalt Lake City, UT
Period11/10/1211/16/12

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Software

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