Challenges of scaling algebraic multigrid across modern multicore architectures

Allison H. Baker, Todd Gamblin, Martin Schulz, Ulrike Meier Yang

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

50 Scopus citations

Abstract

Algebraic multigrid (AMG) is a popular solver for large-scale scientific computing and an essential component of many simulation codes. AMG has shown to be extremely efficient on distributed-memory architectures. However, when executed on modern multicore architectures, we face new challenges that can significantly deteriorate AMG's performance. We examine its performance and scalability on three disparate multicore architectures: a cluster with four AMD Opteron Quad-core processors per node (Hera), a Cray XT5 with two AMD Opteron Hex-core processors per node (Jaguar), and an IBM Blue Gene/P system with a single Quad-core processor (Intrepid). We discuss our experiences on these platforms and present results using both an MPI-only and a hybrid MPI/OpenMP model. We also discuss a set of techniques that helped to overcome the associated problems, including thread and process pinning and correct memory associations.

Original languageEnglish
Title of host publicationProceedings - 25th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2011
Pages275-286
Number of pages12
DOIs
StatePublished - 2011
Event25th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2011 - Anchorage, AK, United States
Duration: May 16 2011May 20 2011

Publication series

NameProceedings - 25th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2011

Conference

Conference25th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2011
Country/TerritoryUnited States
CityAnchorage, AK
Period05/16/1105/20/11

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