TeaLeaf: A mini-application to enable design-space explorations for iterative sparse linear solvers

Simon McIntosh-Smith, Matt Martineau, Tom Deakin, Grzegorz Pawelczak, Wayne Gaudin, Paul Garrett, Wei Liu, Richard Smedley-Stevenson, David Beckingsale

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

8 Citations (Scopus)
373 Downloads (Pure)

Abstract

Iterative sparse linear solvers are an important class of algorithm in high performance computing, and form a crucial component of many scientific codes. As intra and inter node parallelism continues to increase rapidly, the design of new, scalable solvers which can target next generation architectures becomes increasingly important. In this work we present TeaLeaf, a recent mini-App constructed to explore design space choices for highly scalable solvers. We then use TeaLeaf to compare the standard CG algorithm with a Chebyshev Polynomially Preconditioned Conjugate Gradient (CPPCG) iterative sparse linear solver. CPPCG is a communication-Avoiding algorithm, requiring less global communication than previous approaches. TeaLeaf includes support for many-core processors, such as GPUS and Xeon Phi, and we include strong-scaling results across a range of world-leading Petascale supercomputers, including Titan and Piz Daint.
Original languageEnglish
Title of host publication2017 IEEE International Conference on Cluster Computing (CLUSTER 2017)
Subtitle of host publicationProceedings of a meeting held 5-8 September 2017, Honolulu, Hawaii, USA
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages842-849
Number of pages8
ISBN (Electronic)9781538623268
ISBN (Print)9781538623275
DOIs
Publication statusPublished - Oct 2017
Event2017 IEEE International Conference on Cluster Computing, CLUSTER 2017 - Honolulu, United States
Duration: 5 Sep 20178 Sep 2017

Publication series

Name
ISSN (Print)2168-9253

Conference

Conference2017 IEEE International Conference on Cluster Computing, CLUSTER 2017
CountryUnited States
CityHonolulu
Period5/09/178/09/17

Keywords

  • Accelerators
  • Iterative parse linear solvers
  • Mini-Apps
  • Strong scaling

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