Hostile Cache Implications for Small, Dense Linear Solves

Tom J Deakin, Jim H Cownie, Simon N Mcintosh-Smith, Justin Lovegrove, Richard Smedley-Stevenson

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

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Abstract

The full assembly of the stiffness matrix in finite element codes can be prohibitive in terms of memory footprint resulting from storing that enormous matrix. An optimisation and work around, particularly effective for discontinuous Galerkin based approaches, is to construct and solve the small dense linear systems locally within each element and avoid the global assembly entirely. The different independent linear systems can be solved concurrently in a batched manner, however we have found that
the memory subsystem can show destructive behaviour in this paradigm, severely affecting the performance. In this paper we demonstrate the range of performance that can be obtained by allocating the local systems differently, along with evidence to attribute the reasons behind these differences.
Original languageEnglish
Title of host publication2020 IEEE/ACM Workshop on Memory Centric High Performance Computing (MCHPC)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages8
ISBN (Electronic)978-0-7381-1066-0
ISBN (Print)978-0-7381-1067-7
DOIs
Publication statusPublished - 20 Dec 2020
Event2020 IEEE/ACM Workshop on Memory Centric High Performance Computing (MCHPC) - Virtual event
Duration: 11 Nov 202011 Nov 2020
https://passlab.github.io/mchpc/mchpc2020/

Conference

Conference2020 IEEE/ACM Workshop on Memory Centric High Performance Computing (MCHPC)
Period11/11/2011/11/20
Internet address

Keywords

  • finite element analysis
  • linear systems
  • instruction sets
  • reseource management
  • runtime
  • parallel processing
  • bandwidth
  • Galerkin method
  • batched linear algebra
  • cahe
  • memory allocation

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