ParSy: Inspection and transformation of sparse matrix computations for parallelism

Kazem Cheshmi, Shoaib Kamil, Michelle Mills Strout, Maryam Mehri Dehnavi

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

12 Scopus citations

Abstract

In this work, we describe ParSy, a framework that uses a novel inspection strategy along with a simple code transformation to optimize parallel sparse algorithms for shared memory processors. Unlike existing approaches that can suffer from load imbalance and excessive synchronization, ParSy uses a novel task coarsening strategy to create well-balanced tasks that can execute in parallel, while maintaining locality of memory accesses. Code using the ParSy inspector and transformation outperforms existing highly-optimized sparse matrix algorithms such as Cholesky factorization on multi-core processors with speedups of 2.8× and 3.1× over the MKL Pardiso and PaStiX libraries respectively.

Original languageEnglish (US)
Title of host publicationProceedings - International Conference for High Performance Computing, Networking, Storage, and Analysis, SC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages779-793
Number of pages15
ISBN (Electronic)9781538683842
DOIs
StatePublished - Mar 11 2019
Externally publishedYes
Event2018 International Conference for High Performance Computing, Networking, Storage, and Analysis, SC 2018 - Dallas, United States
Duration: Nov 11 2018Nov 16 2018

Publication series

NameProceedings - International Conference for High Performance Computing, Networking, Storage, and Analysis, SC 2018

Conference

Conference2018 International Conference for High Performance Computing, Networking, Storage, and Analysis, SC 2018
Country/TerritoryUnited States
CityDallas
Period11/11/1811/16/18

Keywords

  • Domain-specific code generation
  • Loop transformations
  • Matrix computations
  • Parallel algorithms

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Networks and Communications
  • Hardware and Architecture
  • Theoretical Computer Science

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