An approach for code generation in the Sparse Polyhedral Framework

Michelle Mills Strout, Alan LaMielle, Larry Carter, Jeanne Ferrante, Barbara Kreaseck, Catherine Olschanowsky

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

Applications that manipulate sparse data structures contain memory reference patterns that are unknown at compile time due to indirect accesses such as A[B[i]]. To exploit parallelism and improve locality in such applications, prior work has developed a number of Run-Time Reordering Transformations (RTRTs). This paper presents the Sparse Polyhedral Framework (SPF) for specifying RTRTs and compositions thereof and algorithms for automatically generating efficient inspector and executor code to implement such transformations. Experimental results indicate that the performance of automatically generated inspectors and executors competes with the performance of hand-written ones when further optimization is done.

Original languageEnglish (US)
Pages (from-to)32-57
Number of pages26
JournalParallel Computing
Volume53
DOIs
StatePublished - Apr 1 2016

Keywords

  • Inspector/executor strategies
  • Runtime reordering transformations
  • Sparse Polyhedral Framework

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computer Networks and Communications
  • Computer Graphics and Computer-Aided Design
  • Artificial Intelligence

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