Schedule-Independent Storage Mapping for Loops

Michelle Mills Strout, Larry Carter, Jeanne Ferrante, Beth Simon

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

This paper studies the relationship between storage requirements and performance. Storage-related dependences inhibit optimizations for locality and parallelism. Techniques such as renaming and array expansion can eliminate all storage-related dependences, but do so at the expense of increased storage. This paper introduces the universal occupancy vector (UOV) for loops with a regular stencil of dependences. The UOV provides a schedule-independent storage reuse pattern that introduces no further dependences (other than those implied by true flow dependences). OV-mapped code requires less storage than full array expansion and only slightly more storage than schedule-dependent minimal storage. We show that determine if a vector is a UOV is NP-complete. However, an easily constructed but possibly non-minimal UOV can be used. We also present a branch and bound algorithm which finds the minimal UOV, while still maintaining a legal UOV at all times. Our experimental results show that the use of OV-mapped storage, coupled with tiling for locality, achieves better performance than tiling after array expansion, and accommodates larger problem sizes than untilable, storage-optimized code. Furthermore, storage mapping based on the UOV introduces negligible runtime overhead.

Original languageEnglish (US)
Pages (from-to)24-33
Number of pages10
JournalSIGPLAN Notices (ACM Special Interest Group on Programming Languages)
Volume33
Issue number11
DOIs
StatePublished - Nov 1998
Externally publishedYes

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design

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