Automatic parallelization of a class of irregular loops for distributed memory systems

Abstract

Many scientific applications spend significant time within loops that are parallel, except for dependences from associative reduction operations. However these loops often contain data-dependent control-flow and array-access patterns. Traditional optimizations that rely on purely static analysis fail to generate parallel code in such cases.

Document Details

Document Type
Pub Defense Publication
Publication Date
Oct 03, 2014
Source ID
10.1145/2660251

Entities

People

  • Atanas Rountev
  • J. Ramanujam
  • John Eisenlohr
  • Louis-noël Pouchet
  • Mahesh Ravishankar
  • P. Sadayappan

Organizations

  • Louisiana State University
  • National Science Foundation
  • Ohio State University
  • United States Army
  • United States Department of Energy
  • University of California, Los Angeles

Tags

Fields of Study

  • Computer science

Readers

  • Economics
  • Parallel and Distributed Computing.