The implementation and evaluation of fusion and contraction in array languages

  • Authors:

  • E. Christopher Lewis;Calvin Lin;Lawrence Snyder

  • Affiliations:

  • University of Washington, Seattle, WA;University of Texas, Austin, TX;University of Washington, Seattle, WA

  • Venue:
  • PLDI '98 Proceedings of the ACM SIGPLAN 1998 conference on Programming language design and implementation
  • Year:
  • 1998

Quantified Score

Hi-index 0.00

Visualization

Abstract

Array languages such as Fortran 90, HPF and ZPL have many benefits in simplifying array-based computations and expressing data parallelism. However, they can suffer large performance penalties because they introduce intermediate arrays---both at the source level and during the compilation process---which increase memory usage and pollute the cache. Most compilers address this problem by simply scalarizing the array language and relying on a scalar language compiler to perform loop fusion and array contraction. We instead show that there are advantages to performing a form of loop fusion and array contraction at the array level. This paper describes this approach and explains its advantages. Experimental results show that our scheme typically yields runtime improvements of greater than 20% and sometimes up to 400%. In addition, it yields superior memory use when compared against commercial compilers and exhibits comparable memory use when compared with scalar languages. We also explore the interaction between these transformations and communication optimizations.