Transforming for Parallelism Using Symbolic Summarization

Abstract

Effective use of parallelism is an important goal of computing research. This dissertation describes MAGNIFY, an interactive analysis and transformation tool that is part of the Delirium programming environment. The purpose of the environment is to transform sequential FORTRAN programs to execute efficiently on massively parallel distributed memory architectures. The main contributions of MAGNIFY are that it provides new and complex parallelization strategies that would be prohibitively difficult to implement by hand, and that it allows the programmer to determine their use. MAGNIFY, selectively guided by the programmer in an interactive dialog, applies a novel set of code transformations to the application. The transformations reveal opportunities for concurrency beyond those available through traditional loop-based optimizations. Normal parallelizing compilers focus on individual parallel computations and introduce synchronization operations after each one. MAGNIFY is able to manage the interactions among parallel computations to achieve more efficient performance. MAGNIFY summarizes the data access behavior of sub-computations using symbolic data descriptors. The descriptors contain extensive symbolic and conditional information, providing more accuracy than previously developed summary structures. Once the code is analyzed, MAGNIFY uses the descriptors to apply transformations that expose concurrency and pipelining opportunities. The key transformation is split, which reduces synchronization constraints by sub-dividing computations. MAGNIFY also applies traditional loop transformations like interchange and loop-invariant code motion. After the programmer has used MAGNIFY to transform an application, the parallelization strategy is encoded in an intermediate form based on two notations: a coordination language called Delirium and an annotation language called Dossier. An adaptive run-time system executes the application.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1995
Accession Number
ADA637046

Entities

People

  • Oliver J. Sharp

Organizations

  • University of California, Berkeley

Tags

DTIC Thesaurus Topics

  • Applied Computer Science
  • Artificial Intelligence
  • Automated Text Summarization
  • Computations
  • Computer Languages
  • Computer Programming
  • Computer Programs
  • Computer Science
  • Computers
  • Engineering
  • Formal Languages
  • Information Operations
  • Language
  • Parallel Computing

Fields of Study

  • Computer science
  • Engineering

Readers

  • Parallel and Distributed Computing.