Lazy Task Creation: A Technique for Increasing the Granularity of Parallel Programs

Abstract

Many parallel algorithms are naturally expressed at a fine level of granularity, often finer than a MIMD parallel system can exploit efficiently. Most builders of parallel systems have looked to either the programmer or a parallelizing compiler to increase the granularity of such algorithms. In this paper, we explore a third approach to the granularity problem by analyzing two strategies for combining parallel tasks dynamically at run-time. We reject the simpler load-based inlining method, where tasks are combined based on dynamic load level, in favor of the safer and more robust lazy task creation method, where tasks are created only retroactively as processing resources become available. These strategies grew out of work on Mul-T 17, an efficient parallel implementation of Scheme, but could be used with other languages as well. We describe our Mul-T implementations of lazy task creation for two contrasting machines, and present performance statistics which show the method's effectiveness. Lazy task creation allows efficient execution of naturally expressed algorithms of a substantially finer grain than possible with previous parallel Lisp systems.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1991
Accession Number
ADA237477

Entities

People

  • David Kranz
  • Eric Mohr
  • Robert H. Halstead Jr

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Weapons Technologies

DTIC Thesaurus Topics

  • Classification
  • Compilers
  • Computations
  • Computer Architecture
  • Computer Programming
  • Computer Programs
  • Computer Science
  • Computers
  • Fish
  • Information Processing
  • Instruction Set Architecture
  • Lisp Programming Language
  • Multiprocessors
  • Programming Languages
  • Scheduling (Production)
  • Standards
  • Trees (Data Structures)

Fields of Study

  • Computer science
  • Engineering

Readers

  • Educational Psychology
  • Parallel and Distributed Computing.