A Model of Parallel Performance

Abstract

This report introduces a general model of parallel performance. With the goal of developing conceptual and empirical methods for characterizing and understanding parallel algorithms, new definitions of speedup and efficiency have been formulated. These definitions take into account the effects that problem size and the number of processors have on efficiency and speedup, and provide a natural and quantifiable measure of parallel performance. The terms introduced in the definitions provide new and improved interpretations of the 'serial' and 'parallel' fraction parameters commonly used in the literature (i. e., Amdahl's Law) to explain the behavior of parallel algorithms. The model provides a more complete characterization of parallel algorithm behavior and is used to correct apparent deficiencies in the formulation of speedup as expressed by Amdahl's Law. Chapter of this report reviews the basic definitions of speedup and efficiency and introduces new definitions of these quantities in terms of work units and presents two illustrative examples. Chapter 3 discusses two models of parallel performance which appear in the parallel computing literature. The two formulations of speedup and efficiency are based on the notion of 'serial' and 'parallel' fractions and present an apparent dichotomy which must be resolved. Then, the 'serial' and ''parallel' fractions are expressed terms of the new work quantities introduced in Chapter 2, providing a natural interpretation of the serial and parallel fractions of a task. The resulting equations are used to reconcile the (apparent) dichotomy between Amdahl's Law and the more recent formulation of speedup.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1989
Accession Number
ADA207792

Entities

People

  • Edward A. Carmona
  • Michael Rice

Organizations

  • Air Force Research Laboratory

Tags

Communities of Interest

  • C4I
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Air Force Facilities
  • Algorithms
  • Case Studies
  • Classification
  • Computations
  • Efficiency
  • Governments
  • Law
  • Literature
  • Parallel Computing
  • Parallel Processing
  • Security
  • Simulations
  • Square Roots
  • United States
  • United States Government

Readers

  • Computational Fluid Dynamics (CFD)
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference