A Model for Speedup of Parallel Programs

Abstract

We propose a new model for parallel speedup that is based on two parameters, the average parallelism of a program and its variance in parallelism. We present a way to use the model to estimate these program characteristics using only observed speedup curves (as opposed to the more detailed program knowledge otherwise required). We apply this method to speedup curves from real programs on a variety of architectures and show that the model fits the observed data well. We propose several applications for the model, including the selection of cluster sizes for parallel jobs.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1997
Accession Number
ADA637068

Entities

People

  • Allen B. Downey

Organizations

  • University of California, Berkeley

Tags

Communities of Interest

  • Energy and Power Technologies
  • Space

DTIC Thesaurus Topics

  • California
  • Computations
  • Computer Science
  • Computers
  • Engineering
  • Equations
  • Failure Mode And Effect Analysis
  • Information Operations
  • Measurement
  • Navier Stokes Equations
  • Observation
  • Ray Tracing
  • Scheduling (Production)
  • Simulations
  • Three Dimensional
  • Workload

Fields of Study

  • Computer science
  • Mathematics

Readers

  • Life Cycle Cost Analysis
  • Neural Network Machine Learning.
  • Psychometric Testing or Psychological Assessment.