Accurate Modeling of Parallel Scientific Computations

Abstract

Scientific codes are usually parallelized by partitioning a grid among processors. To achieve top performance it is necessary to partition the grid so as to balance workload and minimize communication/synchronization costs. This problem is particularly acute when the grid is irregular, changes over the course of the computation, and is not known until load-time. Critical mapping and remapping decisions rest on our ability to accurately predict performance, given a description of a grid and its partition. This paper discusses one approach to this problem, and illustrates its use on a one-dimensional fluids code. The models we construct are shown empirically to be accurate, and are used to find optimal remapping schedules. Keywords: Parallel processing; Dynamic remapping; Analytic modeling.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1988
Accession Number
ADA203533

Entities

People

  • David M. Nicol
  • James C. Townsend

Tags

Communities of Interest

  • Cyber
  • Human Systems

DTIC Thesaurus Topics

  • Algorithms
  • Boundaries
  • Computations
  • Computer Programming
  • Computers
  • Contracts
  • Decomposition
  • Engineering
  • Equations
  • Measurement
  • Parallel Computing
  • Parallel Processing
  • Parallel Processors
  • Scheduling (Production)
  • Sequences
  • Workload

Fields of Study

  • Engineering

Readers

  • Distributed Systems and Data Platform Development
  • Operations Research