Static Task Allocation for Parallel Processing Systems During Software Development

Abstract

In the sequential world, the mapping of processes to a computer system was not a problem because of the classic Von Newman architecture. However, in the parallel world, the mapping of processes to nodes and the balancing of the load on each node becomes an issue that needs to be addressed. This problem enters software development in the implementation phase and remains an issue through the testing and system integration phases. This report describes a new method developed to improve the mapping on a hypercube system. This new hypersphere mapping approach performs an optimal mapping based on the geometry of the physical system and the communication patterns of the processes. The hypersphere mapper can map processes to nodes where the number of processes exceeds the number of nodes. Other mapping approaches rely on heuristics to cluster the communication graphs into subgraphs to accomplish this mapping. The hypersphere mapper can be instrumental in the implementation phase of software development by specifying an optimal mapping that will improve the performance of the system. This method also provides a transparent programming environment, where the programmer does not need to know about the interconnection network of the physical computer system. The hypersphere mapper was tested using simulated directed and undirected random communication graphs.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1993
Accession Number
ADA274204

Entities

People

  • John K. Antonio
  • Loretta S. Auvil
  • Richard C. Metzger

Organizations

  • Rome Laboratory

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Computational Fluid Dynamics
  • Computer Programming
  • Computer Science
  • Computers
  • Differential Equations
  • Environment
  • Equations
  • Geometry
  • Information Processing
  • Information Systems
  • Mathematics
  • Parallel Computing
  • Parallel Processing
  • Simulations
  • Software Development
  • Three Dimensional

Fields of Study

  • Computer science
  • Engineering

Readers

  • Computer Vision.
  • Graph Algorithms and Convex Optimization.
  • Software Engineering.