An efficient load-balancing processor scheduling algorithm for parallelization of gauss-seidel type algorithms

Garng Morton Huang, W. Ongsakul

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

The paper extends our earlier results on the parallelization of Gauss-Seidel (G-S) algorithms for power flow analysis. In the earlier paper, we formulate the parallelizing process as a basic coloring problem, which satisfies the constraint that no directly connected vertices have the same color, without worrying about the constraint on the number of available processors. In this paper, this extra constraint is considered. A heuristic approach is developed to maximize the processor efficiency under the number of processor constraint. The idea is to fully utilize the processor resource, to balance the computational load, and to maximize the use of newly computed data for faster convergence. Some examples and test results are described in this paper.

Original languageEnglish
Pages (from-to)350-358
Number of pages9
JournalJournal of Parallel and Distributed Computing
Volume22
Issue number2
DOIs
Publication statusPublished - 1 Jan 1994
Externally publishedYes

Fingerprint

Gauss-Seidel
Coloring
Scheduling algorithms
Load Balancing
Scheduling Algorithm
Parallelization
Resource allocation
Color
Maximise
Power Flow
Colouring
Heuristics
Resources

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Software
  • Hardware and Architecture
  • Computer Networks and Communications
  • Artificial Intelligence

Cite this

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