Nested Dissection on a Mesh-Connected Processor Array,

Abstract

We present a parallel implementation of Gaussian elimination without pivoting using the nested dissection ordering for solving Ax=b where A is an N x N symmetric positive definite matrix. If the graph of A is a square root of N x square root of N finite element mesh then Birkhoff and George and Liu have shown that a parallel complexity of 0 (Square root of N) can be achieved for Gaussian elimination with the nested dissection ordering. Our implementation achieves this parallel complexity on a two dimensional MIMD processor array with N processors and nearest neighbors interconnections. Thus nested dissection is a near optimal algorithm for this problem on this interconnection topology. The parallel implementation on this architecture requires 158 square root of N + 0 (log of square root of N to base 2) parallel floating point multiplications. It is faster than a Kung-Leiserson systolic array for banded matrices for N greater than or equal to 961, and faster than a serial implementation for N as small as 9.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1985
Accession Number
ADA154088

Entities

People

  • P. H. Worley
  • R. Schreiber

Organizations

  • Stanford University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Communication Channels
  • Computational Complexity
  • Computer Architecture
  • Computer Programming
  • Computer Science
  • Computers
  • Computing System Architectures
  • Data Storage Systems
  • Differential Equations
  • Efficiency
  • Elimination
  • Equations
  • Grids
  • Multiprocessors
  • Parallel Processors
  • Partial Differential Equations

Readers

  • Linear Algebra
  • Parallel and Distributed Computing.