Fault-Tolerant and Efficient Parallel Computation

Abstract

RECENT advances in computer technology made parallel machines a reality. Massively parallel systems use many general-purpose, inexpensive processing elements to attain computation speed-ups comparable to or better than those achieved by expensive, specialized machines with a small number of fast processors. In such setting, however, one would expect to see an increased number of processor failures attributable to hardware or software. This may eliminate the potential advantage of parallel computation. We believe that this presents a reliability bottleneck that is among fundamental problems in parallel computation. We investigate algorithmic ways of introducing fault-tolerance in multiprocessors under the constraint of preserving efficiency. This research demonstrates how in certain models of parallel computation it is possible to combine efficiency and fault-tolerance. We show that in the models we study, it is possible to develop efficient parallel algorithms without concern for fault-tolerance, and then correctly and efficiently execute these algorithms on parallel machines whose processors are subject to arbitrary dynamic failstop errors. By ensuring efficient executions for any patterns of failures, the efficiency is also maintained when failures are infrequent, or when the expected number of failures is small.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1992
Accession Number
ADA253350

Entities

People

  • Alexander A. Shvartsman

Organizations

  • Brown University

Tags

Communities of Interest

  • C4I
  • Engineered Resilient Systems

DTIC Thesaurus Topics

  • Algorithms
  • Computations
  • Computer Programming
  • Computer Science
  • Computers
  • Computing System Architectures
  • Construction
  • Damage Detection
  • Distributed Computing
  • Engineering
  • Fault Tolerance
  • Manufacturing
  • Network Protocols
  • Operating Systems
  • Parallel Computing
  • Parallel Processing
  • Trees (Data Structures)

Fields of Study

  • Computer science
  • Engineering

Readers

  • Applied Combinatorial Optimization and Logic Circuit Design.
  • Parallel and Distributed Computing.