Distributed Shared Memory for New Generation Networks.

Abstract

Shared memory is widely believed to provide an easier programming model than message passing for expressing parallel algorithms. Distributed Shared Memory (DSM) systems provide the illusion of shared memory on top of standard message passing hardware at very low implementation cost but provide acceptable performance on only a limited class of applications. In this paper we study the main sources of overhead found in software-coherent distributed shared-memory systems and argue that recent revolutionary changes in network technology now allow us to design protocols that minimize such overheads and that approach the performance of full hardware coherence. Specifically we claim that memory-mapped network interfaces that support a global physical address space can greatly improve the performance of DSM systems. To support this claim we study a variety of coherence protocols that can take advantage of the global physical address space and compare their performance with the best known protocol for pure message passing hardware. For the programs in our application suite, protocols taking advantage of the new hardware features improve performance by at least 50% and by as much as an order of magnitude.

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Document Details

Document Type
Technical Report
Publication Date
Mar 27, 1995
Accession Number
ADA293722

Entities

People

  • Leonidas I. Kontothanassis
  • Michael L. Scott

Organizations

  • University of Rochester

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Communication Systems
  • Computations
  • Computer Architecture
  • Computer Programming
  • Computer Programs
  • Computer Science
  • Computers
  • Computing System Architectures
  • Data Transmission
  • Demographic Cohorts
  • Electromagnetic Wave Propagation
  • Molecular Dynamics
  • Operating Systems
  • Parallel Computing
  • Parallel Processing
  • Simulations

Fields of Study

  • Computer science

Readers

  • Computer Networking
  • Parallel and Distributed Computing.

Technology Areas

  • Space