Fast Mutual Exclusion, Even with Contention

Abstract

The authors present a mutual exclusion algorithm that performs well both with and without contention, on machines with no atomic instructions other than read and write. The algorithm capitalizes on the ability of memory systems to read and write at both full-and half-word granularities. It depends on predictable processor execution rates, but requires no bound on the length of critical sections, performs only O(n) total references to shared memory when arbitrating among conflicting requests (rather than O(n squared) in the general version of Lamport's fast mutual exclusion algorithm), and performs only 2 reads and 4 writes (a new lower bound) in the absence of contention. We provide a correctness proof. We also investigate the utility of exponential backoff in fast mutual exclusion, with experimental results on the Silicon Graphics Iris multiprocessor and on a larger, simulated machine. With backoff in place, we find that Lamport's algorithm, our new algorithm, and a recent algorithm due to Alur and Taubenfeld all work extremely well, outperforming the native hardware locks of the Silicon Graphics machine, even with heavy contention.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1993
Accession Number
ADA272947

Entities

People

  • Maged M. Michael
  • Michael L. Scott

Organizations

  • University of Rochester

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Acquisition
  • Algorithms
  • Computer Programming
  • Computer Science
  • Computers
  • Distributed Computing
  • Embedded Systems
  • Graphics
  • Information Processing
  • Information Science
  • Information Systems
  • Instructions
  • Multiprocessors
  • Operating Systems
  • Programming Languages
  • Simulations

Fields of Study

  • Computer science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Mathematical Modeling and Probability Theory.
  • Parallel and Distributed Computing.