On Probabilistic and Symmetric Parallel Computations,

Abstract

There are many known examples of problems for which there is a probabilistic (sequential) algorithm more efficient than any known deterministic algorithm. This paper considers the question: Are parallel machines made more efficient by allowing processors to take probabilistic choices. We also consider the questions: What is the computational power of parallel machines, if we require transitions of processors to be symmetric? This is motivated by physical constraints to parallel computation such as energy consumption. Also, there appears to be some fundamental relationship between symmetrical and probabilistic computations. To partially answer these questions, we use previous studies of the computational complexity of parallel machines, studies of probabilistic computations, work on symmetric computations, and work relating probabilistic and symmetric computations. We formulate a general thesis for how both the probabilistic and symmetric types of parallel computation relate to other types of computation.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1980
Accession Number
ADA095657

Entities

People

  • John Reif

Organizations

  • Harvard University

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Automata
  • Computational Complexity
  • Computations
  • Computer Science
  • Computers
  • Energy Consumption
  • Machines
  • Parallel Computing
  • Parallel Processing
  • Probability
  • Random Walk
  • Sequences
  • Simulations
  • Symmetric Games
  • Systems Science

Fields of Study

  • Computer science
  • Mathematics

Readers

  • Graph Algorithms and Convex Optimization.
  • Mathematical Modeling and Probability Theory.