Parallel Searching and Merging on ZMOB.

Abstract

One of the most difficult issues that must be addressed when studying a class of parallel algorithms is the problem of choosing a model that captures the inherent difficulty of implementing these algorithms on a multiprocessor architecture. Shared memory models have proven to be an effective tool for deriving lower bounds on the complexity of comparison problems. In particular, a speed-up of lg(P) is possible for the problem of finding an element in an N-element sorted list, and speed-ups of PlglgP and P are possible for merging N-element sorted lists of P processors for the cases N=P and P<N respectively. In practice, these speed-ups are not attainable since the shared memory models ignore many practical considerations in multiprocessor systems, such as interprocessor communications, distribution of data on local memories and limited fan-out of memory locations. In this paper we introduce a model for parallel computation that is strictly weaker than the shared memory models. The model is based on an actual machine currently being constructed (ZMOB). We examine the communication facilities available in the model and show that lower bounds for merging and searching on shared memory models are attainable (within a constant).

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1984
Accession Number
ADA145424

Entities

People

  • S. Kasif

Organizations

  • University of Maryland

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  • Air Force
  • Classification
  • Computations
  • Computer Programming
  • Computer Science
  • Computers
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  • Maryland
  • Multiprocessors
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  • Parallel Computing
  • Parallel Processing
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  • United States Government

Fields of Study

  • Computer science

Readers

  • Applied Combinatorial Optimization and Logic Circuit Design.
  • Computational Fluid Dynamics (CFD)
  • Computer Programming and Software Development.