Parallel Performance of Pure MATLAB "M-files" versus "C-code" as Applied to Formation of Wide-Bandwidth and Wide-Beamwidth SAR Imagery

Abstract

To the extent that tools can allow rapid prototyping, increased value is achieved. For scientists in the area of Signal and Image processing, MATLAB is often the tool of choice. MATLAB allows extremely rapid prototyping and debugging of complicated studies with a minimal of computer science expertise. Frequently an idea is implemented in MATLAB code and tested on small data sets. These small data sets provide outputs in sufficient time such that performance studies can be conducted. However, as the studies progress and the same codes are used on much larger real data sets, run times may grow to unrealistic lengths. This may force the research scientist to use another implementation language, such as C and MPI, and implement the code on parallel architectures. This code conversion is undesirable, time consuming, and error prone. An alternative and convenient way to accomplish run time reduction is to use the MatlabMPI suite written by Jeremy Kepner of MIT. This suite of pure MATLAB code allows one to simulate many of the MPI functions within MATLAB. It accomplishes inter-processor communication via disk I/O and a common disk drive.

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Document Details

Document Type
Technical Report
Publication Date
Sep 25, 2003
Accession Number
ADA428838

Entities

People

  • Ashok Krishnamurthy
  • John Nehrbass
  • Juan C. Chaves
  • Mehrdad Soumekh
  • Stan Ahalt

Organizations

  • Ohio State University

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Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Bandwidth
  • Central Processing Units
  • Change Detection
  • Computer Programming
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  • Computer Science
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  • Electrical Engineering
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  • Image Processing
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  • Signal Processing
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Fields of Study

  • Computer science

Readers

  • Database Systems and Applications
  • Parallel and Distributed Computing.