Parallel implementation and communication of low-level vision operations on a hypercube machine

Abstract

Several commercial hypercube parallel processors with the potential to deliver massive parallelism cost-effectively have appeared in the computer market. Hypercube machines open the door to a wide variety of application areas that could benefit from parallelism. Computer vision and image processing is one of these application areas. This thesis develops a general model for hypercube machines to show how three low-level computer vision algorithms and related communications can be implemented on a new generation hypercube machine, nCUBE 2 supercomputer, in parallel. The primary objective is to design an efficient algorithm, which runs on a network based on the hypercube topology, to carry out the communication tasks that are very important in parallel processing of low-level vision operations. Specific schemes are developed for data exchange among processors, which is indispensable in window convolution operations. Results reveal the relationship between communication and efficiency in parallel processing and illustrate the potential use of such a machine.

Notes

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Graduation Date

1992

Semester

Summer

Advisor

DeCatrel, John M.

Degree

Master of Science (M.S.)

College

College of Engineering

Department

Computer Engineering

Format

PDF

Pages

84 p.

Language

English

Length of Campus-only Access

None

Access Status

Masters Thesis (Open Access)

Identifier

DP0029741

Subjects

Dissertations, Academic -- Engineering; Engineering -- Dissertations, Academic

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