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Proceedings Paper

Performance enhancement of various real-time image processing techniques via speculative execution
Author(s): Mohamed F. Younis; Purnendu Sinha; Thomas J. Marlowe; Alexander D. Stoyenko
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Paper Abstract

In real-time image processing, an application must satisfy a set of timing constraints while ensuring the semantic correctness of the system. Because of the natural structure of digital data, pure data and task parallelism have been used extensively in real-time image processing to accelerate the handling time of image data. These types of parallelism are based on splitting the execution load performed by a single processor across multiple nodes. However, execution of all parallel threads is mandatory for correctness of the algorithm. On the other hand, speculative execution is an optimistic execution of part(s) of the program based on assumptions on program control flow or variable values. Rollback may be required if the assumptions turn out to be invalid. Speculative execution can enhance average, and sometimes worst-case, execution time. In this paper, we target various image processing techniques to investigate applicability of speculative execution. We identify opportunities for safe and profitable speculative execution in image compression, edge detection, morphological filters, and blob recognition.

Paper Details

Date Published: 5 March 1996
PDF: 10 pages
Proc. SPIE 2661, Real-Time Imaging, (5 March 1996); doi: 10.1117/12.234656
Show Author Affiliations
Mohamed F. Younis, New Jersey Institute of Technology (United States)
Purnendu Sinha, New Jersey Institute of Technology (United States)
Thomas J. Marlowe, New Jersey Institute of Technology (United States)
Alexander D. Stoyenko, New Jersey Institute of Technology (United States)

Published in SPIE Proceedings Vol. 2661:
Real-Time Imaging
Phillip A. Laplante; Alexander D. Stoyenko; Divyendu Sinha, Editor(s)

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