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Journal of Electronic Imaging

Combining high productivity and high performance in image processing using Single Assignment C on multi-core CPUs and many-core GPUs
Author(s): Volkmar Wieser; Peter Haslinger; Filip Korzeniowski; Bernhard Moser; Clemens Grelck; Jing Guo; Robert Bernecky; Sven-Bodo Scholz
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Paper Abstract

We address the challenge of parallelization development of industrial high-performance inspection systems comparing a conventional parallelization approach versus an auto-parallelized technique. Therefore, we introduce the functional array processing language Single Assignment C (SAC), which relies on a hardware virtualization concept for automated, parallel machine code generation for multi-core CPUs and GPUs. Additional software engineering aspects like programmability, productivity, understandability, maintainability, and resulting achieved gain in performance are discussed from the point of view of a developer. With several illustrative benchmarking examples from the field of image processing and machine learning, the relationship between runtime performance and efficiency of development is analyzed.

Paper Details

Date Published: 9 July 2012
PDF: 14 pages
J. Electron. Imaging. 21(2) 021116 doi: 10.1117/1.JEI.21.2.021116
Published in: Journal of Electronic Imaging Volume 21, Issue 2
Show Author Affiliations
Volkmar Wieser, Software Competence Ctr. Hagenberg (Austria)
Peter Haslinger, Software Competence Ctr. Hagenberg (Austria)
Filip Korzeniowski, Software Competence Ctr. Hagenberg (Austria)
Bernhard Moser, Software Competence Ctr. Hagenberg (Austria)
Clemens Grelck, Univ. van Amsterdam (Netherlands)
Jing Guo, Univ. of Hertfordshire (United Kingdom)
Robert Bernecky, Snake Island Research, Inc. (Canada)
Sven-Bodo Scholz, Heriot-Watt Univ. (United Kingdom)


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