Combining high productivity and high performance in image processing using Single Assignment C on multi-core CPUs and many-core GPUs

Volkmar Wieser; Peter Haslinger; Filip Korzeniowski; Bernhard Moser; Clemens Grelck; Jing Guo; Robert Bernecky; Sven-Bodo Scholz

doi:10.1117/1.JEI.21.2.021116

9 July 2012 Combining high productivity and high performance in image processing using Single Assignment C on multi-core CPUs and many-core GPUs

Volkmar Wieser, Peter Haslinger, Filip Korzeniowski, Bernhard Moser, Clemens Grelck, Jing Guo, Robert Bernecky, Sven-Bodo Scholz

Author Affiliations +

Journal of Electronic Imaging, Vol. 21, Issue 2, 021116 (July 2012). https://doi.org/10.1117/1.JEI.21.2.021116

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.

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Volkmar Wieser, Peter Haslinger, Filip Korzeniowski, Bernhard Moser, Clemens Grelck, Jing Guo, Robert Bernecky, and Sven-Bodo Scholz "Combining high productivity and high performance in image processing using Single Assignment C on multi-core CPUs and many-core GPUs," Journal of Electronic Imaging 21(2), 021116 (9 July 2012). https://doi.org/10.1117/1.JEI.21.2.021116

Published: 9 July 2012

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