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

In this paper the challenge of parallelization development of industrial high performance inspection systems is addressed concerning 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 multicore 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. Further author information: 1Corresponding author, Volkmar Wieser: E-mail: [email protected], Telephone: +43 7236 3343 844 Clemens Grelck: E-mail: [email protected], Telephone: +31 20 525 8683 Peter Haslinger: E-mail: [email protected], Telephone: +43 7236 3343 834 Jing Guo: E-mail: [email protected], Telephone: +44 1707 28 3360 Filip Korzeniowski: E-mail: [email protected], Telephone: +43 7236 3343 838 Robert Bernecky: E-mail: [email protected], Telephone: +1 416 203 0854 Bernhard Moser: E-mail: [email protected], Telephone: +43 7236 3343 833 Sven-Bodo Scholz: E-mail: [email protected], Telephone: +44 131 451 3814