Synthesizing High-Performance Image Processing Applications with Hipacc

Özkan MA, Reiche O, Qiao B, Membarth R, Teich J, Hannig F (2019)


Publication Type: Conference contribution, Conference Contribution

Publication year: 2019

Event location: Florence IT

URI: https://www12.cs.fau.de/downloads/oezkan/publications/date-ubooth19.pdf

Abstract

Programming heterogeneous platforms to achieve high performance is laborious since writing efficient code requires tuning at a low level with architecture-specific optimizations and is based on drastically differing programming models. Performance portability across different platforms can be achieved by decoupling the algorithm description from the target implementation. We present Hipacc (http://hipacc-lang.org), a framework consisting of an open-source image processing DSL and a compiler to target CPUs, GPUs, and FPGAs from the same program. We demonstrate Hipacc’s productivity by considering real-world computer vision applications, e.g., optical flow, and generating target code (C++, OpenCL, C-based HLS) for three platforms (CPU and GPU in a laptop and an FPGA board). Finally, we showcase the real-time processing of images acquired by a USB camera on these platforms.

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How to cite

APA:

Özkan, M.A., Reiche, O., Qiao, B., Membarth, R., Teich, J., & Hannig, F. (2019). Synthesizing High-Performance Image Processing Applications with Hipacc. In Proceedings of the Demo at the University Booth at Design, Automation and Test in Europe (DATE). Florence, IT.

MLA:

Özkan, Mehmet Akif, et al. "Synthesizing High-Performance Image Processing Applications with Hipacc." Proceedings of the Demo at the University Booth at Design, Automation and Test in Europe (DATE), Florence 2019.

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