Vorträge und Posterpräsentationen (mit Tagungsband-Eintrag):
W. El-Harouni, S. Rehman, B. Prabakaran, A. Kumar, R. Hafiz, M. Shafique:
"Embracing Approximate Computing for Energy-Efficient Motion Estimation in High Efficiency Video Coding";
Vortrag: 2017 IEEE/ACM 20th Design, Automation and Test in Europe Conference (DATE'17),
Lausanne, Switzerland;
27.03.2017
- 31.03.2017; in: "Proceedings of the 2017 Design, Automation & Test in Europe (DATE)",
IEEE,
(2017),
ISSN: 1558-1101;
S. 1384
- 1389.
Kurzfassung englisch:
Approximate Computing is an emerging paradigm for developing highly energy-efficient computing systems. It leverages the inherent resilience of applications to trade output quality with energy efficiency. In this paper, we present a novel approximate architecture for energy-efficient motion estimation (ME) in high efficiency video coding (HEVC). We synthesized our designs for both ASIC and FPGA design flows. ModelSim gatelevel simulations are used for functional and timing verification. We comprehensively analyze the impact of heterogeneous approximation modes on the power/energy-quality tradeoffs for various video sequences. To facilitate reproducible results for comparisons and further research and development, the RTL and behavioral models of approximate SAD architectures and constituting approximate modules are made available at https://sourceforge.net/projects/lpaclib/.
Schlagworte:
Approximate Computing, Hardware Accelerator, Motion Estimation, HEVC, Video Coding, Energy Efficiency
"Offizielle" elektronische Version der Publikation (entsprechend ihrem Digital Object Identifier - DOI)
http://dx.doi.org/10.23919/DATE.2017.7927209
Erstellt aus der Publikationsdatenbank der Technischen Universität Wien.