TY - GEN
T1 - Embracing approximate computing for energy-efficient motion estimation in high efficiency video coding
AU - El-Harouni, Walaa
AU - Rehman, Semeen
AU - Prabakaran, Bharath Srinivas
AU - Kumar, Akash
AU - Hafiz, Rehan
AU - Shafique, Muhammad
N1 - Publisher Copyright:
© 2017 IEEE.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2017/5/11
Y1 - 2017/5/11
N2 - 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 gate-level 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/.
AB - 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 gate-level 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/.
KW - Approximate computing
KW - Energy efficiency
KW - Hardware accelerator
KW - HEVC
KW - Motion estimation
KW - Video coding
UR - http://www.scopus.com/inward/record.url?scp=85020195597&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85020195597&partnerID=8YFLogxK
U2 - 10.23919/DATE.2017.7927209
DO - 10.23919/DATE.2017.7927209
M3 - Conference contribution
AN - SCOPUS:85020195597
T3 - Proceedings of the 2017 Design, Automation and Test in Europe, DATE 2017
SP - 1384
EP - 1389
BT - Proceedings of the 2017 Design, Automation and Test in Europe, DATE 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 20th Design, Automation and Test in Europe, DATE 2017
Y2 - 27 March 2017 through 31 March 2017
ER -