Energy Efficient RRAM Crossbar-Based Approximate Computing for Smart Cameras

2016 ◽  
pp. 109-133
Author(s):  
Yu Wang ◽  
Boxun Li ◽  
Lixue Xia ◽  
Tianqi Tang ◽  
Huazhong Yang
Keyword(s):  
Energy Efficient ◽  
Approximate Computing ◽  
Smart Cameras

Energy-Efficient IoT-Health Monitoring System using Approximate Computing

2020 ◽  
Vol 9 ◽  
pp. 100166 ◽  
Author(s):  
Avrajit Ghosh ◽  
Arnab Raha ◽  
Amitava Mukherjee
Keyword(s):  
Monitoring System ◽  
Health Monitoring ◽  
Energy Efficient ◽  
Approximate Computing ◽  
Health Monitoring System

Exploring Approximate Computing and Near- Threshold Operation to Design Energy -efficient Multipliers

2021 ◽  
Author(s):  
Vinicius Zanandrea ◽  
Douglas M. Borges ◽  
Vagner S. Rosa ◽  
Cristina Meinhardt
Keyword(s):  
Energy Efficient ◽  
Approximate Computing ◽  
Near Threshold

scholarly journals Spin Wave Based Approximate Computing

2021 ◽  
Author(s):  
Abdulqader Mahmoud ◽  
Frederic Vanderveken ◽  
Florin Ciubotaru ◽  
Christoph Adelmann ◽  
Said Hamdioui ◽  
...  
Keyword(s):  
Real Estate ◽  
Error Rate ◽  
Energy Efficient ◽  
State Of The Art ◽  
Magnetic Tunnel Junction ◽  
Domain Wall Motion ◽  
Full Adder ◽  
Average Error ◽  
Approximate Computing ◽  
Average Error Rate

By their very nature Spin Waves (SWs) enable the realization of energy efficient circuits as they propagate and interfere within waveguides without consuming noticeable energy. However, SW computing can be even more energy efficient by taking advantage of the approximate computing paradigm as many applications are error-tolerant like multimedia and social media. In this paper we propose an ultra-low energy novel Approximate Full Adder (AFA) and a 2-bit inputs Multiplier (AMUL). The approximate FA consists of one Majority gate while the approximate MUL is built by means of 3 AND gates. We validate the correct functionality of our proposal by means of micromagnetic simulations and evaluate the approximate FA figure of merit against state-of-the-art accurate SW, 7nm CMOS, Spin Hall Effect (SHE), Domain Wall Motion (DWM), accurate and approximate 45nm CMOS, Magnetic Tunnel Junction (MTJ), and Spin-CMOS FA implementations. Our results indicate that AFA consumes 43% and 33% less energy than state-of-the-art accurate SW and 7nm CMOS FA, respectively, and saves 69% and 44% when compared with accurate and approximate 45nm CMOS, respectively, and provides a 2 orders of magnitude energy reduction when compared with accurate SHE, accurate and approximate DWM, MTJ, and Spin-CMOS, counterparts. In addition, it achieves the same error rate as approximate 45nm CMOS and Spin-CMOS FA whereas it exhibits 50% less error rate than the approximate DWM FA. Furthermore, it outperforms its contenders in terms of area by saving at least 29% chip real-estate. AMUL is evaluated and compared with state-of-the-art accurate SW and 16nm CMOS accurate and approximate state-of-the-art designs. The evaluation results indicate that it saves at least 2x and 5x energy in comparison with the state-of-the-art SW designs and 16nm CMOS accurate and approximate designs, respectively, and has an average error rate of 10%, while the approximate CMOS MUL has an average error rate of 12.5%, and requires at least 64% less chip real-estate.

scholarly journals E-ERA: An energy-efficient reconfigurable architecture for RNNs using dynamically adaptive approximate computing

2017 ◽  
Vol 14 (15) ◽  
pp. 20170637-20170637 ◽  
Author(s):  
Bo Liu ◽  
Wei Dong ◽  
Tingting Xu ◽  
Yu Gong ◽  
Wei Ge ◽  
...  
Keyword(s):  
Energy Efficient ◽  
Reconfigurable Architecture ◽  
Approximate Computing

Energy-Efficient Digital Processing via Approximate Computing

2016 ◽  
pp. 55-89 ◽  
Author(s):  
Daniele Jahier Pagliari ◽  
Massimo Poncino ◽  
Enrico Macii
Keyword(s):  
Energy Efficient ◽  
Digital Processing ◽  
Approximate Computing
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