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Novel Stochastic Computing for Energy-Efficient Image Processors

School of Computer and Information Engineering, Kwangwoon University, Seoul 01897, Korea
School of Electronic and Electrical Engineering, Hongik University, Seoul 04066, Korea
Author to whom correspondence should be addressed.
Electronics 2019, 8(6), 720;
Received: 21 May 2019 / Revised: 17 June 2019 / Accepted: 21 June 2019 / Published: 25 June 2019
(This article belongs to the Special Issue Energy Efficient Circuit Design Techniques for Low Power Systems)
PDF [1665 KB, uploaded 25 June 2019]


Stochastic computing, which is based on probability, involves a trade-off between accuracy and power and is a promising solution for energy-efficiency in error-tolerance designs. In this paper, adder and multiplier circuits based on the proposed stochastic computing architecture are studied and analyzed. First, we propose an efficient yet simple stochastic computation technique for multipliers and adders by exchanging the wires used for their operation. The results demonstrate that the proposed design reduces the relative error in computation compared with the conventional designs and has smaller area compared to conventional designs. Then, a new energy-efficient and high-performance stochastic adder with acceptable error metrics is investigated. The proposed multiplier shows better error metrics than other existing stochastic multipliers, and significantly improves area utilization and power consumption compared to the exact binary multiplier. Finally, we apply the proposed stochastic architecture to an edge detection algorithm and achieve a significant reduction in area utilization (64%) and power consumption (96%). It is therefore demonstrated that the proposed stochastic architecture is suitable for energy-efficient hardware designs. View Full-Text
Keywords: approximate computing; stochastic computing; wire exchange; energy-efficiency; edge detection approximate computing; stochastic computing; wire exchange; energy-efficiency; edge detection

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Joe, H.; Kim, Y. Novel Stochastic Computing for Energy-Efficient Image Processors. Electronics 2019, 8, 720.

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