Abstract
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.
Highlights
Energy efficiency is one of the major design objectives in electronic devices such as wireless or wearable devices because of limited battery life
The image obtained using the proposed stochastic computing technique is better than the other stochastic methods and is similar to the image obtained by the accurate edge detection
Up to 64% of total area and 96% of power were saved in application specific integrated circuit (ASIC) compared with the accurate edge detection
Summary
Energy efficiency is one of the major design objectives in electronic devices such as wireless or wearable devices because of limited battery life. Approximate computing, which provides advantages such as small area and low power by compromising on the accuracy of computation, is one of the techniques used to increase energy efficiency. In References [11,12,13,14,15,16,17,18,19], various random number generator architectures and real world applications based on stochastic computing were introduced and analyzed in terms of accuracy and area. We propose an efficient and simple technique that improves the accuracy of stochastic computing by using a wire exchanging method. We can reduce area utilization and improve efficiency by exchanging the wire of the RNG, which is one of the inseparable elements of stochastic computing, for improved accuracy
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