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Stochastic computing (SC) is a promising approach for low-power and low-cost applications with the added benefit of high error tolerance. However, the high overhead of generating stochastic bitstreams can offset… Click to show full abstract
Stochastic computing (SC) is a promising approach for low-power and low-cost applications with the added benefit of high error tolerance. However, the high overhead of generating stochastic bitstreams can offset the advantages of SC especially when a large number of bitstreams are needed. In this paper, we propose a new stochastic number generator (SNG) that significantly reduces area and energy while improving accuracy. Experimental results show that the proposed SNG can reduce energy by more than 72% compared with the state-of-the-art designs.
Journal Title: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Year Published: 2018
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