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• W2955669702 abstract "Convolutional neural networks (CNN) have achieved excellent performance on various tasks, but deploying CNN to edge is constrained by the high energy consumption of convolution operation. Stochastic computing (SC) is an attractive paradigm which performs arithmetic operations with simple logic gates and low hardware cost. This paper presents an energy-efficient mixed-signal multiply-accumulate (MAC) engine based on SC. A parallel architecture is adopted in this work to solve the latency problem of SC. The simulation results show that the overall energy consumption of our design is 5.03pJ per 26-input MAC operation under 28nm CMOS technology." @default.
• W2955669702 created "2019-07-12" @default.
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• W2955669702 date "2019-07-03" @default.
• W2955669702 modified "2023-09-26" @default.
• W2955669702 title "An Energy-Efficient Mixed-Signal Parallel Multiply-Accumulate (MAC) Engine Based on Stochastic Computing" @default.
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• W2955669702 doi "https://doi.org/10.48550/arxiv.1907.01807" @default.
• W2955669702 hasPublicationYear "2019" @default.
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