Skip to main navigation Skip to search Skip to main content

Hardware Architecture of Stochastic Computing Neural Network

  • Yuhao Chen
  • , Yinjie Song
  • , Yanan Zhu
  • , Yunfei Gao
  • , Hongge Li*
  • *Corresponding author for this work
  • Beihang University

Research output: Contribution to journalArticlepeer-review

Abstract

Stochastic computing is a kind of logic calculation that converts binary into probabilistic coded digital pulse stream. At the cost of computing power and time delay, it has the computing advantages of low power consumption and high energy efficiency. In this paper, the basic concept of stochastic computing is explained, and a stochastic computing circuit with single-channel or multi-channel is designed to improve the speed and accuracy. Based on the stochastic computing circuit, the stochastic pulse neuron is designed, and the reconfigurable computing architecture of neural network, BUAA-ChouSuan, is realized. The design is implemented with KINTEX-7 (FPGA), the logic resource (lookup table, LUT) of stochastic MAC (multiply accumulate) is 80% lower than that of traditional MAC. In SCNN (stochastic convolutional neural network) experiment, LeNet and AlexNet are tested. Under the condition of 350 MHz clock frequency, the average energy efficiency can reach 0.536 TSOPS/W, and the utilization rate of processing unit (PE) can reach more than 90%.

Original languageEnglish
Pages (from-to)2105-2115
Number of pages11
JournalJournal of Frontiers of Computer Science and Technology
Volume15
Issue number11
DOIs
StatePublished - 2021

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • brain like chip
  • low power consumption
  • spiking neural network
  • stochastic computing

Fingerprint

Dive into the research topics of 'Hardware Architecture of Stochastic Computing Neural Network'. Together they form a unique fingerprint.

Cite this