• Title/Summary/Keyword: Connection-Per-Second (CPS)

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Multiple Network-on-Chip Model for High Performance Neural Network

  • Dong, Yiping;Li, Ce;Lin, Zhen;Watanabe, Takahiro
    • JSTS:Journal of Semiconductor Technology and Science
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    • v.10 no.1
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    • pp.28-36
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    • 2010
  • Hardware implementation methods for Artificial Neural Network (ANN) have been researched for a long time to achieve high performance. We have proposed a Network on Chip (NoC) for ANN, and this architecture can reduce communication load and increase performance when an implemented ANN is small. In this paper, a multiple NoC models are proposed for ANN, which can implement both a small size ANN and a large size one. The simulation result shows that the proposed multiple NoC models can reduce communication load, increase system performance of connection-per-second (CPS), and reduce system running time compared with the existing hardware ANN. Furthermore, this architecture is reconfigurable and reparable. It can be used to implement different applications of ANN.