The 81st JSAP Autumn Meeting, 2020

Presentation information

Oral presentation

13 Semiconductors » 13.1 Fundamental properties, surface and interface, and simulations of Si related materials

[10p-Z09-1~20] 13.1 Fundamental properties, surface and interface, and simulations of Si related materials

Thu. Sep 10, 2020 12:30 PM - 6:00 PM Z09

Koichiro Saga(Sony), Nobuya Mori(Osaka Univ.), Takashi Hasunuma(Univ. of Tsukuba)

4:30 PM - 4:45 PM

[10p-Z09-15] A Simulation Study on the System Performance of Neural Networks using Embedded Nonvolatile Memory

〇(M2)Paul Davin Johansen1,2, Masaharu Kobayashi1,2 (1.Inst. of Industrial Science, 2.University of Tokyo)

Keywords:neural network, nonvolatile memory

Hardware neural networks (HNNs) can provide faster training/inference latency and reduced power consumption than neural networks implemented via software. While neural networks have been studied extensively, as of yet, there has been little research on how device configuration and variability can affect performance metrics for neural networks on a system level. In this simulation study, several system performance metrics such as accuracy, latency, and energy consumption for HNNs were analyzed.