Presentation 2020-03-05
[Memorial Lecture] A Tuning-Free Hardware Reservoir Based on MOSFET Crossbar Array for Practical Echo State Network Implementation
Yuki Kume, Song Bian, Takashi Sato,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Echo state network (ESN) is a class of recurrent neural network, and is known for drastically reducing the training time by the use of reservoir, a random and fixed network as the input and middle layers. In this paper, we propose a hardware implementation of ESN that uses practical MOSFET-based reservoir. As opposed to existing reservoirs that require additional tuning of network weights for improved stability, ourESN requires no post-training parameter tuning. To this end, we apply the circular law of random matrix to sparse reservoirs to determine a stable and fixed feedback gain. Through the evaluations using Mackey-Glass time-series dataset, the proposed ESN performs successful inference without post parameter tuning.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) echo state network / reservoir computing / recurrent neural network / MOSFET / crossbar array
Paper # VLD2019-118,HWS2019-91
Date of Issue 2020-02-26 (VLD, HWS)

Conference Information
Committee HWS / VLD
Conference Date 2020/3/4(4days)
Place (in Japanese) (See Japanese page)
Place (in English) Okinawa Ken Seinen Kaikan
Topics (in Japanese) (See Japanese page)
Topics (in English) Design Technology for System-on-Silicon, Hardware Security, etc.
Chair Shinichi Kawamura(Toshiba) / Nozomu Togawa(Waseda Univ.)
Vice Chair Makoto Ikeda(Univ. of Tokyo) / Yasuhisa Shimazaki(Renesas Electronics) / Daisuke Fukuda(Fujitsu Labs.)
Secretary Makoto Ikeda(SECOM) / Yasuhisa Shimazaki(Kyushu Univ.) / Daisuke Fukuda(Univ. of Aizu)
Assistant / Kazuki Ikeda(Hitachi)

Paper Information
Registration To Technical Committee on Hardware Security / Technical Committee on VLSI Design Technologies
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) [Memorial Lecture] A Tuning-Free Hardware Reservoir Based on MOSFET Crossbar Array for Practical Echo State Network Implementation
Sub Title (in English)
Keyword(1) echo state network
Keyword(2) reservoir computing
Keyword(3) recurrent neural network
Keyword(4) MOSFET
Keyword(5) crossbar array
1st Author's Name Yuki Kume
1st Author's Affiliation Kyoto University(Kyoto Univ.)
2nd Author's Name Song Bian
2nd Author's Affiliation Kyoto University(Kyoto Univ.)
3rd Author's Name Takashi Sato
3rd Author's Affiliation Kyoto University(Kyoto Univ.)
Date 2020-03-05
Paper # VLD2019-118,HWS2019-91
Volume (vol) vol.119
Number (no) VLD-443,HWS-444
Page pp.pp.139-144(VLD), pp.139-144(HWS),
#Pages 6
Date of Issue 2020-02-26 (VLD, HWS)