| Presentation | 2020-03-06 Performance Evaluation of Echo State Networks with Hardware Reservoirs Yuki Kume, Song Bian, Kenta Nagura, Takashi Sato, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Echo state Network (ESN), a class of recurrent neural network, is characteristic in its use of a reservoir having random and constant weights during training and inference computations. ESN is suitable for hardware implementation because of its low training cost and simple neural architecture. Recently, MOS-ESN is proposed to implement ESN by using hardware reservoir consists of physical metal-oxide-semiconductor field effect transistors (MOSFETs). The variations in MOSFETs are used as the source of the random weights without the need to manually tune the parameters for stability. MOS-ESN and the related Dual-MOS-ESN architecture demonstrates high inference accuracy on a particular dataset, but the evaluation is inadequate. In this paper, we conduct a more thorough performance evaluation for Dual-MOS-ESN and other similar hardware reservoir structures. Through the evaluation, we show the effectiveness of the dual architecture across datasets in comparison with other MOS-ESN architectures. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | echo state network / reservoir computing / recurrent neural network / MOSFET / crossbar array |
| Paper # | VLD2019-136,HWS2019-109 |
| Date of Issue | 2020-02-26 (VLD, HWS) |
| Conference Information | |
| Committee | HWS / VLD |
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| 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 |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Performance Evaluation of Echo State Networks with Hardware Reservoirs |
| 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 | Kenta Nagura |
| 3rd Author's Affiliation | Kyoto University(Kyoto Univ.) |
| 4th Author's Name | Takashi Sato |
| 4th Author's Affiliation | Kyoto University(Kyoto Univ.) |
| Date | 2020-03-06 |
| Paper # | VLD2019-136,HWS2019-109 |
| Volume (vol) | vol.119 |
| Number (no) | VLD-443,HWS-444 |
| Page | pp.pp.245-250(VLD), pp.245-250(HWS), |
| #Pages | 6 |
| Date of Issue | 2020-02-26 (VLD, HWS) |