| Presentation | 2017-05-22 CNN implementation on FPGA with Power of 2 Approximation of Weight Takahiro Utsunomiya, Motoki Amagasaki, Masahiro Iida, Morihiro Kuga, Toshinori Sueyoshi, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Convolutional Neural Network (CNN), a method of Image recognition, is utilized in various fields. Considering CNN implementation to embedded devices, Field Programmable Gate Array (FPGA) is one of the promising medium. The feature of FPGA is high speed processing with low power. There are enormous number of multiply-add operations in Fully Connected (FC) layers of CNN. Therefore, for CNN implementation on FPGA, it is required to consider the resource utilization of multiply-add circuit and memory access for weight of neural network. In this paper, we propose power of 2 approximation of weight in FC layers of CNN. This method enables multiply-add circuit to be configured by Shifter and Adder. Our proposed method improved LUT consumption up to 10.7 times and operating frequency up to 2.6 times. Furthermore, the bit width required for weight was reduced to 3 bits. In this case, deterioration of recognition accuracy was suppressed to about 1%. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | FPGA / Deep Learning / CNN |
| Paper # | RECONF2017-6 |
| Date of Issue | 2017-05-15 (RECONF) |
| Conference Information | |
| Committee | RECONF / CPSY / DC / IPSJ-ARC |
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| Conference Date | 2017/5/22(3days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Noboribetsu-Onsen Dai-ichi-Takimoto-Kan |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | HotSPA2017: Reconfigurable System, Dependable Computing System, and General Topics |
| Chair | Minoru Watanabe(Shizuoka Univ.) / Yasuhiko Nakashima(NAIST) / Michiko Inoue(NAIST) |
| Vice Chair | Masato Motomura(Hokkaido Univ.) / Yuichiro Shibata(Nagasaki Univ.) / Koji Nakano(Hiroshima Univ.) / Hidetsugu Irie(Univ. of Tokyo) / Satoshi Fukumoto(Tokyo Metropolitan Univ.) |
| Secretary | Masato Motomura(Univ. of Tsukuba) / Yuichiro Shibata(Hiroshima City Univ.) / Koji Nakano(Fujitsu Labs.) / Hidetsugu Irie(NII) / Satoshi Fukumoto(Kyoto Sangyo Univ.) / (Tokyo Inst. of Tech.) |
| Assistant | Takefumi Miyoshi(e-trees.Japan) / Yuuki Kobayashi(NEC) / Takeshi Ohkawa(Utsunomiya Univ.) / Shinya Takameda(Hokkaido Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Reconfigurable Systems / Technical Committee on Computer Systems / Technical Committee on Dependable Computing / Special Interest Group on System Architecture |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | CNN implementation on FPGA with Power of 2 Approximation of Weight |
| Sub Title (in English) | |
| Keyword(1) | FPGA |
| Keyword(2) | Deep Learning |
| Keyword(3) | CNN |
| 1st Author's Name | Takahiro Utsunomiya |
| 1st Author's Affiliation | Kumamoto University(Kumamoto Univ.) |
| 2nd Author's Name | Motoki Amagasaki |
| 2nd Author's Affiliation | Kumamoto University(Kumamoto Univ.) |
| 3rd Author's Name | Masahiro Iida |
| 3rd Author's Affiliation | Kumamoto University(Kumamoto Univ.) |
| 4th Author's Name | Morihiro Kuga |
| 4th Author's Affiliation | Kumamoto University(Kumamoto Univ.) |
| 5th Author's Name | Toshinori Sueyoshi |
| 5th Author's Affiliation | Kumamoto University(Kumamoto Univ.) |
| Date | 2017-05-22 |
| Paper # | RECONF2017-6 |
| Volume (vol) | vol.117 |
| Number (no) | RECONF-46 |
| Page | pp.pp.25-30(RECONF), |
| #Pages | 6 |
| Date of Issue | 2017-05-15 (RECONF) |