Presentation 2021-09-10
Convolutional neural network implementations using Vitis AI
Akihiko Ushiroyama, Nobuya Watanabe, Akira Nagoya, Minoru Watanabe,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Recently, Xilinx provides an FPGA-based Vitis AI development environment which is one of deep learning frameworks to accelerate AI operations and to search a suitable neural network construction for a target application. In this paper, we've implemented three types of convolutional neural networks onto the Vitis AI development environment and evaluated the performance, power consumption, lines of code, and so on. As a result, we have confirmed the advantages of the Vitis AI. For example, the energy consumption of the FPGA platform is 5.06 times lower than that of a GPU.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Convolutional Neural Network (CNN) / FPGA / Vitis AI
Paper # RECONF2021-19
Date of Issue 2021-09-03 (RECONF)

Conference Information
Committee RECONF
Conference Date 2021/9/10(1days)
Place (in Japanese) (See Japanese page)
Place (in English) Online
Topics (in Japanese) (See Japanese page)
Topics (in English) Reconfigurable system, etc.
Chair Kentaro Sano(RIKEN)
Vice Chair Yoshiki Yamaguchi(Tsukuba Univ.) / Tomonori Izumi(Ritsumeikan Univ.)
Secretary Yoshiki Yamaguchi(NEC) / Tomonori Izumi(Tokyo Inst. of Tech.)
Assistant Yukitaka Takemura(INTEL) / Yasunori Osana(Ryukyu Univ.)

Paper Information
Registration To Technical Committee on Reconfigurable Systems
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Convolutional neural network implementations using Vitis AI
Sub Title (in English)
Keyword(1) Convolutional Neural Network (CNN)
Keyword(2) FPGA
Keyword(3) Vitis AI
1st Author's Name Akihiko Ushiroyama
1st Author's Affiliation Okayama University(Okayama Univ.)
2nd Author's Name Nobuya Watanabe
2nd Author's Affiliation Okayama University(Okayama Univ.)
3rd Author's Name Akira Nagoya
3rd Author's Affiliation Okayama University(Okayama Univ.)
4th Author's Name Minoru Watanabe
4th Author's Affiliation Okayama University(Okayama Univ.)
Date 2021-09-10
Paper # RECONF2021-19
Volume (vol) vol.121
Number (no) RECONF-175
Page pp.pp.13-18(RECONF),
#Pages 6
Date of Issue 2021-09-03 (RECONF)