Deep learning on high performance FPGA switching boards: Flow-in-cloud

Kazusa Musha, Tomohiro Kudoh, Hideharu Amano

研究成果: Conference contribution

1 引用 (Scopus)

抜粋

FiC (Flow-in-Cloud)-SW is an FPGA-based switching node for an efficient AI computing system. It is equipped with a number of serial links directly connected to other nodes. Unlike other multi-FPGA systems, the circuit switching fabric with the STDM (Static Time Division Multiplexing) is implemented on the FPGA for predictable communication and cost-efficient data broadcasting. Parallel convolution modules for AlexNet are implemented on FiC-SW1 prototype boards consisting of Kintex Ultrascale FPGA, and evaluation results show that the parallel execution with 20 boards achieved 4.6 times better performance than the state of art implementation on a single Virtex 7 FPGA board.

元の言語English
ホスト出版物のタイトルApplied Reconfigurable Computing
ホスト出版物のサブタイトルArchitectures, Tools, and Applications - 14th International Symposium, ARC 2018, Proceedings
出版者Springer Verlag
ページ43-54
ページ数12
ISBN(印刷物)9783319788890
DOI
出版物ステータスPublished - 2018 1 1
イベント14th International Symposium on Applied Reconfigurable Computing, ARC 2018 - Santorini, Greece
継続期間: 2018 5 22018 5 4

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
10824 LNCS
ISSN(印刷物)0302-9743
ISSN(電子版)1611-3349

Other

Other14th International Symposium on Applied Reconfigurable Computing, ARC 2018
Greece
Santorini
期間18/5/218/5/4

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • これを引用

    Musha, K., Kudoh, T., & Amano, H. (2018). Deep learning on high performance FPGA switching boards: Flow-in-cloud. : Applied Reconfigurable Computing: Architectures, Tools, and Applications - 14th International Symposium, ARC 2018, Proceedings (pp. 43-54). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 巻数 10824 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-78890-6_4