Towards an optimized multi FPGA architecture with STDM network: A preliminary study

Kazuei Hironaka, Ng Anh Vu Doan, Hideharu Amano

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

In this work, we propose a multi FPGA architecture with STDM network that aims to tackle compute-intensive applications such as neural networks training or pattern recognition in artificial intelligence while realizing high cost-performance and energy efficiency. To achieve this goal, optimizing different aspects of the system communication is a key challenge. In order to do this, a preliminary study on the application mapping for both the execution time and the number of slots for the STDM is carried out. An optimization based on a multi-criteria paradigm is implemented and the preliminary results show the possibility to optimize several parameters of the communication simultaneously alongside quantitative analyses of different architecture choices.

Original languageEnglish
Title of host publicationApplied Reconfigurable Computing
Subtitle of host publicationArchitectures, Tools, and Applications - 14th International Symposium, ARC 2018, Proceedings
PublisherSpringer Verlag
Pages142-150
Number of pages9
ISBN (Print)9783319788890
DOIs
Publication statusPublished - 2018 Jan 1
Event14th International Symposium on Applied Reconfigurable Computing, ARC 2018 - Santorini, Greece
Duration: 2018 May 22018 May 4

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10824 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other14th International Symposium on Applied Reconfigurable Computing, ARC 2018
CountryGreece
CitySantorini
Period18/5/218/5/4

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Hironaka, K., Doan, N. A. V., & Amano, H. (2018). Towards an optimized multi FPGA architecture with STDM network: A preliminary study. In Applied Reconfigurable Computing: Architectures, Tools, and Applications - 14th International Symposium, ARC 2018, Proceedings (pp. 142-150). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10824 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-78890-6_12