FPGA-based deep-pipelined architecture for FDTD acceleration using OpenCL

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

13 Citations (Scopus)

Abstract

Acceleration of the FDTD (finite-difference time-domain) computation is very important for the electromagnetic simulations. Conventional FDTD acceleration methods using multicore CPUs and CPUs have the common problem of memory-bandwidth limitation due to a large amount of parallel data access. Although FPGAs have the potential to solve this problem, very long design, testing and debugging time is required to implement an architecture successfully. To solve this problem, we propose an FPGA architecture designed using C-like programming language called OpenCL (open computing language). Therefore, the design time is very small and extensive knowledge about hardware-design is not required. We implemented the proposed architecture on an FPGA and achieved over 114 GFLOPS of processing power. We also achieved more than 13 times and 4 times speed-up compared to CPU and GPU implementations respectively.

Original languageEnglish
Title of host publication2016 IEEE/ACIS 15th International Conference on Computer and Information Science, ICIS 2016 - Proceedings
EditorsKuniaki Uehara, Masahide Nakamura
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509008063
DOIs
Publication statusPublished - 2016 Aug 23
Event15th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2016 - Okayama, Japan
Duration: 2016 Jun 262016 Jun 29

Publication series

Name2016 IEEE/ACIS 15th International Conference on Computer and Information Science, ICIS 2016 - Proceedings

Other

Other15th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2016
CountryJapan
CityOkayama
Period16/6/2616/6/29

Keywords

  • FDTD
  • OpenCL for FPGA
  • accelerator
  • stencil computation

ASJC Scopus subject areas

  • Computer Science(all)
  • Energy Engineering and Power Technology
  • Control and Optimization

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