An interval-based mapping algorithm for multi-shape tasks on dynamic partial reconfigurable FPGAs

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

1 Citation (Scopus)

Abstract

The Dynamic Partial Reconfiguration (DPR) feature of reconfigurable devices allows multiple tasks to be implemented on a single device simultaneously. However, a task mapping problem emerges with the parallelism of the FPGA, especially in a real-time system, a task mapping position has to be quickly determined with a requirement of efficient usage for limited FPGA resources. Traditional task mapping algorithms simplify the task as a rectangular shape, which results in the additional internal unused areas, thus wasting a significant portion of FPGA resources. In this paper, a task mapping algorithm for the multi-shape tasks based on an interval list is proposed. Simulation results demonstrate that the FPGA utilization ratio is improved by at least 10.3% compared with existing algorithms.

Original languageEnglish
Title of host publicationProceedings - 2020 IEEE 34th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages127-130
Number of pages4
ISBN (Electronic)9781728174457
DOIs
Publication statusPublished - 2020 May
Event34th IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2020 - New Orleans, United States
Duration: 2020 May 182020 May 22

Publication series

NameProceedings - 2020 IEEE 34th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2020

Conference

Conference34th IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2020
CountryUnited States
CityNew Orleans
Period20/5/1820/5/22

Keywords

  • FPGA
  • Multi-shape tasks
  • Reconfigurable computing
  • Task mapping algorithm

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Safety, Risk, Reliability and Quality
  • Control and Optimization

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