Area-energy aware dataflow optimisation of visual tracking systems

Paulo Garcia, Deepayan Bhowmik*, Andrew Wallace, Robert Stewart, Greg Michaelson

*Corresponding author for this work

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

1 Citation (Scopus)
23 Downloads (Pure)


This paper presents an orderly dataflow-optimisation approach suitable for area-energy aware computer vision applications on FPGAs. Vision systems are increasingly being deployed in power constrained scenarios, where the dataflow model of computation has become popular for describing complex algorithms. Dataflow model allows processing datapaths comprised of several independent and well defined computations. However, compilers are often unsuccessful in identifying domain-specific optimisation opportunities resulting in wasted resources and power consumption. We present a methodology for the optimisation of dataflow networks, according to patterns often found in computer vision systems, focusing on identifying optimisations which are not discovered automatically by an optimising compiler. Code transformation using profiling and refactoring provides opportunities to optimise the design, targeting FPGA implementations and focusing on area and power abatement. Our refactoring methodology, applying transformations to a complex algorithm for visual tracking resulted in significant reduction in power consumption and resource usage.

Original languageEnglish
Title of host publicationApplied Reconfigurable Computing
Subtitle of host publicationArchitectures, Tools, and Applications
Number of pages14
ISBN (Electronic)9783319788906
ISBN (Print)9783319788890
Publication statusPublished - 8 Apr 2018
Event14th International Symposium on Applied Reconfigurable Computing 2018 - Santorini, Greece
Duration: 2 May 20184 May 2018

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference14th International Symposium on Applied Reconfigurable Computing 2018
Abbreviated titleARC 2018

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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