Computing to the Limit with Heterogeneous CPU-FPGA Devices in a Video Fusion Application

Jose L Nunez-Yanez*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

1 Citation (Scopus)
466 Downloads (Pure)


This paper presents a complete video fusion system with hardware acceleration and investigates its performance and energy optimization. The video fusion application is based on the Dual-Tree Complex Wavelet Transforms (DT-CWT). Video fusion combines information from different spectral bands into a single representation and advanced algorithms based on wavelet transforms are compute and energy intensive. In this work the transforms are mapped to a hardware accelerator using high-level synthesis tools for the FPGA resulting in an increase of performance of the system by a factor of 3. In a second stage the hardware engine is transformed with a set of tools and detector blocks that allow the CPU device to monitor and pre-detect timing failures in the FPGA fabric. The CPU device can control the voltage and frequency of the FPGA and obtain a new working point with reducing power requirements by approximately 70 % with an equivalent performance level. This results in an energy proportional computing system in which only the energy required to maintain a required level of performance is used.

Original languageEnglish
Title of host publicationApplied Reconfigurable Computing
Subtitle of host publication12th International Symposium, ARC 2016 Mangaratiba, RJ, Brazil, March 22–24, 2016 Proceedings
EditorsVanderlei Bonato, Christos Bouganis, Marek Gorgon
PublisherSpringer Verlag
Number of pages13
ISBN (Electronic)9783319304816
ISBN (Print)9783319304809
Publication statusPublished - 13 Mar 2016
Event12th International Symposium on Applied Reconfigurable Computing, ARC 2016 - Mangaratiba, Brazil
Duration: 22 Mar 201624 Mar 2016

Publication series

NameLecture Notes in Computer Science
PublisherSpringer International Publishing
ISSN (Print)0302-9743


Conference12th International Symposium on Applied Reconfigurable Computing, ARC 2016


  • fusion
  • fpga
  • ARM
  • ZYNQ
  • energy efficient


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