Energy efficient video fusion with heterogeneous CPU-FPGA devices

Peng Sun, Alin Achim, Ian Hasler, Paul Hill, Jose Nunez-Yanez

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

2 Citations (Scopus)
275 Downloads (Pure)


This paper presents a complete video fusion system with hardware acceleration and investigates the energy trade-offs between computing in the CPU or the FPGA device. 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 and also vectorized code for the single instruction multiple data (SIMD) engine available in the CPU. The accelerated system reduces computation time and energy by a factor of 2. Moreover, the results show a key finding that the FPGA is not always the best choice for acceleration, and the SIMD engine should be selected when the wavelet decomposition reduces the frame size below a certain threshold. This dependency on workload size means that an adaptive system that intelligently selects between the SIMD engine and the FPGA achieves the most energy and performance efficiency point.

Original languageEnglish
Title of host publication2016 Design, Automation & Test in Europe Conference & Exhibition (DATE 2016)
Subtitle of host publicationProceedings of a meeting held 14-18 March 2016, Dresden, Germany
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages6
ISBN (Electronic)9783981537062
ISBN (Print)9781467392280
Publication statusPublished - Jun 2016
Event19th Design, Automation and Test in Europe Conference and Exhibition, DATE 2016 - Dresden, Germany
Duration: 14 Mar 201618 Mar 2016


Conference19th Design, Automation and Test in Europe Conference and Exhibition, DATE 2016


  • Energy efficient
  • Hybrid FPGA
  • video fusion


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