Accelerating FPGA-based evolution of wavelet transform filters by optimized task scheduling

  • Authors:
  • Ruben Salvador;Alberto Vidal;Felix Moreno;Teresa Riesgo;Lukas Sekanina

  • Affiliations:
  • Centre of Industrial Electronics, Universidad Politécnica de Madrid, José Gutierrez Abascal 2, 28006 Madrid, Spain;Centre of Industrial Electronics, Universidad Politécnica de Madrid, José Gutierrez Abascal 2, 28006 Madrid, Spain;Centre of Industrial Electronics, Universidad Politécnica de Madrid, José Gutierrez Abascal 2, 28006 Madrid, Spain;Centre of Industrial Electronics, Universidad Politécnica de Madrid, José Gutierrez Abascal 2, 28006 Madrid, Spain;IT4Innovations Centre of Excellence, Faculty of Information Technology, Brno University of Technology, Boetchova 2, 612 66 Brno, Czech Republic

  • Venue:
  • Microprocessors & Microsystems
  • Year:
  • 2012

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Abstract

Adaptive embedded systems are required in various applications. This work addresses these needs in the area of adaptive image compression in FPGA devices. A simplified version of an evolution strategy is utilized to optimize wavelet filters of a Discrete Wavelet Transform algorithm. We propose an adaptive image compression system in FPGA where optimized memory architecture, parallel processing and optimized task scheduling allow reducing the time of evolution. The proposed solution has been extensively evaluated in terms of the quality of compression as well as the processing time. The proposed architecture reduces the time of evolution by 44% compared to our previous reports while maintaining the quality of compression unchanged with respect to existing implementations. The system is able to find an optimized set of wavelet filters in less than 2min whenever the input type of data changes.