Detail publikace

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

Originální název

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

Anglický název

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

Jazyk

en

Originální abstrakt

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 2 min whenever the input type of data changes.

Anglický abstrakt

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 2 min whenever the input type of data changes.

BibTex


@article{BUT96948,
  author="Ruben {Salvador} and Alberto {Vidal} and Felix {Moreno} and Teresa {Riesgo} and Lukáš {Sekanina}",
  title="Accelerating FPGA-based evolution of wavelet transform filters by optimized task scheduling",
  annote="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 2 min
whenever the input type of data changes.",
  address="NEUVEDEN",
  chapter="96948",
  doi="10.1016/j.micpro.2012.02.002",
  edition="NEUVEDEN",
  howpublished="print",
  institution="NEUVEDEN",
  number="5",
  volume="36",
  year="2012",
  month="june",
  pages="427--438",
  publisher="NEUVEDEN",
  type="journal article in Web of Science"
}