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

Salvador Perea, Rubén; Moreno González, Félix Antonio; Riesgo Alcaide, Teresa; Vidal, Alberto y Sekanina, Lukás (2012). Accelerating FPGA-based evolution of wavelet transform filters by optimized task scheduling. "Microprocessors and Microsystems", v. 36 (n. 5); pp. 427-438. ISSN 0141-9331. https://doi.org/10.1016/j.micpro.2012.02.002.

Descripción

Título: Accelerating FPGA-based evolution of wavelet transform filters by optimized task scheduling
Autor/es:
  • Salvador Perea, Rubén
  • Moreno González, Félix Antonio
  • Riesgo Alcaide, Teresa
  • Vidal, Alberto
  • Sekanina, Lukás
Tipo de Documento: Artículo
Título de Revista/Publicación: Microprocessors and Microsystems
Fecha: Julio 2012
Volumen: 36
Materias:
Palabras Clave Informales: Evolvable hardware, FPGA, Bio-inspired architectures, Adaptive embedded systems, Adaptive image compression, Evolutionary Computation, Evolved wavelet transforms, Filter optimization
Escuela: E.U.I.T. Telecomunicación (UPM) [antigua denominación]
Departamento: Sistemas Electrónicos y de Control [hasta 2014]
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

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.

Más información

ID de Registro: 15939
Identificador DC: http://oa.upm.es/15939/
Identificador OAI: oai:oa.upm.es:15939
Identificador DOI: 10.1016/j.micpro.2012.02.002
URL Oficial: http://www.sciencedirect.com/science/article/pii/S0141933112000191
Depositado por: Memoria Investigacion
Depositado el: 18 Nov 2013 18:54
Ultima Modificación: 23 Feb 2017 17:31
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