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  • In this paper, a hardware platform for coevolutionary cartesian genetic programming is proposed. The proposed two-population coevolutionary algorithm involves the implementation of search algorithms in two MicroBlaze soft processors (one for each population) interconnected by the AXI bus in Xilinx Virtex 6 FPGA. Candidate programs are evaluated in a domain-specific virtual reconfigurable circuit incorporated into custom MicroBlaze peripheral. Experimental results in the task of evolutionary image filter design show that we can achieve a significant speed-up (up to 58) in comparison with a highly optimized software implementation.
  • In this paper, a hardware platform for coevolutionary cartesian genetic programming is proposed. The proposed two-population coevolutionary algorithm involves the implementation of search algorithms in two MicroBlaze soft processors (one for each population) interconnected by the AXI bus in Xilinx Virtex 6 FPGA. Candidate programs are evaluated in a domain-specific virtual reconfigurable circuit incorporated into custom MicroBlaze peripheral. Experimental results in the task of evolutionary image filter design show that we can achieve a significant speed-up (up to 58) in comparison with a highly optimized software implementation. (en)
Title
  • Coevolutionary Cartesian Genetic Programming in FPGA
  • Coevolutionary Cartesian Genetic Programming in FPGA (en)
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  • Coevolutionary Cartesian Genetic Programming in FPGA
  • Coevolutionary Cartesian Genetic Programming in FPGA (en)
skos:notation
  • RIV/00216305:26230/13:PU106355!RIV14-GA0-26230___
http://linked.open...avai/predkladatel
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  • P(GAP103/10/1517), S
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  • 65873
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  • RIV/00216305:26230/13:PU106355
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  • Cartesian genetic programming, coevolutionary algortihms, fitness modeling, hardware acceleration, FPGA. (en)
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  • [7E5DFEF71F92]
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  • Taormina
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  • Cambridge
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  • Advances in Artificial Life, ECAL 2013, Proceedings of the Twelfth European Conference on the Synthesis and Simulation of Living Systems
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  • Hrbáček, Radek
  • Šikulová, Michaela
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number of pages
http://bibframe.org/vocab/doi
  • 10.7551/978-0-262-31709-2-ch062
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  • MIT Press
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  • 978-0-262-31709-2
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  • 26230
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