A Reconfigurable Custom Machine for Accelerating Cellular Genetic Algorithms

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P. V. Santos
José Carlos Alves
João Canas Ferreira

Abstract

In this work we present a reconfigurable and scalable custom processor array for solving optimization problems using cellular genetic algorithms (cGAs), based on a regular fabric of processing nodes and local memories. Cellular genetic algorithms are a variant of the well-known genetic algorithm that can conveniently exploit the coarse-grain parallelism afforded by this architecture. To ease the design of the proposed computing engine for solving different optimization problems, a high-level synthesis design flow is proposed, where the problem-dependent operations of the algorithm are specified in C++ and synthesized to custom hardware. A spectrum allocation problem was used as a case study and successfully implemented in a Virtex-6 FPGA device, showing relevant figures for the computing acceleration.

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Author Biographies

P. V. Santos, INESC TEC

INESC TEC - INESC Tecnologia e Ciência

Campus da Faculdade de Engenharia da Universidade do Porto

Rua Dr. Roberto Frias

Edifício I

4200-465 PORTO

Portugal

José Carlos Alves, Universidade do Porto

Departamento de Engenharia Eletrotécnica e de Computadores

Faculdade de Engenharia

Universidade do Porto

Rua Dr. Roberto Frias

4200-465 PORTO

Portugal

João Canas Ferreira, Universidade do Porto

Departamento de Engenharia Eletrotécnica e de Computadores

Faculdade de Engenharia

Universidade do Porto

Rua Dr. Roberto Frias

4200-465 PORTO

Portugal