Proposta de implementação paralela de algoritmo genético em FPGA
Genetic Algorithms (GAs) are used to solve search and optimization problems in which an optimal solution can be found using an iterative process and using probabilistic transitions. However, depending on the type of problem, the time required to find a solution can be high in sequential machines...
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| Formato: | Dissertação |
| Idioma: | por |
| Publicado em: |
Brasil
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| Endereço do item: | https://repositorio.ufrn.br/jspui/handle/123456789/24729 |
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| Resumo: | Genetic Algorithms (GAs) are used to solve search and optimization problems in
which an optimal solution can be found using an iterative process and using probabilistic
transitions. However, depending on the type of problem, the time required to find a solution
can be high in sequential machines due to the computational complexity of genetic
algorithm. This work proposes a parallel implementation of a genetic algorithm on fieldprogrammable
gate array (FPGA). Optimization of the system’s processing time is the
main goal of this project. Results associated with the processing time and area occupancy
(in FPGA) for various population size are analyzed. Studies concerning the accuracy of
the GA response for the optimization of functions with one and two variables were also
analyzed for the hardware implementation. The project was developed using the System
Generator software (Xilinx development platform) and the Virtex-7 xc7vx550t-1ffg1158
FPGA. |
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