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Title: | An FPGA Framework for Genetic Algorithms: Solving the Minimum Energy Broadcast Problem |
Authors: | dos Santos,PV José Carlos Alves João Canas Ferreira |
Issue Date: | 2015 |
Abstract: | Solving complex optimization problems with genetic algorithms (GAs) with custom computing architectures is a way to improve the execution time of this metaheuristic, which is known to consume considerable amounts of time to converge to final solutions. In this work, we present a scalable computing array architecture to accelerate the execution of cellular GAs (cGAs), a variant of genetic algorithms which can conveniently exploit the coarse- grain parallelism afforded by custom parallel processing. The proposed architecture targets Xilinx FPGAs and is used as an auxiliary processor of an embedded CPU (MicroBlaze). To handle different optimization problems, a high- level synthesis (HLS) design flow is proposed where the problem- dependent operations are specified in C++ and synthesised to custom hardware, thus requiring a minimum knowledge of digital design for FPGAs. The minimum energy broadcast (MEB) problem in wireless ad hoc networks is used as a case study. An existing software implementation of a GA to solve this problem is ported to the proposed computing array to demonstrate its effectiveness and the HLS- based design flow. Implementation results in a Virtex- 6 FPGA show significant speedups, while finding solutions with improved quality. |
URI: | http://repositorio.inesctec.pt/handle/123456789/5555 http://dx.doi.org/10.1109/dsd.2015.81 |
metadata.dc.type: | conferenceObject Publication |
Appears in Collections: | CRAS - Articles in International Conferences CTM - Articles in International Conferences |
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