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Efficient exploitation of the Xeon Phi architecture for the Ant Colony Optimization (ACO) metaheuristic

dc.contributor.authorTirado-Marabolí, Felipe
dc.contributor.authorBarrientos, Ricardo
dc.contributor.authorMora, Marco
dc.contributor.authorGonzález-Gutiérrez, Paulo
dc.date.accessioned2018-01-04T18:37:14Z
dc.date.available2018-01-04T18:37:14Z
dc.date.issued2017
dc.identifier.urihttp://repositorio.ucm.cl/handle/ucm/1662
dc.description.abstractIn recent years, the use of compute-intensive coprocessors has been widely studied in the field of Parallel Computing to accelerate sequential processes through a Graphic Processing Unit (GPU). Intel has recently released a GPU-type coprocessor, the Intel Xeon Phi. It is composed up to 72 cores connected by a bidirectional ring network with a Vector Process Unit (VPU) on large vector registers. In this work, we present novel parallel algorithms of the well-known Ant Colony Optimization (ACO) on the recent many-core platform Intel Xeon Phi coprocessor. ACO is a popular metaheuristic algorithm applied to a wide range of NP-hard problems. To show the efficiency of our approaches, we test our algorithms solving the Traveling Salesman Problem. Our results confirm the potential of our proposed algorithms which led to distinct improvements of performance over previous state-of-the-art approaches in GPU. We implement and compare a set of algorithms to deal with the different steps of ACO. The matrices calculation in the proposed algorithms efficiently exploit the VPU and cache in Xeon Phi. We also show a novel implementation of the roulette wheel selection algorithm, named as UV-Roulette (unique random value roulette). We compare our results in Xeon Phi to state-of-the-art GPU methods, achieving higher performance with large size problems. We also exposed the difficulties and key hardware performance factors to deal with the ACO algorithm on a Xeon Phi coprocessor.es_CL
dc.language.isoenes_CL
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 Chile*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/cl/*
dc.sourceThe Journal of Supercomputing, 73(11), 5053-5070es_CL
dc.subjectMetaheuristices_CL
dc.subjectXeon Phies_CL
dc.subjectParallel computinges_CL
dc.subjectCoprocessorses_CL
dc.subjectAnt colony optimizationes_CL
dc.titleEfficient exploitation of the Xeon Phi architecture for the Ant Colony Optimization (ACO) metaheuristices_CL
dc.typeArticlees_CL
dc.ucm.facultadFacultad de Ciencias de la Ingenieríaes_CL
dc.ucm.indexacionScopuses_CL
dc.ucm.indexacionIsies_CL
dc.ucm.urisibib2.ucm.cl:2048/login?url=https://link.springer.com/article/10.1007/s11227-017-2124-5es_CL
dc.ucm.doidoi.org/10.1007/s11227-017-2124-5es_CL


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Atribución-NoComercial-SinDerivadas 3.0 Chile
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