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Comparative evaluation of platforms for parallel Ant Colony Optimization

Gines D. Guerrero, Jose M. Cecilia, Antonio Llanes, Jose M. Garcia, Martyn Amos, Manuel Ujaldon
National Laboratory for High Performance Computing, University of Chile, Chile
University of Chile, 2014

@article{guerrero2014comparative,

   title={Comparative evaluation of platforms for parallel Ant Colony Optimization},

   author={Guerrero, Gines D. and Cecilia, Jose M. and Llanes, Antonio and Garcia, Jose M. and Amos, Martyn and Ujaldon, Manuel},

   year={2014}

}

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The rapidly growing field of nature-inspired computing concerns the development and application of algorithms and methods based on biological or physical principles. This approach is particularly compelling for practitioners in high-performance computing, as natural algorithms are often inherently parallel in nature (for example, they may be based on a "swarm"-like model that uses a population of agents to optimize a function). Coupled with rising interest in nature-based algorithms is the growth in heterogeneous computing; systems that use more than one kind of processor. We are therefore interested in the performance characteristics of nature-inspired algorithms on a number of different platforms. To this end, we present a new OpenCL-based implementation of the Ant Colony Optimization algorithm, and use it as the basis of extensive experimental tests. We benchmark the algorithm against existing implementations, on a wide variety of hardware platforms, and offer extensive analysis. This work provides rigorous foundations for future investigations of Ant Colony Optimization on high-performance platforms.
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