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Particle Swarm Optimization on a GPU

Authors: Mikhail Rabinovich; Phillip Kainga; David Johnson; Brandon Shafer; Jaehwan John Lee; Rusell Eberhart;

Particle Swarm Optimization on a GPU

Abstract

Optimization problems that contain discontinuities, non-linearity, or high dimensionality are difficult to solve and time consuming using conventional computational methods. This paper introduces a tool that solves these kinds of optimization problems using a patent pending Gaming Particle Swarm Optimization (GPSO) algorithm implemented on Graphics Processing Unit (GPU) hardware. Our study applied this utility to a radio frequency resource allocation optimizer. This tool, implemented on an Nvidia GTX 465, resulted in 5X performance gain over a state-of-the-art AMD Phenom 3.4GHz quad-core CPU. This study provides a powerful tool that may be used for solving various multi-disciplinary optimization problems such as training of artificial neural networks, function maximization/minimization, autotuning for universal mobile telecommunication system networks, as well as scheduling.

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    influence
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
10
Average
Top 10%
Top 10%
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