粒子群优化在FPSoC器件中的实现

Roberto Fernández Molanes, Martin Garaj, W. Tang, J. Rodríguez-Andina, J. Fariña, K. Tsang, Kim-Fung Man
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引用次数: 3

摘要

粒子群算法(PSO)是一种广泛应用于求解具有非线性目标函数的复杂优化问题的算法。PSO通常需要强大而昂贵的计算机来实现合理的执行时间。有时,计算系统的价格或大小是不可接受的,迫使设计者简化目标函数或放弃粒子群算法。为了克服这一限制,本文提出了PSO在现场可编程片上系统(fpsoc)中的实现。FPSoC器件在同一芯片中结合了强大的处理器和可重构逻辑(FPGA结构)。实验结果表明,该系统以很小的成本和体积实现了与台式计算机相似的性能。可以清楚地得出结论,所建议的系统是在设计和最终应用程序部署级别运行PSO的好选择。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Implementation of Particle Swarm Optimization in FPSoC devices
Particle Swarm Optimization (PSO) is a widely used algorithm to solve complex optimization problems with non-linear objective functions. PSO usually requires powerful and expensive computers to achieve reasonable execution times. Sometimes the price or size of the computing system is unacceptable, forcing designers to simplify the objective function or to discard PSO. To overcome this limitation, this paper proposes the implementation of PSO in Field Programmable Systems-on-Chip (FPSoCs). FPSoC devices combine in the same chip powerful processors and reconfigurable logic (FPGA fabric). Experimental results are presented demonstrating that the proposed system achieves a performance similar to that of a desktop computer for a fraction of cost and size. It can be clearly concluded that the proposed system is a good option for running PSO both at design and final application deployment levels.
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