Power-aware multi-objective evolvable hardware system on an FPGA

B. Lopez, J. Valverde, E. D. L. Torre, T. Riesgo
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引用次数: 11

Abstract

Dynamic and Partial Reconfiguration (DPR) allows a system to be able to modify certain parts of itself during run-time. This feature gives rise to the capability of evolution: changing parts of the configuration according to the online evaluation of performance or other parameters. The evolution is achieved through a bio-inspired model in which the features of the system are identified as genes. The objective of the evolution may not be a single one; in this work, power consumption is taken into consideration, together with the quality of filtering, as the measure of performance, of a noisy image. Pareto optimality is applied to the evolutionary process, in order to find a representative set of optimal solutions as for performance and power consumption. The main contributions of this paper are: implementing an evolvable system on a low-power Spartan-6 FPGA included in a Wireless Sensor Network node and, by enabling the availability of a real measure of power consumption at run-time, achieving the capability of multi-objective evolution, that yields different optimal configurations, among which the selected one will depend on the relative “weights” of performance and power consumption.
基于FPGA的功率感知多目标演化硬件系统
动态和部分重新配置(DPR)允许系统在运行时修改自身的某些部分。这个特性产生了演化能力:根据对性能或其他参数的在线评估来改变部分配置。这种进化是通过一种受生物启发的模型实现的,在这种模型中,系统的特征被识别为基因。进化的目标可能不是单一的;在这项工作中,考虑了功耗和滤波质量,作为噪声图像性能的衡量标准。将帕累托最优性应用于进化过程中,以寻找具有代表性的性能和功耗最优解集。本文的主要贡献是:在包含在无线传感器网络节点中的低功耗Spartan-6 FPGA上实现可进化系统,并通过在运行时提供真实的功耗度量,实现多目标进化的能力,从而产生不同的最佳配置,其中所选择的配置将取决于性能和功耗的相对“权重”。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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