Multi-Objective Genetic optimized multiprocessor SoC design

M. Arjomand, H. Sarbazi-Azad, S. Amiri
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引用次数: 4

Abstract

In this paper, we introduce a new multi-objective genetic algorithm (MOGA) for mapping a given set of intellectual property onto a network-on-chip architecture such that for a specific application total communication cost and energy consumption become optimized while bandwidth constraints are satisfied. As the main theoretical contribution, we first introduce a generic queuing model to estimate performance and an experimental energy consumption model during the design phase, with acceptable accuracy. Then, an efficient genetic algorithm employs these models to propose a Pareto optimal front for an application and an arbitrary topology. Experimental results show that the proposed algorithm is very fast which results in a new approach for mapping MPSoC cores on chip.
多目标遗传优化的多处理器SoC设计
本文介绍了一种新的多目标遗传算法(MOGA),用于将给定的一组知识产权映射到片上网络架构上,从而在满足带宽约束的情况下优化特定应用的总通信成本和能耗。作为主要的理论贡献,我们首先引入了一个通用的排队模型来估计性能,并在设计阶段引入了一个实验能耗模型,精度可以接受。然后,利用这些模型提出了一种有效的遗传算法,为应用程序和任意拓扑结构提出了Pareto最优前沿。实验结果表明,该算法的速度非常快,为MPSoC内核的片上映射提供了一种新的方法。
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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