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A multiobjective evolutionary algorithm-based optimisation model for network on chip synthesis

机译:基于多目标进化算法的片上网络综合优化模型

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Network on Chip (NoC) is a new paradigm for design core-based System on Chip (SoC). It is expected to provide higher computation power due to its higher clock frequencies and parallel execution of processes. This paper addresses the problem of topological mapping of Intellectual Properties (IPs) on the tile of a mesh-based NoC. As the stated problem is NP-hard in nature, we propose a heuristic technique based on multiobjective Genetic Algorithm (GA) to obtain an optimal approximation of the pereto-optimal front. The evaluation performed on three randomly generated benchmarks and a real application (a M-JPEG encoder) to conform the efficiency, accuracy and scalability of the proposed approach. Our proposed approach saves up to 15-20% of energy and more than 15% of bandwidth requirement compared with the existing approaches.
机译:片上网络(NoC)是用于设计基于内核的片上系统(SoC)的新范例。由于其更高的时钟频率和进程的并行执行,有望提供更高的计算能力。本文解决了在基于网格的NoC的图块上对知识产权(IP)进行拓扑映射的问题。由于所陈述的问题本质上是NP难题,因此我们提出了一种基于多目标遗传算法(GA)的启发式技术,以获取最佳的前向最优阵线近似值。评估是在三个随机生成的基准和一个实际应用程序(一个M-JPEG编码器)上进行的,以符合所提出方法的效率,准确性和可伸缩性。与现有方法相比,我们提出的方法可节省多达15-20%的能源和超过15%的带宽需求。

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