Application-specific Network-on-Chip architecture synthesis based on set partitions and Steiner Trees

Shan Yan, Bill Lin
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引用次数: 37

Abstract

This paper considers the problem of synthesizing application-specific network-on-chip (NoC) architectures. We propose two heuristic algorithms called CLUSTER and DECOMPOSE that can systematically examine different set partitions of communication flows, and we propose Rectilinear-Steiner-tree (RST) based algorithms for generating an efficient network topology for each group in the partition. Different evaluation functions in fitting with the implementation backend and the corresponding implementation technology can be incorporated into our solution framework to evaluate the implementation cost of the set partitions and RST topologies generated. In particular, we experimented with an implementation cost model based on the power consumption parameters of a 70 nm process technology where leakage power is a major source of energy consumption. Experimental results on a variety of NoC benchmarks showed that our synthesis results can on average achieve a 6.92 x reduction in power consumption over the best standard mesh implementation. To further gauge the effectiveness of our heuristic algorithms, we also implemented an exact algorithm that enumerates all distinct set partitions. For the benchmarks where exact results could be obtained, our CLUSTER and DECOMPOSE algorithms on average can achieve results within 1% and 2% of exact results, with execution times all under 1 second whereas the exact algorithms took as much as 4.5 hours.
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基于集合分区和斯坦纳树的特定应用的片上网络体系结构综合
本文研究了应用专用片上网络(NoC)体系结构的综合问题。我们提出了两种启发式算法,称为CLUSTER和decomposition,它们可以系统地检查通信流的不同分区集,并且我们提出了基于直线斯坦纳树(RST)的算法,用于为分区中的每个组生成有效的网络拓扑。可以将适合实现后端和相应实现技术的不同评估函数合并到我们的解决方案框架中,以评估生成的集合分区和RST拓扑的实现成本。特别是,我们实验了一个基于70纳米工艺技术功耗参数的实施成本模型,其中泄漏功率是能耗的主要来源。在各种NoC基准测试上的实验结果表明,我们的合成结果平均可以比最佳标准网格实现降低6.92倍的功耗。为了进一步衡量启发式算法的有效性,我们还实现了一个精确的算法,该算法枚举所有不同的集合分区。对于可以获得精确结果的基准测试,我们的CLUSTER和分解算法平均可以在精确结果的1%和2%内获得结果,执行时间都在1秒以下,而精确算法则需要多达4.5小时。
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