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Dynamic migratory selection strategy for adaptive routing in mesh NoCs

机译:网格NoC中自适应路由的动态迁移选择策略

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NoC architectures are the most commonly used communication framework for multicore processors. Few factors that affect the performance of an on-chip network include the efficiency of the routing algorithm and the effectiveness of the output selection strategy used. All popular selection strategies use a static technique that behaves uniformly across various traffic patterns. This paper proposes a cost effective adaptive model of Regional Congestion Awareness (RCA) selection strategy. The traffic analyser incorporated in the proposed model learns the flit-flow pattern at each router and makes RCA behaves like the local best selection strategy under local traffic. Under non-local traffic, the normal RCA selection strategy works as it is. This switching (migration) between two selection strategies is done by proper controlling of aggregation and propagation mechanisms of RCA. As only in-router information is used for this switching, the design has no additional communication overhead. This dynamic switching decreases average packet latency and effectively optimises the network resources depending on traffic pattern, thereby, reducing power consumption. Our experiments on 8°8 mesh NoC with various synthetic and real traffic patterns show promising improvements compared to the existing baseline adaptive selection strategies.
机译:NoC架构是多核处理器最常用的通信框架。影响片上网络性能的因素很少,包括路由算法的效率和所使用的输出选择策略的效率。所有流行的选择策略均使用静态技术,该技术在各种流量模式下均会表现均匀。本文提出了一种具有成本效益的区域拥塞意识(RCA)选择策略自适应模型。提议的模型中包含的流量分析器学习每个路由器上的流量流模式,并使RCA的行为类似于本地流量下的本地最佳选择策略。在非本地流量下,正常的RCA选择策略照原样工作。通过适当控制RCA的聚合和传播机制,可以在两种选择策略之间进行切换(迁移)。由于仅将路由器内信息用于此交换,因此设计没有额外的通信开销。这种动态交换减少了平均数据包延迟,并根据流量模式有效地优化了网络资源,从而降低了功耗。我们在8°8网格NoC上进行了各种合成和实际流量模式的实验,与现有的基线自适应选择策略相比,显示出可喜的改进。

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