论文标题
在交通拥堵下具有偏转路线的优先级感知的NOC的绩效分析
Performance Analysis of Priority-Aware NoCs with Deflection Routing under Traffic Congestion
论文作者
论文摘要
芯片上的优先感知网络(NOC)在行业中用于在不同的工作量条件下实现可预测的延迟。这些NOC结合了挠度路由,以最大程度地减少路由器中的排队资源,并在低流量期间达到低潜伏期。但是,由于消耗NOC带宽,因此偏斜的数据包可能会加剧交通拥堵的交通拥堵。优先感知的NOC的最先进的分析模型忽略了偏转的流量,尽管在充血过程中其潜伏期很大。本文提出了一种新型的分析方法,以估计优先级感知的NOC的端到端潜伏期,并在爆发和交通繁忙的情况下进行偏转路由。实验评估表明,与周期精确模拟相比,该提出的技术的表现优于替代方法,并估计误差少于8%的真实应用的平均潜伏期。
Priority-aware networks-on-chip (NoCs) are used in industry to achieve predictable latency under different workload conditions. These NoCs incorporate deflection routing to minimize queuing resources within routers and achieve low latency during low traffic load. However, deflected packets can exacerbate congestion during high traffic load since they consume the NoC bandwidth. State-of-the-art analytical models for priority-aware NoCs ignore deflected traffic despite its significant latency impact during congestion. This paper proposes a novel analytical approach to estimate end-to-end latency of priority-aware NoCs with deflection routing under bursty and heavy traffic scenarios. Experimental evaluations show that the proposed technique outperforms alternative approaches and estimates the average latency for real applications with less than 8% error compared to cycle-accurate simulations.