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Register a new userPerformance Analysis of Priority-Aware NoCs with Deflection Routing under Traffic Congestion
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Added by
Sumit Mandal
Publication date
2020
fields
Informatics Engineering
and research's language is
English
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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.
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Networks-on-Chip (NoCs) used in commercial many-core processors typically incorporate priority arbitration. Moreover, they experience bursty traffic due to application workloads. However, most state-of-the-art NoC analytical performance analysis techniques assume fair arbitration and simple traffic models. To address these limitations, we propose an analytical modeling technique for priority-aware NoCs under bursty traffic. Experimental evaluations with synthetic and bursty traffic show that the proposed approach has less than 10% modeling error with respect to cycle-accurate NoC simulator.
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We present a congestion-aware routing solution for indoor evacuation, which produces real-time individual-customized evacuation routes among multiple destinations while keeping tracks of all evacuees locations. A population density map, obtained on-the-fly by aggregating locations of evacuees from user-end Augmented Reality (AR) devices, is used to model the congestion distribution inside a building. To efficiently search the evacuation route among all destinations, a variant of A* algorithm is devised to obtain the optimal solution in a single pass. In a series of simulated studies, we show that the proposed algorithm is more computationally optimized compared to classic path planning algorithms; it generates a more time-efficient evacuation route for each individual that minimizes the overall congestion. A complete system using AR devices is implemented for a pilot study in real-world environments, demonstrating the efficacy of the proposed approach.
Simulations and runtime measurements are some of the methods which can be used to evaluate whether a given NoC-based platform can accommodate application workload and fulfil its timing requirements. Yet, these techniques are often time-consuming, and hence can evaluate only a limited set of scenarios. Therefore, these approaches are not suitable for safety-critical and hard real-time systems, where one of the fundamental requirements is to provide strong guarantees that all timing requirements will always be met, even in the worst-case conditions. For such systems the analytic-based real-time analysis is the only viable approach. In this paper the focus is on the real-time communication analysis for wormhole-switched priority-preemptive NoCs. First, we elaborate on the existing analysis and identify one source of pessimism. Then, we propose an extension to the analysis, which efficiently overcomes this limitation, and allows for a less pessimistic analysis. Finally, through a comprehensive experimental evaluation, we compare the newly proposed approach against the existing one, and also observe how the trends change with different traffic parameters.
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