On the Accuracy of Stochastic Delay Bound for Network on Chip
Gaoming Du, Yongliang Zhang, Zhenmin Li, Guanyu Liu, Duoli Zhang, Yiming Ouyang · 2017
Delay bound guarantee in network on chip (NoC) is important for hard real-time applications, and deterministic network calculus (DNC) is a effective tool for delay bound modeling. But for soft real-time applications, delay bound derivation using DNC is often over-pessimistic, resulting in too much chip area (e.g., router buffer) and power consumption; stochastic network calculus (SNC), on the contrary, improves the delay bound accuracy by providing stochastic service curves. Existing service models assume that contention takes place as long as there exist contention flows from different input channels requesting the same output channel. These models only consider flow paths in flows contention analyzing. We have observed that, beyond flow path contentions, the arrival rate also has deep influence on the flow contention in NoC, consequently affecting delay bound. In this paper, we further analyze the intrinsic factors affecting the flow contention, and propose a stochastic analytic model of per-flow delay bound to improve the calculation accuracy, according to both path and arrival rate. Within this model, the end-to-end delay bound is evaluated based on SNC. Experimental results show that our proposed model is both effective and accurate.