HARE: History-Aware Adaptive Routing Algorithm for Endpoint Congestion in Networks-on-Chip

Abstract

Endpoint congestion is one of the most challenging issues when designing low latency and high bandwidth on-chip interconnection networks. Tree saturation and head-of-line blocking caused by the endpoint congestion seriously decrease system throughput and increases network latency, leading to overall performance degradation. Adaptive routing algorithms utilize dynamic network states to route packets around congestion areas and potentially mitigate network congestions, but still cannot deal with endpoint congestions. Existing adaptive routing algorithms mainly take the current route information into account, and rarely use the route information of past packets. In this paper, we explore the route information of past packets, and led to the following novel observations that the virtual channel (VC) allocations of prior packets can be collected as useful information, and the tree saturation can be isolated through better VC selection strategy based on the past route information. Based on this observation, a novel history-aware adaptive routing algorithm for endpoint congestion, HARE, is proposed to improve network performance. We implement HARE based on the state-of-the-art routing algorithm, Footprint, and conduct extensive simulation experiments to compare it with our algorithm. The evaluation results show that our design alleviate the impact of tree saturation consistently and achieve high throughput on both synthetic and trace-driven workloads.