Destination-based adaptive routing on 2D mesh networks

The choice of routing algorithm plays a vital role in the performance of on-chip interconnection networks. Adaptive routing is appealing because it offers better latency and throughput than oblivious routing, especially under non-uniform and bursty traffic. The performance of an adaptive routing algorithm is determined by its ability to accurately estimate congestion in the network. In this regard, maintaining global congestion information using a separate monitoring network offers better congestion visibility into distant parts of the network than solutions relying only on local congestion state. However, the main challenge in designing such routing schemes is to keep the logic and bandwidth overhead as low as possible to fit into the tight power, area and delay budgets of on-chip routers. In this paper, we propose a minimal destination-based adaptive routing strategy (DAR) where every node estimates the delay to every other node in the network, and routing decisions are based on these per-destination delay estimates. DAR outperforms Regional Congestion Awareness (RCA) [7], the best previously known adaptive routing algorithm that uses non-local congestion knowledge. This is because the per-destination delay estimates in DAR are more accurate and not corrupted by congestion on links outside the admissible routing paths to the destination. We show that DAR outperforms minimal adaptive routing by up to 65% and RCA by up to 41% in terms of latency on SPLASH-2 benchmarks. It also outperforms these algorithms in latency and throughput under synthetic traffic patterns on both 8x8 and 16x16 mesh topologies.