Q-StaR: A Quasi-Static Routing Scheme for NoCs

TL;DR

Q-StaR discovers two factors (topology and traffic distribution) that determine the long-term trend of load distribution, and proposes N-Rank to extract this trend and is used to guide BiDOR's route selection at runtime.

Abstract

In networks-on-chip, static routing schemes are favored for their simplicity and predictability, but they cannot effectively balance network load due to the unawareness of runtime load distribution. Q-StaR discovers two factors (topology and traffic distribution) that determine the long-term trend of load distribution, and proposes N-Rank to extract this trend. The obtained information is used to guide BiDOR's route selection at runtime, thereby improving load balancing while retaining simplicity and predictability. Simulation validates that Q-StaR significantly outperforms the typical dimension-order routing (throughput under uniform traffic improved by 42.9\%, and mean/maximum latency under realistic workloads reduced by 86.4\%/95.3\%).

Figures (9)

• Figure 1: (a) load distribution on different nodes (2DMesh + Uniform + XY routing); (b), (c), (d) load distribution in different topologies, with different traffic patterns.
• Figure 2: Heatmap of traffic from source nodes (Y-axis) to destination nodes (X-axis), in different scenarios.
• Figure 3: Workflow of Q-StaR (compared with DOR).
• Figure 4: Evolutionary Model of N-Rank.
• Figure 5: $\langle s_1,d_1 \rangle$'s minimum rectangle encircles $Chan_{u,n}$, thus in $P^{u,n}$, otherwise not ($\langle s_2,d_2 \rangle$).