In view of the problems that the spatial distribution of traffic model in traditional Network on Chip (NoC) was not consistent with the communication locality in practical applications and the overhead of network bandwidth is large, a novel algorithm for flow generation with NoC localized characteristic based on Rent rule was proposed. By establishing the communication probability distribution model with finite Mesh structure, the communication probability matrix was used to send packets to each node uniformly and obtain synthesis flows, and the locality was realized. The experiment simulated on flow with different locality degree and different network size. The results show that the proposed algorithm has better performance in flow locality, which is more close to the actual flows compared with five algorithms including Random Uniform, Bit Complement, Reversal, Transpose and Butterfly. In addition, the overhead of network bandwidth is lower.

To facilitate the communication between remote and adjacent nodes on the large-scale Networks-on-Chip (NoC), a hierarchical Cluster-like Hierarchical Mesh (CHM) topology based on region partition was proposed. Correspondingly, to avoid performance degradation due to the bad network congestion near the intermediate nodes, an adaptive source region path selection algorithm was elaborated. According to the region characteristic in CHM, the routing decision was determined in the source region instead of source node only, and the adaptive routing node pair was distinguished among bottom and upper node pairs, which enhanced the routing selection performance for those node pairs, so as to alleviate the bad network congestion. The experimental results show that, compared with the shortest path algorithm, the proposed algorithm can increase saturation injection by at most 51% and 31% respectively under synthetic and local traffic patterns, showing an effective improvement in network throughput.