Scalability analysis of release and sequential consistency models in NoC based multicore systems

Abstract

We analyze the scalability of the Release Consistency (RC) and Sequential Consistency (SC) models which are realized in the Network-on-Chip (NoC) based distributed shared memory multicore systems. The analysis is performed on the basis of workloads mapped on the different sizes of networks with different data sets. The experiments use a configurable platform based on a 2D mesh NoC using deflection routing algorithm. The results show that under the synthetic workloads using different distributed locks, the performance of the RC model is increased by 17.6% to 54.6% over the SC model in the 64-cores system. For the application workloads, as the network size grows from 1 to 64 cores, the execution time under the RC model decreases relative to the SC model which depends on the application and its match to the architecture. The performance improvement of the RC model over the SC model tends to be higher than 50% observed in the experiments, when the system is further scaled up.