On the Scalability of Real-Time Scheduling Algorithms on Multicore Platforms: A Case Study
Source: University of North Alabama
Multicore platforms are predicted to become significantly larger in the coming years. Given that real-time workloads will inevitably be deployed on such platforms, the scalability of the scheduling algorithms used to support such workloads warrants investigation. In this paper, this issue is considered and an empirical evaluation of several global and partitioned scheduling algorithms is presented. This evaluation was conducted using a Sun Niagara multicore platform with 32 logical CPUs (eight cores, four hardware threads per core). In this paper, each tested algorithm proved to be a viable choice for some subset of the workload categories considered.