A Hybrid Real-Time Scheduling Approach for Large-Scale Multicore Platforms

We propose a hybrid approach for scheduling real-time tasks on large-scale multicore platforms with hierarchical shared caches. In this approach, a multicore platform is partitioned into clusters. Tasks are statically assigned to these clusters, and scheduled within each cluster using the preemptive global EDF scheduling algorithm. We show that this hybrid of partitioning and global scheduling performs better on large-scale platforms than either approach alone. We also determine the appropriate cluster size to achieve the best performance possible, given the characteristics of the task set to be supported.