Analyzing Fixed Task Priority Based Memory Centric Scheduler for the 3-Phase Task Model

The sharing of main memory among concurrently executing tasks on a multicore platform results in increasing the execution times of those tasks in a non-deterministic manner. The use of phased execution models that divide the execution of tasks into distinct execution and memory phase(s), e.g., the PRedictable Execution Model (PREM) and the 3-Phase task model, along with Memory Centric Scheduling (MCS) present a promising solution to reduce main memory interference among tasks.Existing works in the state-of-the-art that focus on MCS have considered (i) a TDMA-based memory scheduler, i.e., tasks’ memory requests are served under a static TDMA schedule, and (ii) Processor-Priority (PP) based memory scheduler, i.e., tasks’ memory requests are served depending on the priority of the processor/core on which the task is executing. This paper extends MCS by considering a Task-Priority (TP) based memory scheduler, i.e., tasks’ memory requests are served under a global priority order depending on the priority of the task that issues the requests. We present an analysis to bound the total memory interference that can be suffered by the tasks under the TPbased MCS. In contrast to the recent works on MCS that considers non-preemptive tasks, our analysis considers limited preemptive scheduling. Additionally, we investigate the impact of different preemption points on the memory interference of tasks. Experimental results show that our proposed TP-based MCS can significantly reduce the memory interference that can be suffered by the tasks in comparison to the PP-based MCS.