Cache allocation for fixed-priority real-time scheduling on multi-core platforms

Abstract

The increased resource sharing on multi-core platforms has posed significant challenges on the predictability of real-time systems. Cache memory partitioning has proven to be one of the most effective methods to improve the predictability and also the schedulability of real-time systems. In this paper, we study how to allocate cache memory of a multi-core platform when scheduling fixed-priority hard real-time tasks. As the bounded worst-case execution time (WCET) of a real-time task varies with its cache allocation, the challenges of this problem are twofold: how to judiciously allocate the cache memory among all real-time tasks and how to map real-time tasks to each core to improve the schedulability. To address these challenges, we develop an approach that takes into consideration not only the WCET variations with cache allocations but also the task period relationship and thus can significantly improve the schedulability of real-time tasks. Our simulation results, based on the SPEC CPU2000 benchmarks suite, show that our approach can increase the schedulability of real-time tasks up to four times when compared to other similar scheduling mechanisms.