Memory efficient global scheduling of real-time tasks

Current computing architectures are commonly built with multiple cores and a single shared main memory. Even though this architecture increases the overall computation power, main memory can easily become a bottleneck. Simultaneous access to main memory from multiple cores can cause both (1) severe degradation in performance and (2) unpredictable execution time for real-time applications. We propose in this paper to mitigate these two problems by co-scheduling cores as well as the main memory for predictable execution. In particular, we use a DMA component to overlap memory with computation for hiding the memory latency and therefore increasing the system performance. The main contribution of this paper is a novel global co-scheduling algorithm along with its associated schedulability analysis for sporadic hard real-time tasks. We evaluated our system by generating synthetic tasksets based on real benchmark parameters. The results show a significant improvement in system utilization while retaining a predictable system behavior.