Interference-aware program scheduling for multicore processors

Running multiple application programs on a multicore processor can maximize processor resources utilization. However, contention to the shared resources may result in interference among co-running programs, and make the program performance unstable and unpredictable. In order to optimize the performance of co-running programs and ensure the QoS of latency-sensitive applications, we propose an interference-aware scheduling strategy IA for systems based on multicore processors. Our work begins with analysis of the behavior of a set of benchmark programs, after that we train a simple program classifier. We use this classifier to classify the benchmark programs into three categories according to their interference with each other. The interferenceaware scheduler tries to schedule the programs with less interference to the same multicore processor. Experiments results show that our method improves system performance while maintaining reasonable resource utilization. It outperforms the previously published scheduling strategy in guaranteeing the QoS of latency-sensitive applications.