Real-time gang schedulings with workload models for parallel computers

Gang scheduling has recently been shown to be an effective task scheduling policy for parallel computers because it combines elements of space sharing and time sharing [10, 20]. In this paper, we propose new policies to enable gang scheduling to adapt to environments with real-time constraints. Our work, to our best knowledge, is the first attempt to address these real-time aspects with gang scheduling. Our system, guided by a metric called the "task utilization workload." can schedule both real-time and non-real-time tasks at the same time. In this paper, we report simulation results obtained using a family of scheduling algorithms based on our proposed metric. Our scheme is designed for practical use with large scale industrial and commercial parallel systems. Preliminary simulation results also show that our proposed policy is effective for real-time scheduling and can schedule non-real-time tasks with fairness and good throughput.