Parallel job scheduling for power constrained HPC systems

Power has become the primary constraint in high performance computing. Traditionally, parallel job scheduling policies have been designed to improve certain job performance metrics when scheduling parallel workloads on a system with a given number of processors. The available number of processors is not anymore the only limitation in parallel job scheduling. The recent increase in processor power consumption has resulted in a new limitation: the available power. Given constraints naturally lead to an optimization problem. We proposed MaxJobPerf, a new parallel job scheduling policy based on integer linear programming. Dynamic Voltage Frequency Scaling (DVFS) is a widely used technique that running applications at reduced CPU frequency/voltage trades increased execution time for power reduction. The optimization problem determines which jobs should run and at which frequency. In this paper, we compare the MaxJobPerf policy against other power budgeting policies for different power budgets. It clearly outperforms the other power-budgeting approaches at the parallel job scheduling level. Furthermore, we give a detailed analysis of the policy parameters including a discussion on how to manage job reservations to avoid job starvation.

► Parallel job scheduling policy for power constrained HPC centers.
► Policy that manages both power and processors simultaneously.
► Applying Dynamic Voltage Frequency Scaling (DVFS) to decrease job wait time.
► Job-level DVFS impact models.
► Comparison of existing power-budgeting approaches.