Dynamic Co-scheduling Driven by Main Memory Bandwidth Utilization

Most applications running on supercomputers achieve only a fraction of a system's peak performance. It has been demonstrated that the co-scheduling of applications can improve the overall system utilization. However, following this approach, applications need to fulfill certain criteria such that the mutual slowdown is kept at a minimum. In this paper, we present an HPC scheduler that applies co-scheduling and utilizes virtual machine migration for a re-orchestration of applications at runtime based on their main memory bandwidth requirements. Given a job queue consisting of main memory-bound applications and compute-bound applications, we can see a throughput increase of up to 35% while at the same time reducing energy consumption by around 30%.