Dynamic Application-aware Power Capping

A future large-scale high-performance computing (HPC) cluster will likely be power capped since the surrounding infrastructure like power supply and cooling is constrained. For such a cluster, it may be impossible to supply thermal design power (TDP) to all components. The default power supply of current system guarantees TDP to each computing node will become unfeasible. Power capping was introduced to limit power consumption to a value below TDP, with the drawback of resulting performance limitations. We developed an alternative dynamic application-aware power scheduling (DAPS) strategy to enforce a predetermined power limit and at the same time improve the cluster-wide performance. The power scheduling decision is guided by the cap value, the hardware usage, and the application-specific performance sensitivity to power. Applying DAPS on a test platform comprising 12 computing nodes with three representative applications, we obtained a performance improvement up to 17% compared to a strategy that distributes power equally and statically across nodes.