RLP: Power Management Based on a Latency-Aware Roofline Model

The ever-growing power draw in high-performance computing (HPC) clusters and the rising energy costs enforce a pressing urge for energy-efficient computing. Consequently, advanced infrastructure orchestration is required to regulate power dissipation efficiently. In this work, we propose a novel approach for managing power consumption at runtime based on the well-known roofline model and call it Roofline Power (RLP) management. The RLP employs rigorously selected but generally available hardware performance events to construct rooflines, with minimal overheads. In particular, RLP extends the original roofline model to include the memory access latency metric for the first time. The extension identifies whether execution is bandwidth, latency, or compute-bound, and improves the modeling accuracy. We evaluated the RLP model on server-grade CPUs and a GPU with real-world HPC workloads in two scenarios: optimization with and without power capping. Compared to system default settings, RLP reduces the energy-to-solution up to 22% with negligible performance degradation. The other scenario accelerates the execution up to 14.7% under power capping. In addition, RLP outperforms other state-of-the-art techniques in generality and effectiveness.