Presentation
Exploring the Frontiers of Energy Efficiency using Power Management at System Scale
SessionSustainable Supercomputing
DescriptionIn the face of surging power demands for exascale HPC systems, this work tackles the critical challenge of understanding the impact of software-driven power management
techniques like Dynamic Voltage and Frequency Scaling (DVFS) and Power Capping. These techniques have been actively developed over the past few decades. By combining insights from
GPU benchmarking to understand application power profiles, we present a telemetry data-driven approach for deriving energy savings projections. This approach has been demonstrably applied
to the Frontier supercomputer at scale. Our findings based on three months of telemetry data indicate that, for certain resource constrained jobs, significant energy savings (up to 8.5%) can be
achieved without compromising performance. This translates to a substantial cost reduction, equivalent to 1438 MWh of energy saved. The key contribution of this work lies in the methodology for establishing an upper limit for these best-case scenarios and its successful application.
techniques like Dynamic Voltage and Frequency Scaling (DVFS) and Power Capping. These techniques have been actively developed over the past few decades. By combining insights from
GPU benchmarking to understand application power profiles, we present a telemetry data-driven approach for deriving energy savings projections. This approach has been demonstrably applied
to the Frontier supercomputer at scale. Our findings based on three months of telemetry data indicate that, for certain resource constrained jobs, significant energy savings (up to 8.5%) can be
achieved without compromising performance. This translates to a substantial cost reduction, equivalent to 1438 MWh of energy saved. The key contribution of this work lies in the methodology for establishing an upper limit for these best-case scenarios and its successful application.