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Accurate Measurement of Application-Level Energy Consumption for Energy-Aware Large-Scale Simulations
SessionSustainable Supercomputing
DescriptionSustainability in HPC is a major challenge not only for HPC centers and their users, but also for society. A lot of effort went into reducing the energy consumption of systems, but most efforts propose solutions targeting CPUs. As HPC systems shift more to GPU-centric architectures, simulation codes increasingly adopt GPU-programming models, leading to an urgent need to increase the energy-efficiency of GPU-enabled codes. However, studies for reducing the energy consumption of large-scale simulations executing on CPUs and GPUs have received insufficient attention.
In this work, we enable accurate energy measurements using an open-source toolkit across CPU+GPU architectures. We use this approach in SPH-EXA, an open-source GPU-centric astrophysical and cosmological simulation framework showing that with code instrumentation, users can accurately measure energy consumption of their application, beyond the data provided by HPC systems. The accurate energy data provide significant insights to users for conducting energy-aware computational experiments and code development.
In this work, we enable accurate energy measurements using an open-source toolkit across CPU+GPU architectures. We use this approach in SPH-EXA, an open-source GPU-centric astrophysical and cosmological simulation framework showing that with code instrumentation, users can accurately measure energy consumption of their application, beyond the data provided by HPC systems. The accurate energy data provide significant insights to users for conducting energy-aware computational experiments and code development.
Event Type
Workshop
TimeSunday, 12 November 20239:46am - 10am MST
Location603
Energy Efficiency
Green Computing
Sustainability
W