Towards energy-proportional computing for enterprise-class server workloads
Proceedings of the 4th ACM/SPEC International Conference on Performance Engineering
Enabling accurate power profiling of HPC applications on exascale systems
Proceedings of the 3rd International Workshop on Runtime and Operating Systems for Supercomputers
High-Resolution power profiling of GPU functions using low-resolution measurement
Euro-Par'13 Proceedings of the 19th international conference on Parallel Processing
Leakage energy estimates for HPC applications
E2SC '13 Proceedings of the 1st International Workshop on Energy Efficient Supercomputing
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Energy and power consumption are becoming critical metrics in the design and usage of high performance systems. We have extended the Performance API (PAPI) analysis library to measure and report energy and power values. These values are reported using the existing PAPI API, allowing code previously instrumented for performance counters to also measure power and energy. Higher level tools that build on PAPI will automatically gain support for power and energy readings when used with the newest version of PAPI. We describe in detail the types of energy and power readings available through PAPI. We support external power meters, as well as values provided internally by recent CPUs and GPUs. Measurements are provided directly to the instrumented process, allowing immediate code analysis in real time. We provide examples showing results that can be obtained with our infrastructure.