Analysis of RAPL Energy Prediction Accuracy in a Matrix Multiplication Application on Shared Memory

JUAN MANUEL PANIEGO; FRANCO CHICHIZOLA; MARTIN PI PUIG; JAVIER BALLADINI; SILVANA GALLO; LAURA DE GIUSTI

Communications in Computer and Information Science

Springer International Publishing

Año: 2018; p. 37 - 46

In recent years, energy consumption has emerged as one of the biggest issues in the development of HPC applications. The traditional approach of parallel and distributed computing has changed its perspective from looking for greater computational efficiency to an approach that balances performance with energy consumption. As a consequence, different metrics and measurement mechanisms have been implemented to achieve this balance. The objective of this article focuses on monitoring and analyzing energy consumption for a given application through physical measurements and a software interface based on hardware counters. A comparison of the energy values gathered by Intel RAPL versus physical measurements obtained through the processor power source is presented. These measurements are applied during the execution of a classic matrix multiplication application. Our results show that, for the application being considered, the average power required by the processor has an error of up to 22% versus the values predicted by RAPL.