TY  - GEN
AU  - Paniego,Juan Manuel
AU  - Gallo,Silvana Lis
AU  - Pi Puig,Martín
AU  - Chichizola,Franco
AU  - De Giusti,Laura Cristina
AU  - Balladini,Javier Aldo
TI  - Analysis of RAPL energy prediction accuracy in a matrix multiplication application on shared memory
KW  - HARDWARE
KW  - consumo de energía
N1  - Formato de archivo PDF. -- Este documento es producción intelectual de la Facultad de Informática - UNLP (Colección BIPA/Biblioteca); Argentine Congress of Computer Science. CACIC 2017 (23ro : 2017 : La Plata, Argentina)
N2  - 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
ER  -