Energy Analysis of a 4D Variational Data Assimilation Algorithm and Evaluation on ARM-Based HPC Systems
Document typeConference lecture
Rights accessOpen Access
European Commisision's projectEC-H2020-691184
MONT-BLANC - Mont-Blanc, European scalable and power efficient HPC platform based on low-power embedded technology (EC-FP7-288777)
MONT-BLANC 2 - Mont-Blanc 2, European scalable and power efficient HPC platform based on low-power embedded technology (EC-FP7-610402)
Driven by the emerging requirements of High Performance Computing (HPC) architectures, the main focus of this work is the interplay of computational and energetic aspects of a Four Dimensional Variational (4DVAR) Data Assimilation algorithm, based on Domain Decomposition (named DD-4DVAR). We report first results on the energy consumption of the DD-4DVAR algorithm on embedded processor and a mathematical analysis of the energy behavior of the algorithm by assuming the architectures characteristics as variable of the model. The main objective is to capture the essential operations of the algorithm exhibiting a direct relationship with the measured energy. The experimental evaluation is carried out on a set of mini-clusters made available by the Barcelona Supercomputing Center.
CitationArcucci, R. [et al.]. Energy Analysis of a 4D Variational Data Assimilation Algorithm and Evaluation on ARM-Based HPC Systems. A: International Conference on Parallel Processing and Applied Mathematics. "PPAM 2017: Parallel Processing and Applied Mathematics". Springer, 2018, p. 37-47.