dc.contributor
Barcelona Supercomputing Center
dc.contributor.author
Arcucci, Rossella
dc.contributor.author
Basciano, Davide
dc.contributor.author
Cilardo, Alessandro
dc.contributor.author
D'Amore, Luisa
dc.contributor.author
Mantovani, Filippo
dc.date.issued
2018-03-23
dc.identifier
Arcucci, 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.
dc.identifier
978-3-319-78053-5
dc.identifier
https://hdl.handle.net/2117/116207
dc.identifier
10.1007/978-3-319-78054-2_4
dc.description.abstract
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.
dc.description.abstract
The research has received funding from European Commission under H2020-MSCA-RISE NASDAC project (grant agreement no. 691184) FP7 Mont-Blanc and Mont-Blanc 2 (grant agreements no. 288777 and 610402), H2020-FET Mont-Blanc 3 (grant agreement 671697).
dc.description.abstract
Peer Reviewed
dc.description.abstract
Postprint (author's final draft)
dc.format
application/pdf
dc.relation
https://link.springer.com/chapter/10.1007/978-3-319-78054-2_4
dc.relation
info:eu-repo/grantAgreement/EC/H2020/691184/EU/iNnovative Approaches for Scalable Data Assimilation in oCeanography/NASDAC
dc.relation
info:eu-repo/grantAgreement/EC/FP7/288777/EU/Mont-Blanc, European scalable and power efficient HPC platform based on low-power embedded technology/MONT-BLANC
dc.relation
info:eu-repo/grantAgreement/EC/FP7/610402/EU/Mont-Blanc 2, European scalable and power efficient HPC platform based on low-power embedded technology/MONT-BLANC 2
dc.relation
info:eu-repo/grantAgreement/EC/H2020/671697/EU/Mont-Blanc 3, European scalable and power efficient HPC platform based on low-power embedded technology/Mont-Blanc 3
dc.subject
Àrees temàtiques de la UPC::Informàtica
dc.subject
High performance computing
dc.subject
Data assimilation
dc.subject
Embedded processor architectures
dc.subject
Energy consumption
dc.subject
Supercomputadors
dc.title
Energy Analysis of a 4D Variational Data Assimilation Algorithm and Evaluation on ARM-Based HPC Systems
dc.type
Conference lecture
