Distributed and cloud-based multi-model analytics experiments on large volumes of climate change data in the Earth System Grid Federation eco-system

被引:5
|
作者
Fiore, S. [1 ]
Plociennik, M. [2 ]
Doutriaux, C. [3 ]
Palazzo, C. [1 ]
Boutte, J. [3 ]
Zok, T. [2 ]
Elia, D. [1 ]
Owsiak, M. [2 ]
D'Anca, A. [1 ]
Shaheen, Z. [3 ]
Bruno, R. [4 ]
Fargetta, M. [4 ]
Caballer, M. [5 ]
Molto, G. [5 ]
Blanquer, I. [5 ]
Barbera, R. [4 ,6 ]
David, M. [7 ]
Donvito, G. [4 ]
Williams, D. N. [3 ]
Anantharaj, V. [8 ]
Salomoni, D. [4 ]
Aloisio, G. [1 ,9 ]
机构
[1] EuroMediterranean Ctr Climate Change Fdn CMCC, Bologna, Italy
[2] Poznan Supercomp & Networking Ctr PSNC, Poznan, Poland
[3] Lawrence Livermore Natl Lab LLNL, San Francisco, CA USA
[4] Italian Natl Inst Nucl Phys INFN, Bologna, Italy
[5] Univ Politecn Valencia UPV, Valencia, Spain
[6] Univ Catania, Catania, Italy
[7] Lab Instrumentacao & Fis Expt Particulas LIP, Lisbon, Portugal
[8] Oak Ridge Natl Lab ORNL, Oak Ridge, TN USA
[9] Univ Salento, Lecce, Italy
来源
2016 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA) | 2016年
关键词
big analytics; workflow management; cloud computing; ESGF; INDIGO-DataCloud;
D O I
10.1109/BigData.2016.7840941
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A case study on climate models intercomparison data analysis addressing several classes of multi-model experiments is being implemented in the context of the EU H2020 INDIGO-DataCloud project. Such experiments require the availability of large amount of data (multi-terabyte order) related to the output of several climate models simulations as well as the exploitation of scientific data management tools for large-scale data analytics. More specifically, the paper discusses in detail a use case on precipitation trend analysis in terms of requirements, architectural design solution, and infrastructural implementation. The experiment has been tested and validated on CMIP5 datasets, in the context of a large scale distributed testbed across EU and US involving three ESGF sites (LLNL, ORNL, and CMCC) and one central orchestrator site (PSNC).
引用
收藏
页码:2911 / 2918
页数:8
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