Imperial College London
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DrRossellaArcucci

Faculty of Engineering, Department of Earth Science & Engineering

Senior Lecturer in Data Science and Machine Learning
 
 
 
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Contact

 

r.arcucci Website

 
 
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Location

 

Royal School of MinesSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{D'Amore:2013,
author = {D'Amore, L and Arcucci, R and Marcellino, L and Murli, A},
journal = {Journal of Numerical Analysis, Industrial and Applied Mathematics},
pages = {91--105},
title = {HPC computation issues of the incremental 3D variational data assimilation scheme in OceanVar software},
volume = {7},
year = {2013}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - The most significant features of Data Assimilation (DA) are that both the models and the observations are very large and non-linear (of order at least O(108)). Further, DA is an ill-posed inverse problem. Such properties make the numerical solution of DA very difficult so that, as stated in [19], "solving this problem in "real-time" it is not always pos- sible and many different approximations to the basic assimilation schemes are employed". Thus, the exploitation of advanced computing environments is mandatory, reducing the computational cost to a suitable turnaround time. This activity should be done according to a co-design methodology where software requirements drive hardware design decisions and hardware design constraints motivate changes in the software design to better fit within those constraints. In this paper, we address high performance computation issues of the three dimensional DA scheme underlying the oceanographic 3D-VAR assimilation scheme, named Ocean- VAR, developed at CMCC (Centro Euro Mediterraneo per i Cambiamenti Climatici), in Italy. The aim is to develop a parallel software architecture which is able to effectively take advantage of the available high performance computing resources. © 2012 European Society of Computational Methods in Sciences, Engineering and Technology.
AU  - D'Amore,L
AU  - Arcucci,R
AU  - Marcellino,L
AU  - Murli,A
EP  - 105
PY  - 2013///
SN  - 1790-8140
SP  - 91
TI  - HPC computation issues of the incremental 3D variational data assimilation scheme in OceanVar software
T2  - Journal of Numerical Analysis, Industrial and Applied Mathematics
VL  - 7
ER  -
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