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[NBF12] YAO: A Generator of Parallel Code for Variational Data Assimilation Applications
Conférence Internationale avec comité de lecture : 2012 IEEE 14th Int'l Conf. on High Performance Computing and Communication (HPCC), June 2012, pp.224-232,Mots clés: data assimilation; automatic parallelization; shared memory architectures; OpenMP; dependence graph; numerical model; adjoint model
Résumé:
Variational data assimilation consists in estimating control parameters of a numerical model in order to minimize the misfit between the forecast values and the actual observations. The YAO framework is a code generator that facilitates, especially for the adjoint model, the writing and the generation of a variational data assimilation program for a given numerical application. In this paper we present how the modular graph specific to YAO enables the automatic and
efficient parallelization of the generated code with OpenMP on shared memory architectures. Thanks to this modular graph
we are also able to completely avoid the data race conditions (write/write conflicts). Performance tests with actual applications
demonstrates good speedups on a multicore CPU.
Equipe:
msdma
Collaboration:
UPMC
BibTeX
| @inproceedings { | |||
| NBF12, | |||
| title | = | "{YAO: A Generator of Parallel Code for Variational Data Assimilation Applications}", | |
| author | = | " L. Nardi and F. Badran and P. Fortin and S. Thiria ", | |
| booktitle | = | "{ 2012 IEEE 14th Int'l Conf. on High Performance Computing and Communication (HPCC)}", | |
| year | = | 2012, | |
| month | = | "June", | |
| pages | = | "224-232", | |
| } | |||
