Abstract
We consider the Incremental Strong constraint 4D VARiational (IS4DVAR) algorithm for data assimilation implemented in ROMS with the aim to study its performance in terms of strong scaling scalability on computing architectures such as a cluster of CPUs. We consider realistic test cases with data collected in enclosed and semi enclosed seas, namely, Caspian sea, West Africa/Angola, as well as data collected into the California bay. The computing architecture we use is currently available at Imperial College London. The analysis allows us to highlight that the ROMS-IS4DVAR performance on emerging architectures depends on a deep relation among the problems size, the domain decomposition approach and the computing architecture characteristics.
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Notes
- 1.
Relation between \(t_{com}\) and \(t_{calc}\) (namely, the value of the parameter q) heavily depends on how the software under consideration is able to efficiently exploit the parallelism of such advanced architectures (the so called sustained performance).
- 2.
Helen is an SGI ICE 8200EX system. The first part of the system is comprised of 122 nodes. Each node has two 4-core 2.93 GHz Intel X5570 (Nehalem) processors and 24 GB of RAM. The processors are hyperthreaded - each physical core appears as two logical processors. The second part of the system consists of two extra ICE 8400EX racks with 179 extra nodes. These nodes have two 6-core 2.93 GHz X5670 (Westmere) processors and 24 GB of RAM. Like the Nehalem processors these are hyperthreaded. Then, the system has a total of 602 processors.
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Acknowledgment
The research has received funding from European Commission under H2020-MSCA-RISE NASDAC project (grant agreement n. 691184).
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D’Amore, L. et al. (2018). Performance Assessment of the Incremental Strong Constraints 4DVAR Algorithm in ROMS. In: Wyrzykowski, R., Dongarra, J., Deelman, E., Karczewski, K. (eds) Parallel Processing and Applied Mathematics. PPAM 2017. Lecture Notes in Computer Science(), vol 10778. Springer, Cham. https://doi.org/10.1007/978-3-319-78054-2_5
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