A divide and conquer strategy for scaling weather simulations with multiple regions of interest


Autoria(s): Malakar, Peeti; George, Thomas; Kumar, Sameer; Mittal, Rashmi; Natarajan, Vijay; Sabharwal, Yogish; Saxena, Vaibhav; Vadhiyar, Sathish S
Data(s)

2012

Resumo

Accurate and timely prediction of weather phenomena, such as hurricanes and flash floods, require high-fidelity compute intensive simulations of multiple finer regions of interest within a coarse simulation domain. Current weather applications execute these nested simulations sequentially using all the available processors, which is sub-optimal due to their sub-linear scalability. In this work, we present a strategy for parallel execution of multiple nested domain simulations based on partitioning the 2-D processor grid into disjoint rectangular regions associated with each domain. We propose a novel combination of performance prediction, processor allocation methods and topology-aware mapping of the regions on torus interconnects. Experiments on IBM Blue Gene systems using WRF show that the proposed strategies result in performance improvement of up to 33% with topology-oblivious mapping and up to additional 7% with topology-aware mapping over the default sequential strategy.

Formato

application/pdf

Identificador

http://eprints.iisc.ernet.in/47718/1/Hig_Per_Comp_Netw_Stora_Ana_1_2012.pdf

Malakar, Peeti and George, Thomas and Kumar, Sameer and Mittal, Rashmi and Natarajan, Vijay and Sabharwal, Yogish and Saxena, Vaibhav and Vadhiyar, Sathish S (2012) A divide and conquer strategy for scaling weather simulations with multiple regions of interest. In: SC '12 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, Monday, October 14, 2013, Los Alamitos, CA, USA.

Publicador

IOS Press

Relação

http://dx.doi.org/10.3233/SPR-130367

http://eprints.iisc.ernet.in/47718/

Palavras-Chave #Computer Science & Automation (Formerly, School of Automation)
Tipo

Conference Paper

PeerReviewed