Statistics – Computation
Scientific paper
Oct 2011
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011aspc..444..281k&link_type=abstract
5th international conference of numerical modeling of space plasma flows (astronum 2010). Proceedings of a 5th international con
Statistics
Computation
Scientific paper
3D global electromagnetic hybrid (fluid electrons, kinetic ions) simulations have long been considered the holy grail in kinetic modeling of the magnetosphere but high computational requirements have kept them out of reach. Petascale computers provide the computational power to make such simulations possible but peta computing poses two technical challenges. One is related to the development of efficient and scalable algorithms that can take advantage of the large number of cores. The second is related to knowledge extraction from the resulting simulation output. The challenge of science discovery from the extremely large data sets (˜ 200 TB from a single run) generated from global kinetic simulations is compounded by the multi-variate and "noisy" nature of the data. Here, we review our innovations to overcome both challenges. We have developed a highly scalable hybrid simulation code (H3D) that we used to perform the first petascale global kinetic simulation of the magnetosphere using 98,304 cores on the NSF Kraken supercomputer. To facilitate analysis of data from such runs, we have developed complex visualization pipeline including physics based algorithms to detect and track events of interest in the data. The effectiveness of this approach is illustrated through examples.
Ayachit U.
Geveci B.
Karimabadi Homa
Loring B.
Majumdar Arka
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