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cs.DC2018
FFT, FMM, and Multigrid on the Road to Exascale: performance challenges and opportunities
Huda Ibeid, Luke Olson, William Gropp
FFT, FMM, and multigrid methods are widely used fast and highly scalable solvers for elliptic PDEs. However, emerging large-scale computing systems are introducing challenges in co…
cs.PF2018
Learning with Analytical Models
Huda Ibeid, Siping Meng, Oliver Dobon +2
To understand and predict the performance of scientific applications, several analytical and machine learning approaches have been proposed, each having its advantages and disadvan…
cs.DC2018
Improving Performance Models for Irregular Point-to-Point Communication
Amanda Bienz, William D. Gropp, Luke N. Olson
Parallel applications are often unable to take full advantage of emerging parallel architectures due to scaling limitations, which arise due to inter-process communication. Perform…