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Thursday, March 3 • 11:30am - 11:50am
Algorithms & Accelerators II: Hybrid Parallel Implementation of the DG Method

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The majority of supercomputers today are built using the so-called hybrid architecture where the central processing units are complemented by one or more accelerated units. In order to achieve optimal performance on these hybrid architectures many parallel applications must be modified to support more than one level of parallelism. This requirement can be realized by combining multiple parallel programming models and their implementations which are designed to perform best on their targeted architectures. In this work, we evaluate the parallel scalability of the Discontinuous Galerkin (DG) method using a hybrid parallel programming model. We combine three levels of parallelism to achieve the best performance on a GPU-enabled supercomputer. We also compare the performances of a purely distributed implementation with our hybrid implementation.


Nabil Chaabane

Postdoc fellow, Rice University
Numerical methods for PDEs, High performance computing, MPI, openMP, GPU
avatar for Beatrice Riviere

Beatrice Riviere

Noah Harding Chair and Professor, Rice University

Thursday March 3, 2016 11:30am - 11:50am
BioScience Research Collaborative Building (BRC), Room 280 & 282

Attendees (3)