Kristensen, Mads Ruben Burgdorff4; Happe, Hans Henrik4; Vinter, Brian4
1 Department of Computer Science, Faculty of Science, Københavns Universitet2 IT, The Niels Bohr Institute, Faculty of Science, Københavns Universitet3 eScience, The Niels Bohr Institute, Faculty of Science, Københavns Universitet4 eScience, The Niels Bohr Institute, Faculty of Science, Københavns Universitet
In this work we present optimizations of a Grid-based projector-augmented wave method software, GPAW for the Blue Gene/P architecture. The improvements are achieved by exploring the advantage of shared and distributed memory programming also known as hybrid programming. The work focuses on optimizing a very time consuming operation in GPAW, the finite-different stencil operation, and different hybrid programming approaches are evaluated. The work succeeds in demonstrating a hybrid programming model which is clearly beneficial compared to the original flat programming model. In total an improvement of 1.94 compared to the original implementation is obtained. The results we demonstrate here are reasonably general and may be applied to other finite difference codes.
Proceedings of the 2009 Ieee International Symposium on Parallel & Distributed Processing, 2009, p. 1-6
The Faculty of Science; HPC; Hybrid parallel programming; Parallel framework; GPAW
Main Research Area:
International Parallel and Distributed Processing Symposium (IPDPS 2009)