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GPAW optimized for Blue Gene/P using hybrid programming

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3 Author(s)
Mads Ruben Burgdorff Kristensen ; eScience Centre, University of Copenhagen, Denmark ; Hans Henrik Happe ; Brian Vinter

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.

Published in:

Parallel & Distributed Processing, 2009. IPDPS 2009. IEEE International Symposium on

Date of Conference:

23-29 May 2009