@inproceedings{7341217d09854c6bbd135ba35cb316ed,
title = "A geometric multigrid solver on tsubame 2.0",
abstract = "Tsubame 2.0 is currently one of the largest installed GPU clusters and number 5 in the Top 500 list ranking the fastest supercomputers in the world. In order to make use of Tsubame, there is a need to adapt existing software design concepts to multi-GPU environments. We have developed a modular and easily extensible software framework called waLBerla that covers a wide range of applications ranging from particulate flows over free surface flows to nano fluids coupled with temperature simulations and medical imaging. In this article we report on our experiences to extend waLBerla in order to support geometric multigrid algorithms for the numerical solution of partial differential equations (PDEs) on multi-GPU clusters. We discuss the software and performance engineering concepts necessary to integrate efficient compute kernels into our waLBerla framework and show first weak and strong scaling results on Tsubame for up to 1029 GPUs for our multigrid solver.",
keywords = "CUDA, GPGPU, Parallel multigrid solver, Tsubame 2.0, waLBerla",
author = "Harald K{\"o}stler and Christian Feichtinger and Ulrich R{\"u}de and Takayuki Aoki",
year = "2014",
doi = "10.1007/978-3-642-54774-4_8",
language = "English",
isbn = "9783642547737",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "155--173",
booktitle = "Efficient Algorithms for Global Optimization Methods in Computer Vision - International Dagstuhl Seminar, Revised Selected Papers",
note = "2011 International Dagstuhl Seminar 11471 on Efficient Algorithms for Global Optimization Methods in Computer Vision ; Conference date: 20-11-2011 Through 25-11-2011",
}