Article in Edited Volumes
A Geometric Multigrid Solver on Tsubame 2.0
Author(s): Köstler H, Feichtinger C, Rüde U, Aoki T
Editor(s): Bruhn A, Pock Th, Tai X-C
Title edited volumes: Efficient Algorithms for Global Optimisation Methods in Computer Vision
Publishing place: Berlin, Heidelberg, New York
Publication year: 2014
Title of series: Lecture Notes in Computer Science
Pages range: 155-173
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. © 2014 Springer-Verlag Berlin Heidelberg.
FAU Authors / FAU Editors How to cite
APA: Köstler, H., Feichtinger, C., Rüde, U., & Aoki, T. (2014). A Geometric Multigrid Solver on Tsubame 2.0. In Bruhn A, Pock Th, Tai X-C (Eds.), Efficient Algorithms for Global Optimisation Methods in Computer Vision (pp. 155-173). Berlin, Heidelberg, New York: Springer.
MLA: Köstler, Harald, et al. "A Geometric Multigrid Solver on Tsubame 2.0." Efficient Algorithms for Global Optimisation Methods in Computer Vision Ed. Bruhn A, Pock Th, Tai X-C, Berlin, Heidelberg, New York: Springer, 2014. 155-173.