High-Performance Distributed Multi-Model / Multi-Kernel Simulations: A Case-Study in Jungle Computing

Niels Drost, Jason Maassen, Maarten A.J. van Meersbergen, Henri E. Bal, F. Inti Pelupessy, Simon Portegies Zwart, Michael Kliphuis, Henk A. Dijkstra, Frank J. Seinstra
Dept. of Computer Science, VU University, Amsterdam, The Netherlands
arXiv:1203.0321v1 [cs.DC] (1 Mar 2012)


   author={Drost, Niels and Maassen, Jason and van Meersbergen, Maarten A.J. and Bal, Henri E. and Pelupessy, F. Inti and Zwart, Simon Portegies and Kliphuis, Michael and Dijkstra, Henk A. and Seinstra, Frank J.},

   title={"{High-Performance Distributed Multi-Model / Multi-Kernel Simulations: A Case-Study in Jungle Computing}"},

   journal={ArXiv e-prints},




   keywords={Distributed, Parallel, and Cluster Computing, Solar and Stellar Astrophysics},




   adsnote={Provided by the SAO/NASA Astrophysics Data System}


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High-performance scientific applications require more and more compute power. The concurrent use of multiple distributed compute resources is vital for making scientific progress. The resulting distributed system, a so-called Jungle Computing System, is both highly heterogeneous and hierarchical, potentially consisting of grids, clouds, stand-alone machines, clusters, desktop grids, mobile devices, and supercomputers, possibly with accelerators such as GPUs. One striking example of applications that can benefit greatly of Jungle Computing Systems are Multi-Model / Multi-Kernel simulations. In these simulations, multiple models, possibly implemented using different techniques and programming models, are coupled into a single simulation of a physical system. Examples include the domain of computational astrophysics and climate modeling. In this paper we investigate the use of Jungle Computing Systems for such Multi-Model / Multi-Kernel simulations. We make use of the software developed in the Ibis project, which addresses many of the problems faced when running applications on Jungle Computing Systems. We create a prototype Jungle-aware version of AMUSE, an astrophysical simulation framework. We show preliminary experiments with the resulting system, using clusters, grids, stand-alone machines, and GPUs.
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