2012/03/01 by Niels Drost, Drost, Niels, Jason Maassen +18
Computer Science · Physics and Astronomy · #Advanced Data Storage Technologies #Cloud Computing and Resource Management #Distributed #Distributed and Parallel Computing Systems #FOS: Computer and information sciences #FOS: Physical sciences #Opportunistic and Delay-Tolerant Networks #Parallel #Solar and Stellar Astrophysics (astro-ph.SR) #and Cluster Computing (cs.DC) #astro-ph.SR #cs.DC
paper · pdf · doi:10.48550/arxiv.1203.0321
arxiv created 2012/03/01 · openalex publication_date 2012/03/01 · arxiv updated 2012/03/05 · openalex created_date 2025/10/24 · openalex updated_date 2026/07/28
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.