Interactive Data Exploration for High-Performance Fluid Flow Computations through Porous Media
KAUST Grant NumberUK-c0020
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Abstract© 2014 IEEE. Huge data advent in high-performance computing (HPC) applications such as fluid flow simulations usually hinders the interactive processing and exploration of simulation results. Such an interactive data exploration not only allows scientiest to 'play' with their data but also to visualise huge (distributed) data sets in both an efficient and easy way. Therefore, we propose an HPC data exploration service based on a sliding window concept, that enables researches to access remote data (available on a supercomputer or cluster) during simulation runtime without exceeding any bandwidth limitations between the HPC back-end and the user front-end.
CitationPerovic N, Frisch J, Mundani R-P, Rank E (2014) Interactive Data Exploration for High-Performance Fluid Flow Computations through Porous Media. 2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing. Available: http://dx.doi.org/10.1109/SYNASC.2014.68.
SponsorsThis publication is partially based on work supported byAward No. UK-c0020, made by King Abdullah University ofScience and Technology (KAUST). Furthermore, the authorswould like to cordially thank for the support and usage of theBlue Gene/P at Universitatea de Vest din Timi ̧soara (UVT) inRomania.
Journal2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing