Conference Paper

Application Enabling in DEISA: Petascaling of Plasma Turbulence Codes.

Conference: Parallel Computing: Architectures, Algorithms and Applications, ParCo 2007, Forschungszentrum Jülich and RWTH Aachen University, Germany, 4-7 September 2007
Source: DBLP


The ITER (International Thermonuclear Experimental Reactor) experiment must be accompanied by advanced plasma turbulence simulations. Due to the high demands for compute power and memory, simulations must be capable of using thousands or tens of thousands of processor-cores simultaneously. Highly scalable applications are mandatory. Through a joint effort of application specialists from DEISA (Distributed European Infrastructure for Supercomputing Applications) and scientists engaged in the theory support for ITER, two important European simulation codes for core turbulence, ORB5 and GENE, have been adapted for portable usage within the heterogeneous DEISA infrastructure. Moreover, the codes were thoroughly analyzed, bottlenecks were identified and removed, and, most importantly, the scalability of the codes could be significantly enhanced. Through application of the domain cloning concept, the PIC code ORB5 was enabled for high scalability. Efficient usage of ORB5 code could be demonstrated up to 8k processors, both on a Cray XT3 and on an IBM BlueGene/L system. GENE was parallelized through domain decomposition of the five-dimensional problem grid to such a high degree that close to loss-free efficiency on up to 32k processors of an IBM BlueGene/L machine was achieved. Results combined from both strong and weak scaling measurements indicate an even higher scalability potential for GENE. Extrapolations suggest an efficient usage on up to the order of 1M processor-cores of a similarly scalable future HPC architecture is possible, representing a milestone on the way towards realistic core turbulence simulations of future fusion devices.

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Available from: Hermann Lederer, Jan 07, 2014
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    • "In gyrokinetics the resolution of the gyration in time is dropped so that the development of turbulence in time can be directly observed. But even with its mature parallelization performance [2] [3], GENE is facing scalability problems due to the curse of dimensionality, since even moderate resolutions in each dimension lead to tremendous numbers of degrees of freedom in the simulations. One remedy to that could be the application of sparse grids [4], since they reduce the amount of degrees of freedom used to retrieve a solution. "
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