JUQUEEN: IBM Blue Gene/Q&lt;sup&gt;&amp;reg;&lt;/sup&gt; Supercomputer System at the Jülich Supercomputing Centre

Stephan, Michael; Docter, Jutta

doi:10.17815/jlsrf-1-18

Cited by 177 publications

(94 citation statements)

References 1 publication

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“…Additionally, we gratefully acknowledge the computing time, granted by the "JARA-HPC Vergabegremium" and provided on the "JARA-HPC Partition" part of the supercomputer "JUQUEEN" [91] at Forschungszentrum Jülich.…”

Section: Acknowledgmentsmentioning

confidence: 99%

Real-time dynamics of typical and untypical states in nonintegrable systems

Richter¹,

Jin²,

Raedt³

et al. 2018

Phys. Rev. B

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Understanding (i) the emergence of diffusion from truly microscopic principles continues to be a major challenge in experimental and theoretical physics. At the same time, isolated quantum many-body systems have experienced an upsurge of interest in recent years. Since in such systems the realization of a proper initial state is the only possibility to induce a nonequilibrium process, understanding (ii) the largely unexplored role of the specific realization is vitally important. Our work reports a substantial step forward and tackles the two issues (i) and (ii) in the context of typicality, entanglement as well as integrability and nonintegrability. Specifically, we consider the spin-1/2 XXZ chain, where integrability can be broken due to an additional next-nearest neighbor interaction, and study the real-time and real-space dynamics of nonequilibrium magnetization profiles for a class of pure states. Summarizing our main results, we show that signatures of diffusion for strong interactions are equally pronounced for the integrable and nonintegrable case. In both cases, we further find a clear difference between the dynamics of states with and without internal randomness. We provide an explanation of this difference by a detailed analysis of the local density of states.

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Section: Acknowledgmentsmentioning

confidence: 99%

Real-time dynamics of typical and untypical states in nonintegrable systems

Richter¹,

Jin²,

Raedt³

et al. 2018

Phys. Rev. B

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“…6. All measurements were performed on the IBM BlueGene/Q JUQUEEN [21] system at the JSC. The JUQUEEN consists of 28,672 nodes containing IBM PowerPC A2 CPUs at 1.6 GHz, 16 cores, and 16 GB of RAM per node.…”

Section: Resultsmentioning

confidence: 99%

“…The author gratefully acknowledges the computing time granted by the JARA-HPC Vergabegremium and provided on the JARA-HPC Partition, part of the supercomputer JUQUEEN [21] at Forschungszentrum Jülich. Furthermore, the author would like to thank the Institute of Aerodynamics, RWTH Aachen University, for the provision of their code ZFS.…”

Section: Acknowledgmentsmentioning

confidence: 99%

“…The geometry in most of these cases is small and consumes only a marginal amount of memory, e.g., one of the nasal cavity geometries in [6] consumes around 210 MB in process memory. However, considering a High Performance Computer (HPC) like the IBM BlueGene/Q JUQUEEN [21] at the Jülich Supercomputing Center (JSC), which has 1 GB per computational core available, about 20% of the global process memory is occupied by the nasal cavity geometry and cannot be used for the computation. Future computations for the simulation of flows in complex and large geometries may hence experience memory issues that can only be avoided by a parallel implementation of the geometry or by using less cores per node together with a shared memory parallelization.…”

Section: Introductionmentioning

confidence: 99%

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Efficient Parallel Geometry Distribution for the Simulation of Complex Flows

Lintermann¹

2016

Proceedings of the VII European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS Congress 2016)

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Abstract. Highly resolved intrinsic geometrical shapes used in three-dimensional parallel simulations of fluid flows consume a large portion of the available memory when loaded serially on every process. This demands for a memory efficient implementation of a distributed geometry which is however a non-trivial task when complex spatial domain decomposition methods for the flow domain are involved. To overcome this problem, an algorithm to generate a parallel geometry during the mesh generation is proposed that enables a low-memory subdivision of the geometry based on the decomposition of the flow field. The applied meshing method generates computational grids that can be used for simulations on a quasi-arbitrary number of cores on which the geometry is distributed in an efficient preprocessing step. This allows reducing the number of instances of the geometry in the global memory of the simulation to about one. The algorithm is used to generate a parallel geometry for a large shape consisting of 7 · 10 6 triangles, i.e., for a geometry representing the whole respiratory tract down to the 12 th lung generation. For this case, performance and memory consumption measurements are given for simulations on 8,192 up to 131,072 cores and juxtaposed to results obtained from simulations using non-parallel geometries. The findings show that with the new method not only the memory usage could be reduced by the factors of 1,802 and 19,936 for core numbers of 8,192 and 131,072 but also a large speed-up factor of about 51 is obtained in the geometry I/O and preprocessing. Furthermore, the parallel geometry allows using the sweet spot with respect to a combination of distributed and shared memory parallelization leading to an increase of the computational speed of about 1.43.

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“…JURECA (see Figure 1) serves as a general-purpose supercomputing resource and, in accordance with Forschungszentrum Jülich's dual architecture strategy, augments the leadership-class highly scalable IBM Blue Gene/Q system JUQUEEN (Jülich Supercomputing Centre, 2015). Funding for JURECA was granted by the Helmholtz Association (Helmholtz Association, 2015) through the program "Supercomputing & Big Data".…”

Section: Introductionmentioning

confidence: 99%

JURECA: General-purpose supercomputer at Jülich Supercomputing Centre

Krause¹,

Thörnig²

2016

JLSRF

162

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JURECA is a peta op-scale, general-purpose supercomputer operated by Jülich Supercomputing Centre at Forschungszentrum Jülich. Utilizing a exible cluster architecture based on T-Platforms V-Class blades and a balanced selection of best of its kind components the system supports a wide variety of high-performance computing and data analytics workloads and o ers a low entrance barrier for new users.

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JUQUEEN: IBM Blue Gene/Q<sup>®</sup> Supercomputer System at the Jülich Supercomputing Centre

Cited by 177 publications

References 1 publication

Real-time dynamics of typical and untypical states in nonintegrable systems

Real-time dynamics of typical and untypical states in nonintegrable systems

Efficient Parallel Geometry Distribution for the Simulation of Complex Flows

JURECA: General-purpose supercomputer at Jülich Supercomputing Centre

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