| Reference : Parallelizing XDEM: Load-balancing policies and efficiency, a study |
| Scientific congresses, symposiums and conference proceedings : Unpublished conference | |||
| Engineering, computing & technology : Computer science | |||
| Computational Sciences | |||
| http://hdl.handle.net/10993/32810 | |||
| Parallelizing XDEM: Load-balancing policies and efficiency, a study | |
| English | |
Rousset, Alban  [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >] | |
| Besseron, Xavier [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >] | |
| Peters, Bernhard [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >] | |
| Sep-2017 | |
| Yes | |
| International | |
| International Conference on Particle-Based Methods (PARTICLES17) | |
| from 26-09-2017 to 28-09-2017 | |
| Hannover | |
| Germany | |
| [en] HPC ; load-balancing ; DEM | |
| [en] In XDEM, the simulation domain is geometrically decomposed in regular fixed-size cells that are
used to distribute the workload between the processes. The role of the partitioning algorithm is to distribute the cells among all the processes in order to balance the workload. To accomplish this task, the partitioning algorithm relies on a computing/communication cost that has been estimated for each cell. A proper estimation of these costs is fundamental to obtain pertinent results during this phase. The study in the work is twofold. First, we integrate five partitioning algorithms (ORB, RCB, RIB, kway and PhG) in the XDEM framework [1]. Most of these algorithms are implemented within the Zoltan library [2], a parallel framework for partitioning and ordering problems. Secondly, we propose different policies to estimate the computing cost and communication cost of the different cells composing the simulation domain. Then, we present an experimental evaluation and a performance comparison of these partitioning algorithms and cost-estimation policies on a large scale parallel execution of XDEM running on the HPC platform of the University of Luxembourg. Finally, after explaining the pros and cons of each partitioning algorithms and cost-estimation policies, we discuss on the best choices to adopt depending on the simulation case. | |
| Researchers ; Professionals | |
| http://hdl.handle.net/10993/32810 |
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