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| Hauptseite > Publikationsdatenbank > Multi-Level Load Balancing for Parallel Particle Simulations > print |
| Hauptseite > Publikationsdatenbank > Multi-Level Load Balancing for Parallel Particle Simulations > print |
| 001 | 868011 | ||
| 005 | 20210130004021.0 | ||
| 020 | _ | _ | |a 978-84-121101-1-1 |
| 037 | _ | _ | |a FZJ-2019-06604 |
| 041 | _ | _ | |a English |
| 100 | 1 | _ | |a Sutmann, Godehard |0 P:(DE-Juel1)132274 |b 0 |e Corresponding author |u fzj |
| 111 | 2 | _ | |a VI International Conference on Particle-based Methods–Fundamentals and Applications |c Barcelona |d 2019-10-28 - 2019-10-30 |w Spain |
| 245 | _ | _ | |a Multi-Level Load Balancing for Parallel Particle Simulations |
| 260 | _ | _ | |a Barcelona, Spain |c 2019 |b International Centre for Numerical Methods in Engineering (CIMNE) |
| 300 | _ | _ | |a 80 - 92 |
| 336 | 7 | _ | |a CONFERENCE_PAPER |2 ORCID |
| 336 | 7 | _ | |a Conference Paper |0 33 |2 EndNote |
| 336 | 7 | _ | |a INPROCEEDINGS |2 BibTeX |
| 336 | 7 | _ | |a conferenceObject |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Conference Paper |2 DataCite |
| 336 | 7 | _ | |a Contribution to a conference proceedings |b contrib |m contrib |0 PUB:(DE-HGF)8 |s 1576756576_22299 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a Contribution to a book |0 PUB:(DE-HGF)7 |2 PUB:(DE-HGF) |m contb |
| 520 | _ | _ | |a Ideas from multi-level relaxation methods are combined with loadbalancing techniques to achieve a convergence acceleration for a homogeneous workload distribution over a given set of processors when the underlying workfunction is inhomogeneously distributed in space. The algorithm is based on an orthogonal recursive bisection approach which is evaluated via a hierarchically refined coarse integration.The method only requires a minimal information transfer across processors during the tree traversal steps. It is described of how to partition the system of processors to geometrical space, when global information is needed for the spatial tesselation. |
| 536 | _ | _ | |a 511 - Computational Science and Mathematical Methods (POF3-511) |0 G:(DE-HGF)POF3-511 |c POF3-511 |f POF III |x 0 |
| 856 | 4 | _ | |u https://congress.cimne.com/particles2019/frontal/doc/Ebook_Particles_2019.pdf |
| 909 | C | O | |o oai:juser.fz-juelich.de:868011 |p VDB |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 0 |6 P:(DE-Juel1)132274 |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |1 G:(DE-HGF)POF3-510 |0 G:(DE-HGF)POF3-511 |2 G:(DE-HGF)POF3-500 |v Computational Science and Mathematical Methods |x 0 |4 G:(DE-HGF)POF |3 G:(DE-HGF)POF3 |l Supercomputing & Big Data |
| 914 | 1 | _ | |y 2019 |
| 920 | _ | _ | |l yes |
| 920 | 1 | _ | |0 I:(DE-Juel1)JSC-20090406 |k JSC |l Jülich Supercomputing Center |x 0 |
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| 980 | _ | _ | |a UNRESTRICTED |
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