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| Home > Publications database > Parallel Brownian Dynamics Simulation with MPI, OpenMP and UPC > print |
| 001 | 141420 | ||
| 005 | 20210129212933.0 | ||
| 020 | _ | _ | |a 978-3-89336-849-5 |
| 037 | _ | _ | |a FZJ-2013-06600 |
| 041 | _ | _ | |a eng |
| 082 | _ | _ | |a 500 |
| 100 | 1 | _ | |a Teijeiro, Carlos |0 P:(DE-HGF)0 |b 0 |e Corresponding author |
| 111 | 2 | _ | |a Hybrid Particle-Continuum Methods in Computational Materials Physics |c Jülich |d 2013-03-04 - 2013-03-07 |w Germany |
| 245 | _ | _ | |a Parallel Brownian Dynamics Simulation with MPI, OpenMP and UPC |
| 260 | _ | _ | |a Jülich |c 2013 |b John von Neumann Institute for Computing (NIC) |
| 295 | 1 | 0 | |a Hybrid Particle-Continuum Methods in Computational Materials Physics |
| 300 | _ | _ | |a 25 - 40 |
| 336 | 7 | _ | |a Contribution to a conference proceedings |b contrib |m contrib |0 PUB:(DE-HGF)8 |s 1389087308_22881 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a Contribution to a book |0 PUB:(DE-HGF)7 |2 PUB:(DE-HGF) |m contb |
| 336 | 7 | _ | |a Conference Paper |0 33 |2 EndNote |
| 336 | 7 | _ | |a CONFERENCE_PAPER |2 ORCID |
| 336 | 7 | _ | |a Output Types/Conference Paper |2 DataCite |
| 336 | 7 | _ | |a conferenceObject |2 DRIVER |
| 336 | 7 | _ | |a INPROCEEDINGS |2 BibTeX |
| 490 | 0 | _ | |a NIC Series |v 46 |
| 520 | _ | _ | |a This work presents the design and implementation of a parallel simulation code for the Brownian motion of particles in a fluid. Three different parallelization approaches have been followed:
(1) traditional distributed memory message-passing programming with MPI, (2) a directivebased approach on shared memory with OpenMP, and (3) the Partitioned Global Address Space (PGAS) programming model, oriented towards hybrid shared/distributed memory systems, with the Unified Parallel C (UPC) language. According to the selected environment, different domain decompositions and work distributions are studied in terms of efficiency and programmability in order to select the most suitable strategy. Performance results on different testbeds and using a large number of threads are presented in order to assess the performance and scalability of the parallel solutions. |
| 536 | _ | _ | |a 411 - Computational Science and Mathematical Methods (POF2-411) |0 G:(DE-HGF)POF2-411 |c POF2-411 |x 0 |f POF II |
| 588 | _ | _ | |a Dataset connected to GVK, |
| 700 | 1 | _ | |a Sutmann, Godehard |0 P:(DE-Juel1)132274 |b 1 |
| 700 | 1 | _ | |a Taboada, Guillermo L. |0 P:(DE-HGF)0 |b 2 |
| 700 | 1 | _ | |a Tourino, Juan |0 P:(DE-HGF)0 |b 3 |
| 909 | C | O | |o oai:juser.fz-juelich.de:141420 |p VDB |
| 910 | 1 | _ | |a Forschungszentrum Jülich GmbH |0 I:(DE-588b)5008462-8 |k FZJ |b 1 |6 P:(DE-Juel1)132274 |
| 913 | 2 | _ | |a DE-HGF |b Key Technologies |l Supercomputing & Big Data |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 |
| 913 | 1 | _ | |a DE-HGF |b Schlüsseltechnologien |l Supercomputing |1 G:(DE-HGF)POF2-410 |0 G:(DE-HGF)POF2-411 |2 G:(DE-HGF)POF2-400 |v Computational Science and Mathematical Methods |x 0 |4 G:(DE-HGF)POF |3 G:(DE-HGF)POF2 |
| 914 | 1 | _ | |y 2013 |
| 920 | 1 | _ | |0 I:(DE-Juel1)JSC-20090406 |k JSC |l Jülich Supercomputing Center |x 0 |
| 980 | _ | _ | |a contrib |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a UNRESTRICTED |
| 980 | _ | _ | |a contb |
| 980 | _ | _ | |a I:(DE-Juel1)JSC-20090406 |
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