This title appears in the Scientific Report :
2013
Parallel Brownian Dynamics Simulation with MPI, OpenMP and UPC
Parallel Brownian Dynamics Simulation with MPI, OpenMP and UPC
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 sha...
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Personal Name(s): | Teijeiro, Carlos (Corresponding author) |
---|---|
Sutmann, Godehard / Taboada, Guillermo L. / Tourino, Juan | |
Contributing Institute: |
Jülich Supercomputing Center; JSC |
Published in: |
Hybrid Particle-Continuum Methods in Computational Materials Physics |
Imprint: |
Jülich
John von Neumann Institute for Computing (NIC)
2013
|
Physical Description: |
25 - 40 |
ISBN: |
978-3-89336-849-5 |
Conference: | Hybrid Particle-Continuum Methods in Computational Materials Physics, Jülich (Germany), 2013-03-04 - 2013-03-07 |
Document Type: |
Contribution to a book Contribution to a conference proceedings |
Research Program: |
Computational Science and Mathematical Methods |
Series Title: |
NIC Series
46 |
Publikationsportal JuSER |
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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. | ||
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