We present our approach for a scalable implementation of coupled soft matter
simulations for inhomogeneous applications based on the simulation package
ESPResSo and an extended version of the adaptive grid framework p4est. Our main
contribution in this paper is the development and implementation of a joint
partitioning of two or more distinct octree-based grids based on the concept of
a finest common tree. This concept guarantees that, on all grids, the same
process is responsible for each point in space and, thus, avoids communication
of data in overlapping volumes handled in different partitions. We achieve up
to 85 \% parallel efficiency in a weak scaling setting. Our proposed algorithms
take only a small fraction of the overall runtime of grid adaption.
%0 Conference Paper
%1 hirschmann2018loadbalancing
%A Hirschmann, Steffen
%A Lahnert, Michael
%A Schober, Carolin
%A Brunn, Malte
%A Mehl, Miriam
%A Pflüger, Dirk
%B High Performance Computing in Science and Engineering '18
%D 2018
%E Nagel, Wolfgang E.
%E Kröner, Dietmar H.
%E Resch, Michael M.
%I Springer International Publishing
%K imported from:leiterrl
%P 1--510
%R 10.1007/978-3-030-13325-2
%T Load-Balancing and Spatial Adaptivity for Coarse-Grained Molecular Dynamics Applications
%U http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2018-50&engl=0
%X We present our approach for a scalable implementation of coupled soft matter
simulations for inhomogeneous applications based on the simulation package
ESPResSo and an extended version of the adaptive grid framework p4est. Our main
contribution in this paper is the development and implementation of a joint
partitioning of two or more distinct octree-based grids based on the concept of
a finest common tree. This concept guarantees that, on all grids, the same
process is responsible for each point in space and, thus, avoids communication
of data in overlapping volumes handled in different partitions. We achieve up
to 85 \% parallel efficiency in a weak scaling setting. Our proposed algorithms
take only a small fraction of the overall runtime of grid adaption.
%@ 978-3-030-13324-5
@inproceedings{hirschmann2018loadbalancing,
abstract = {We present our approach for a scalable implementation of coupled soft matter
simulations for inhomogeneous applications based on the simulation package
ESPResSo and an extended version of the adaptive grid framework p4est. Our main
contribution in this paper is the development and implementation of a joint
partitioning of two or more distinct octree-based grids based on the concept of
a finest common tree. This concept guarantees that, on all grids, the same
process is responsible for each point in space and, thus, avoids communication
of data in overlapping volumes handled in different partitions. We achieve up
to 85 \% parallel efficiency in a weak scaling setting. Our proposed algorithms
take only a small fraction of the overall runtime of grid adaption.},
added-at = {2020-07-27T15:42:33.000+0200},
author = {Hirschmann, Steffen and Lahnert, Michael and Schober, Carolin and Brunn, Malte and Mehl, Miriam and Pfl{\"u}ger, Dirk},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/202381c7e1fd80a3e8bd2f3ca2e9639f7/ipvs-sc},
booktitle = {High Performance Computing in Science and Engineering '18},
cr-category = {G.1.0 Numerical Analysis General},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Simulation gro{\ss}er Systeme},
doi = {10.1007/978-3-030-13325-2},
editor = {Nagel, Wolfgang E. and Kr{\"o}ner, Dietmar H. and Resch, Michael M.},
ee = {ftp://ftp.informatik.uni-stuttgart.de/pub/library/ncstrl.ustuttgart_fi/INPROC-2018-50/INPROC-2018-50.pdf},
institution = {Universit{\"a}t Stuttgart, Fakult{\"a}t Informatik, Elektrotechnik und Informationstechnik, Germany},
interhash = {776ea39486f58a7994ae54bb23526281},
intrahash = {02381c7e1fd80a3e8bd2f3ca2e9639f7},
isbn = {978-3-030-13324-5},
keywords = {imported from:leiterrl},
language = {Englisch},
month = {Oktober},
pages = {1--510},
publisher = {Springer International Publishing},
timestamp = {2020-07-27T13:42:33.000+0200},
title = {{Load-Balancing and Spatial Adaptivity for Coarse-Grained Molecular Dynamics Applications}},
type = {Konferenz-Beitrag},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2018-50&engl=0},
year = 2018
}