@inproceedings {INPROC-2020-16,
author = {Steffen Hirschmann and Andreas Kronenburg and Colin W. Glass and Dirk Pfl{\"u}ger},
title = {{Load-Balancing for Large-Scale Soot Particle Agglomeration Simulations}},
booktitle = {Parallel Computing: Technology Trends},
editor = {Ian Foster and Gerhard R. Joubert and Ludek Kucera and Wolfgang E. Nagel and Frans Peters},
publisher = {IOS Press},
institution = {Universit{\"a}t Stuttgart, Fakult{\"a}t Informatik, Elektrotechnik und Informationstechnik, Germany},
series = {Advances in Parallel Computing},
volume = {36},
pages = {147--156},
type = {Konferenz-Beitrag},
month = {M{\"a}rz},
year = {2020},
doi = {10.3233/APC200035},
language = {Englisch},
cr-category = {G.0 Mathematics of Computing General},
ee = {ftp://ftp.informatik.uni-stuttgart.de/pub/library/ncstrl.ustuttgart_fi/INPROC-2020-16/INPROC-2020-16.pdf},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Simulation gro{\ss}er Systeme},
abstract = {In this work, we combine several previous efforts to simulate a large-scale
soot particle agglomeration with a dynamic, multi-scale turbulent background
flow field. We build upon previous simulations which include 3.2 million
particles and implement load-balancing into the used simulation software as
well as tests of the load-balancing mechanisms on this scenario. We increase
the simulation to 109.85 million particles, superpose a dynamically changing
multi-scale background flow field and use our software enhancements to the
molecular dynamics software ESPResSo to simulate this on a Cray XC40
supercomputer. To verify that our setup reproduces essential physics we scale
the influence of the flow field down to make the scenario mostly homogeneous on
the subdomain scale. Finally, we show that even on the homogeneous version of
this soot particle agglomeration simulation, load-balancing still pays off.},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2020-16&engl=0}
}
@inproceedings {INPROC-2018-50,
author = {Steffen Hirschmann and Michael Lahnert and Carolin Schober and Malte Brunn and Miriam Mehl and Dirk Pfl{\"u}ger},
title = {{Load-Balancing and Spatial Adaptivity for Coarse-Grained Molecular Dynamics Applications}},
booktitle = {High Performance Computing in Science and Engineering '18},
editor = {Wolfgang E. Nagel and Dietmar H. Kr{\"o}ner and Michael M. Resch},
publisher = {Springer International Publishing},
institution = {Universit{\"a}t Stuttgart, Fakult{\"a}t Informatik, Elektrotechnik und Informationstechnik, Germany},
pages = {1--510},
type = {Konferenz-Beitrag},
month = {Oktober},
year = {2018},
isbn = {978-3-030-13324-5},
doi = {10.1007/978-3-030-13325-2},
language = {Englisch},
cr-category = {G.1.0 Numerical Analysis General},
ee = {ftp://ftp.informatik.uni-stuttgart.de/pub/library/ncstrl.ustuttgart_fi/INPROC-2018-50/INPROC-2018-50.pdf},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Simulation gro{\ss}er Systeme},
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.},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2018-50&engl=0}
}
@inproceedings {INPROC-2016-45,
author = {Steffen Hirschmann and Dirk Pfl{\"u}ger and Colin W. Glass},
title = {{Towards Understanding Optimal Load-Balancing of Heterogeneous Short-Range Molecular Dynamics}},
booktitle = {2016 IEEE 23rd International Conference on High Performance Computing Workshops (HiPCW)},
publisher = {IEEE},
institution = {Universit{\"a}t Stuttgart, Fakult{\"a}t Informatik, Elektrotechnik und Informationstechnik, Germany},
pages = {130--141},
type = {Konferenz-Beitrag},
month = {Dezember},
year = {2016},
doi = {10.1109/HiPCW.2016.027},
language = {Englisch},
cr-category = {G.1.6 Numerical Analysis Optimization},
ee = {ftp://ftp.informatik.uni-stuttgart.de/pub/library/ncstrl.ustuttgart_fi/INPROC-2016-45/INPROC-2016-45.pdf},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Simulation gro{\ss}er Systeme},
abstract = {},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2016-45&engl=0}
}
@inproceedings {INPROC-2014-96,
author = {Steffen Hirschmann},
title = {{GPU-Based Regression Analysis on Sparse Grids}},
booktitle = {Informatik 2014, Big Data - Komplexit{\"a}t meistern},
editor = {E. Pl{\"o}dereder and L. Grunske and E. Schneider and D. Ull},
address = {Bonn},
publisher = {Gesellschaft f{\"u}r Informatik e.V.},
institution = {Universit{\"a}t Stuttgart, Fakult{\"a}t Informatik, Elektrotechnik und Informationstechnik, Germany},
series = {LNI},
volume = {232},
pages = {2425--2436},
type = {Konferenz-Beitrag},
month = {September},
year = {2014},
language = {Englisch},
cr-category = {G.1.3 Numerical Linear Algebra},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Simulation gro{\ss}er Systeme},
abstract = {},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2014-96&engl=0}
}
@article {ART-2019-05,
author = {Steffen Hirschmann and Colin W. Glass and Dirk Pfl{\"u}ger},
title = {{Enabling unstructured domain decompositions for inhomogeneous short-range molecular dynamics in ESPResSo}},
journal = {The European Physical Journal Special Topics},
publisher = {Springer Nature},
volume = {227},
number = {14},
pages = {1779--1788},
type = {Artikel in Zeitschrift},
month = {M{\"a}rz},
year = {2019},
issn = {1951-6401},
doi = {10.1140/epjst/e2019-800159-0},
language = {Englisch},
cr-category = {G.0 Mathematics of Computing General},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Simulation gro{\ss}er Systeme},
abstract = {In short-range molecular dynamics (MD) simulations, inhomogeneous particle
distributions that dynamically change over time require flexible load-balancing
methods to achieve good parallel efficiency. We have realized a general
framework that can support different load-balancing methods and that can extend
existing simulation packages in a minimally invasive way. This is a follow-up
to recent work where we integrated it into the MD software ESPResSo to support
load-balancing. We have realized a first partitioning strategy based on
space-filling curves that can be used for efficient load-balanced multi-physics
simulations. In this work we present a new graph-based partitioning strategy
that leads to unstructured spatial domain decompositions and integrates well
into the existing framework. We apply this to an inhomogeneous soot
agglomeration scenario. For several load metrics, graph partitioning leads to
better results than space-filling curves. The results indicate that the
parallel performance for a given scenario requires a delicate combination of
partitioning strategy and load metrics.},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=ART-2019-05&engl=0}
}
@inbook {INBOOK-2017-06,
author = {Steffen Hirschmann and Malte Brunn and Michael Lahnert and Colin W. Glass and Miriam Mehl and Dirk Pfl{\"u}ger},
title = {{Load balancing with p4est for Short-Range Molecular Dynamics with ESPResSo}},
series = {Advances in Parallel Computing},
publisher = {IOS Press},
volume = {32},
pages = {455--464},
type = {Beitrag in Buch},
month = {September},
year = {2017},
doi = {10.3233/978-1-61499-843-3-455},
language = {Englisch},
cr-category = {G.0 Mathematics of Computing General},
ee = {ftp://ftp.informatik.uni-stuttgart.de/pub/library/ncstrl.ustuttgart_fi/INBOOK-2017-06/INBOOK-2017-06.pdf},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Simulation gro{\ss}er Systeme},
abstract = {},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INBOOK-2017-06&engl=0}
}