TY - JOUR
T1 - AutoPas in ls1 mardyn
T2 - Massively parallel particle simulations with node-level auto-tuning
AU - Seckler, Steffen
AU - Gratl, Fabio
AU - Heinen, Matthias
AU - Vrabec, Jadran
AU - Bungartz, Hans Joachim
AU - Neumann, Philipp
N1 - Publisher Copyright:
© 2021 Elsevier B.V.
PY - 2021/3
Y1 - 2021/3
N2 - Due to computational cost, simulation software is confronted with the need to always use optimal building blocks — data structures, solver algorithms, parallelization schemes, and so forth — in terms of efficiency, while it typically needs to support a variety of hardware architectures. AutoPas implements the computationally most expensive molecular dynamics (MD) steps (e.g., force calculation) and chooses on-the-fly, i.e., at run time, the optimal combination of the previously mentioned building blocks. We detail decisions made in AutoPas to enable the interplay with MPI-parallel simulations and, to our knowledge, showcase the first MPI-parallel MD simulations that use dynamic tuning. We discuss the benefits of this approach for three simulation scenarios from process engineering, in which we obtain performance improvements of up to 50%, compared to the baseline performance of the highly optimized ls1 mardyn software.
AB - Due to computational cost, simulation software is confronted with the need to always use optimal building blocks — data structures, solver algorithms, parallelization schemes, and so forth — in terms of efficiency, while it typically needs to support a variety of hardware architectures. AutoPas implements the computationally most expensive molecular dynamics (MD) steps (e.g., force calculation) and chooses on-the-fly, i.e., at run time, the optimal combination of the previously mentioned building blocks. We detail decisions made in AutoPas to enable the interplay with MPI-parallel simulations and, to our knowledge, showcase the first MPI-parallel MD simulations that use dynamic tuning. We discuss the benefits of this approach for three simulation scenarios from process engineering, in which we obtain performance improvements of up to 50%, compared to the baseline performance of the highly optimized ls1 mardyn software.
KW - Auto-tuning
KW - AutoPas
KW - MPI
KW - Molecular dynamics
KW - Particle simulations
KW - ls1 mardyn
UR - http://www.scopus.com/inward/record.url?scp=85099677878&partnerID=8YFLogxK
U2 - 10.1016/j.jocs.2020.101296
DO - 10.1016/j.jocs.2020.101296
M3 - Article
AN - SCOPUS:85099677878
SN - 1877-7503
VL - 50
JO - Journal of Computational Science
JF - Journal of Computational Science
M1 - 101296
ER -