We identify hardware that is optimal to produce molecular dynamics trajectories
on Linux compute clusters with the GROMACS 2018 simulation package.
Therefore, we benchmark the GROMACS performance on a diverse set of compute nodes
and relate it to the costs of the nodes, which may include their lifetime costs for
energy and cooling. In agreement with our earlier investigation using GROMACS 4.6
on hardware of 2014, the performance to price ratio of consumer GPU nodes is
considerably higher than that of CPU nodes. However, with GROMACS 2018,
the optimal CPU to GPU processing power balance has shifted even more towards the GPU.
Hence, nodes optimized for GROMACS 2018 and later versions enable a significantly higher
performance to price ratio than nodes optimized for older GROMACS versions.
Moreover, the shift towards GPU processing allows to cheaply upgrade old nodes
with recent GPUs, yielding essentially the same performance as comparable
I studied physics at the University of Göttingen. For my PhD I focused on numerical simulations of Earth’s magnetic field, which brought me in contact with high performance and parallel computing. After a stay at the MPI for Solar System Research I moved to computational biophysics. Since 2004 I am working at the Max Planck Institute for Biophysical Chemistry in the lab of Helmut Grubmüller. I am interested in method development, high performance computing, and atomistic biomolecular simulations.