More Bang for Your Buck: Improved use of GPU Nodes for GROMACS 2018

Abstract

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 brand-new hardware.

41 pages, 13 figures, 4 tables. This updated version includes the following improvements: - most notably, added benchmarks for two coarse grain MARTINI systems VES and BIG, resulting in a new Figure 13 - fixed typos - made text clearer in some places - added two more benchmarks for MEM and RIB systems (E3-1240v6 + RTX 2080 / 2080Ti)

Cited by in corpus (8)

• Heterogeneous Parallelization and Acceleration of Molecular Dynamics Simulations in GROMACS
• GROMACS in the cloud: A global supercomputer to speed up alchemical drug design
• Deep Learning on Image Denoising: An overview
• Ookami: Deployment and Initial Experiences
• GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability
• Breaking Down the Parallel Performance of GROMACS, a High-Performance Molecular Dynamics Software
• Mechanistic rules for de novo design of enzymes
• Microsecond-scale sucrose conformational dynamics in aqueous solution via molecular dynamics methods