Abstract
We have implemented the Martini force field within Lawrence Livermore National Laboratory's molecular dynamics program, ddcMD. The program is extended to a heterogeneous programming model so that it can exploit graphics processing unit (GPU) accelerators. In addition to the Martini force field being ported to the GPU, the entire integration step, including thermostat, barostat, and constraint solver, is ported as well, which speeds up the simulations to 278-fold using one GPU vs one central processing unit (CPU) core. A benchmark study is performed with several test cases, comparing ddcMD and GROMACS Martini simulations. The average performance of ddcMD for a protein-lipid simulation system of 136k particles achieves 1.04 µs/day on one NVIDIA V100 GPU and aggregates 6.19 µs/day on one Summit node with six GPUs. The GPU implementation in ddcMD offloads all computations to the GPU and only requires one CPU core per simulation to manage the inputs and outputs, freeing up remaining CPU resources on the compute node for alternative tasks often required in complex simulation campaigns. The ddcMD code has been made open source and is available on GitHub at https://github.com/LLNL/ddcMD.
Highlights
Molecular dynamics (MD) simulations compute the positions and velocities of particles using Newton’s laws of motion
In addition to the Martini force field being ported to the graphics processing unit (GPU), the entire integration step, including thermostat, barostat, and constraint solver, is ported as well, which speeds up the simulations to 278-fold using one GPU vs one central processing unit (CPU) core
The GPU implementation in ddcMD offloads all computations to the GPU and only requires one CPU core per simulation to manage the inputs and outputs, freeing up remaining CPU resources on the compute node for alternative tasks often required in complex simulation campaigns
Summary
Molecular dynamics (MD) simulations compute the positions and velocities of particles using Newton’s laws of motion. Popular biomolecular MD simulation codes include CHARMM, GROMACS, AMBER, NAMD, and OpenMM.. The speed and accuracy of the bio-MD simulations have been improved significantly over the past few decades, the energy and force functions remain largely unchanged. These energy terms can be divided into two categories, bonded and non-bonded terms. CHARMM, AMBER, OPLS, and GROMOS8 are all/united-atom force fields, while Martini, ELBA, and SIRAH11,12 are coarse-grained (CG) force fields where multiple heavy atoms are merged into a single “bead”; both types of force fields are widely employed in biomolecular simulations
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
