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ddcMD: A fully GPU-accelerated molecular dynamics program for the Martini force field
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...
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Published in: | The Journal of chemical physics 2020-07, Vol.153 (4), p.045103-045103 |
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Main Authors: | , , , , , , , , |
Format: | Article |
Language: | English |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | 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. |
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ISSN: | 0021-9606 1089-7690 |
DOI: | 10.1063/5.0014500 |