DeepDriveMD, Deep learning-driven Adaptive Molecular Simulations for Protein Folding, is a toolkit developed by Brookhaven National Laboratobry (BNL)/RADICAL Laboratory at Rutgers, in collaboration with Argonne National Laboratory.
This is a main repository of DeepDriveMD used in production runs. You can find the latest publication here:
H. Lee, M. Turilli, S. Jha, D. Bhowmik, H. Ma and A. Ramanathan, "DeepDriveMD: Deep-Learning Driven Adaptive Molecular Simulations for Protein Folding," 2019 IEEE/ACM Third Workshop on Deep Learning on Supercomputers (DLS), Denver, CO, USA, 2019, pp. 12-19, doi: 10.1109/DLS49591.2019.00007. https://ieeexplore.ieee.org/abstract/document/8945122
This is an ongoing develeopment branch you can find the source code under src and data
JSSPP folder holds source code and figures used in the paper
COVID-19 Development (Relocated under archive tag)
There is ongoing activity in associcated with the Covid-19 project. https://github.com/2019-ncovgroup/DrugWorkflows/tree/devel/workflow-2
- OpenMM
- swig 3+
- numpy
- cython
- tensorflow-gpu
- keras
- MDAnalysis
- scipy
- numpy 1.16+
- scikit-learn
- Parmed
- pytables
- h5py
- fs-peptide/vhp: https://github.com/radical-collaboration/DeepDriveMD/tree/master/microscope/experiments
- ntl9: https://github.com/radical-collaboration/DeepDriveMD/tree/master/src/mdrun/ntl9
- OLCF Summit Performance Analysis