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DeePMD-kit
DeePMD-kit is a package written in Python/C++, designed to minimize the effort required to build deep learning based model of interatomic potential energy and force field and to perform molecular dynamics (MD). This brings new hopes to addressing the accuracy-versus-efficiency dilemma in molecular simulations. Applications of DeePMD-kit span from finite molecules to extended systems and from metallic systems to chemically bonded systems. The NGC DeePMD-kit container builds upon the NGC TensorFlow container, adding DeePMD-kit with LAMMPS plugin support. System Requirements Pascal(sm60), Volta(sm70), or Ampere(sm80) NVIDIA GPU(s) x86_64 CPU supporting avx2_256 instruction set CUDA driver version >= 510.39.01, -or- r418(>=40.04), r450(>=36.06), r460(>=27.04), r470(>=57.02) Running with DockerStart an interactive session in the container docker run -it --rm --gpus all --shm-size=1g --ulimit memlock=-1 nvcr.io/hpc/deepmd-kit:2.1.1Fetch the DeePMD-kit example data git clone https://github.com/deepmodeling/deepmd-kit.gitTrain the example cd deepmd-kit/examples/water/se_e2_a dp train input.jsonFreeze the model dp freeze -o frozen_model.pbRun the LAMMPS example simulation cd ../lmp cp ../se_e2_a/frozen_model.pb . mpirun --allow-run-as-root -n 1 lmp -k on g 1 -sf kk -pk kokkos cuda/aware on neigh full comm device -in in.plugin.lammps Suggested Reading DeePMD-kit documentation Deep Learning Frameworks Documentation - Running A Container NGC Container User Guide |
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