DP Tutorial 2: DeePMD-kit: Install with Conda & Offline Packages & Docker

Posted on In Word count in article: 305 Reading time ≈ 1 mins.

Do you prepare to read a long article before clicking the tutorial? Since we can teach you how to setup a DeePMD-kit training in 5 minutes, we can also teach you how to install DeePMD-kit in 5 minutes. The installation manual will be introduced as follows:

Install with conda

After you install conda, you can install the CPU version with the following command:

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conda install deepmd-kit=*=*cpu lammps-dp=*=*cpu -c deepmodeling

To install the GPU version containing CUDA 10.1:

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conda install deepmd-kit=*=*gpu lammps-dp=*=*gpu -c deepmodeling

If you want to use the specific version, just replace * with the version:

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conda install deepmd-kit=1.3.3=*cpu lammps-dp=1.3.3=*cpu -c deepmodeling

Install with offline packages

Download offline packages in the Releases page, or use wget:

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wget https://github.com/deepmodeling/deepmd-kit/releases/download/v1.3.3/deepmd-kit-1.3.3-cuda10.1_gpu-Linux-x86_64.sh -O deepmd-kit-1.3.3-cuda10.1_gpu-Linux-x86_64.sh

Take an example of v1.3.3. Execuate the following commands and just follow the prompts.

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sh deepmd-kit-1.3.1-cuda10.1_gpu-Linux-x86_64.sh

With Docker

To pull the CPU version:

docker pull ghcr.io/deepmodeling/deepmd-kit:1.2.2_cpu
To pull the GPU version:

docker pull ghcr.io/deepmodeling/deepmd-kit:1.2.2_cuda10.1_gpu

Tips

dp is the program of DeePMD-kit and lmp is the program of LAMMPS.

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dp -h
lmp -h

GPU version has contained CUDA Toolkit. Note that different CUDA versions support different NVIDIA driver versions. See NVIDIA documents for details.

Don't hurry up and try such a convenient installation process. But I still want to remind everyone that the above installation methods only support the official version released by DeePMD-kit. If you need to use the devel version, you still need to go through a long compilation process. Please refer to the installation manual.