Skip to content

🚀 Quick Start

This page takes you through installation, the first checks, and a small isolated exercise before pointing you to the next task for your existing data.

What it does

GPUMDkit brings common computational-materials tasks such as format conversion, structure analysis, property calculation, and visualization into one command-line tool, without requiring custom scripts.

Before you start

Install GPUMDkit first, then check the command-line entry points. Conda is the recommended route:

conda create -n gpumdkit -c gpumdkit -c conda-forge gpumdkit
conda activate gpumdkit

This installs GPUMDkit and its standard dependencies. You do not need to clone the repository or configure environment variables first.

2. Check the installation

gpumdkit.sh -h
gpumdkit.sh -doctor

-h lists the available options. -doctor checks the Python environment and reports the status of the environment, common packages, and optional packages. MISS for an optional package is not an installation failure; install that package only when you need the corresponding feature.

First practice: convert a POSCAR

Run the exercise in a new directory to avoid overwriting existing files.

(
set -e
mkdir gpumdkit-first-check && cd gpumdkit-first-check || exit 1
cat > POSCAR << 'EOF'
Si
1.0
0 2.715 2.715
2.715 0 2.715
2.715 2.715 0
Si
1
direct
0 0 0
EOF
gpumdkit.sh -pos2exyz POSCAR model.xyz
head model.xyz
)

If model.xyz shows one Si atom and lattice information, this POSCAR-to-extxyz conversion and output check succeeded.

extxyz is extended XYZ: the first line gives the atom count, the second stores lattice and structure-level properties, and later lines store each atom's element, coordinates, and per-atom properties. It is the native training-data format used by NEP.

Existing data: choose the next task

If you already have structures or trajectories, you can skip the practice above. Return to the tutorial index and use the Common Tasks table to choose format conversion, structure sampling, analysis, calculators, plotting, or workflow preparation; each page documents its inputs, outputs, and scope.

Optional packages and agent skills

Some features require optional packages:

pip install neptrain calorine

The package also includes the English and Chinese agent skills. Run the following command to find their installed paths and the instructions for configuring them in your agent client:

gpumdkit.sh -skill

Install from Source (Optional)

If you need to use or modify the source code, clone the repository and run the installer:

git clone https://github.com/zhyan0603/GPUMDkit.git
cd GPUMDkit
source ./install.sh

The installer chooses a shell configuration file from $SHELL, writes the GPUMDkit_path and PATH settings there, and loads them for the current shell. It uses ~/.bashrc by default; when $SHELL points to zsh, it uses ~/.zshrc. If an existing GPUMDkit path is found, the installer prints the old path and asks whether to replace it. Before changing the rc file, it creates a backup.

Read a command before running it

CLI examples use this notation:

Notation Meaning Example
<required> Replace with a value you must provide. Do not type the angle brackets. <output.xyz> → model.xyz
[optional] May be omitted; the script then uses its documented behavior. [max_corr_steps]
... One or more values may follow. <element...>

For an unfamiliar Python-backed command, run its -h option first to read the argument description. Choose time parameters such as dt_fs from your own trajectory-writing settings; they are not inferred from an MD input file. See Plot Scripts for plot types and script-specific argument positions.

Interactive mode

Run gpumdkit.sh and select a module by number. Each module provides its own sub-menu.

CLI mode

Direct commands use fixed positional arguments:

gpumdkit.sh -<option> [args...]

To see the complete option list, run:

gpumdkit.sh -h

Notes

  • For Python-backed commands that expose option help, use gpumdkit.sh -<option> -h; use gpumdkit.sh -plt -h to list plot types. Plot-specific argument positions vary by script.
  • For detailed module usage, use the task navigation on the tutorial index.