Posted onWord count in article: 1.3kReading time ≈5 mins.
The integration of machine learning and physical modeling is changing the paradigm of scientific research. Those who hope to extend the frontier of science and solve challenging practical problems through computational modeling are coming together in new ways never seen before. This calls for a new infrastructure--new platforms for collaboration, new coding frameworks, new data processing schemes, and new ways of using the computing power. It also calls for a new culture—the culture of working together closely for the benefit of all, of free exchange and sharing of knowledge and tools, of respect and appreciation of each other's work, and of the pursuit of harmony among diversity.
The DeepModeling community is a community of such a group of people.
Posted onIntutorialWord count in article: 305Reading 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:
dp is the program of DeePMD-kit and lmp is the program of LAMMPS.
1 2
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.
Posted onIntutorialWord count in article: 949Reading time ≈3 mins.
DeePMD-kit is a software to implement Deep Potential. There is a lot of information on the Internet, but there are not so many tutorials for the new hand, and the official guide is too long. Today, I'll take you 5 minutes to get started with DeePMD-kit.
Let's take a look at the training process of DeePMD-kit:
graph LR
A[Prepare data] --> B[Training]
B --> C[Freeze the model]