add documents for conda

doc/install.md

@@ -3,6 +3,7 @@
 - [Easy installation methods](#easy-installation-methods)
 - [Install from source code](#install-from-source-code)
 - [Install i-PI](#install-i-pi)
+- [Building conda packages](#building-conda-packages)
 
 ## Easy installation methods
 
@@ -18,17 +19,33 @@ After your easy installation, DeePMD-kit (`dp`) and LAMMPS (`lmp`) will be avail
 ### Install off-line packages
 Both CPU and GPU version offline packages are avaiable in [the Releases page](https://github.com/deepmodeling/deepmd-kit/releases).
 
+Some packages are splited into two files due to size limit of GitHub. One may merge them into one after downloading:
+```bash
+cat deepmd-kit-2.0.0-cuda11.1_gpu-Linux-x86_64.sh.0 deepmd-kit-2.0.0-cuda11.1_gpu-Linux-x86_64.sh.1 > deepmd-kit-2.0.0-cuda11.1_gpu-Linux-x86_64.sh
+```
+
 ### Install with conda
 DeePMD-kit is avaiable with [conda](https://github.com/conda/conda). Install [Anaconda](https://www.anaconda.com/distribution/#download-section) or [Miniconda](https://docs.conda.io/en/latest/miniconda.html) first.
 
-To install the CPU version:
+One may create an environment that contains the CPU version of DeePMD-kit and LAMMPS:
+```bash
+conda create -n deepmd deepmd-kit=*=*cpu lammps-dp=*=*cpu -c https://conda.deepmodeling.org
+```
+
+Or one may want to create a GPU environment containing [CUDA Toolkit](https://docs.nvidia.com/deploy/cuda-compatibility/index.html#binary-compatibility__table-toolkit-driver):
 ```bash
-conda install deepmd-kit=*=*cpu lammps-dp=*=*cpu -c deepmodeling
+conda create -n deepmd deepmd-kit=*=*gpu lammps-dp=*=*gpu cudatoolkit=11.1 -c https://conda.deepmodeling.org -c nvidia
 ```
+One could change the CUDA Toolkit version from `11.1` to `10.1` or `10.0`.
 
-To install the GPU version containing [CUDA 10.1](https://docs.nvidia.com/deploy/cuda-compatibility/index.html#binary-compatibility__table-toolkit-driver):
+One may speficy the DeePMD-kit version such as `2.0.0` using
 ```bash
-conda install deepmd-kit=*=*gpu lammps-dp=*=*gpu -c deepmodeling
+conda create -n deepmd deepmd-kit=2.0.0=*cpu lammps-dp=2.0.0=*cpu -c https://conda.deepmodeling.org
+```
+
+One may enable the environment using
+```bash
+conda activate deepmd
 ```
 
 ### Install with docker
@@ -249,3 +266,24 @@ Test with Pytest:
 pip install pytest
 pytest --pyargs ipi.tests
 ```
+
+## Building conda packages
+
+One may want to keep both convenience and personalization of the DeePMD-kit. To achieve this goal, one can consider builing conda packages. We provide building scripts in [deepmd-kit-recipes organization](https://github.com/deepmd-kit-recipes/). These building tools are driven by [conda-build](https://github.com/conda/conda-build) and [conda-smithy](https://github.com/conda-forge/conda-smithy).
+
+For example, if one wants to turn on `MPIIO` package in LAMMPS, go to [`lammps-dp-feedstock`](https://github.com/deepmd-kit-recipes/lammps-dp-feedstock/) repository and modify `recipe/build.sh`. `-D PKG_MPIIO=OFF` should be changed to `-D PKG_MPIIO=ON`. Then go to the main directory and executing
+
+```sh
+./build-locally.py
+```
+
+This requires the Docker has been installed. After the building, the packages will be generated in `build_artifacts/linux-64` and `build_artifacts/noarch`, and then one can install then execuating
+```sh
+conda create -n deepmd lammps-dp -c file:///path/to/build_artifacts -c https://conda.deepmodeling.org -c nvidia
+```
+
+One may also upload packages to one's Anaconda channel, so they can be installed on other machines:
+
+```sh
+anaconda upload /path/to/build_artifacts/linux-64/*.tar.bz2 /path/to/build_artifacts/noarch/*.tar.bz2
+```