Installation
BigDFT can be installed directly using a package manager or compiled from source. In general, the preferred installation way depends on the reason for the usage of the code. In a supercomputer, we advise to install from source first, in order to identify the correct installation environment, which would trigger the remote compilation approach.
For instructions of a minimal install for Ubuntu see Minimum Install Walkthrough. If you run into errors during the install process, you may be able to find a solution to your problem on the Errors and Fixes page.
There are also other installation methods, which are more adapted for local workstations and small laboratory clusters, which are listed below.
Install via pip
pip can be used to install the client version of BigDFT. The client version can’t be used to run actual calculations, but can be used to generate input files and perform postprocessing.
pip install PyBigDFT
Install via Docker
Docker is a virtualization platform that allows us to distribute BigDFT and all of its associated dependencies in a single container. The BigDFT container, along with detailed instructions, is available here.
sudo docker run -ti \
-e OMP_NUM_THREADS=4 \
-v $PWD:/results -w /results \
bigdft/runtime:openmpi \
mpirun -np 2 bigdft
Install via Package Mangers
Conda is a cross-platform package and environment management system which can be used to install BigDFT on Linux / Mac platforms.
conda install -c conda-forge bigdft-suite
BigDFT packages are also available for the more HPC-centric Spack:
spack install bigdft-suite
and Guix-HPC.
Install from Source
- Installing BigDFT From Source
- Using the configuration file (
rcfile) - Separating the build of the core packages from the upstream (useful for developers)
- Installing from a
configureline - Linking external software with BigDFT-suite libraries
- The BigDFT Installer class
- Minimum Install Walkthrough
- Errors and Fixes
- Issues with autogen phase
- Issues with build phase