Developed by the L_Sim group in the MEM laboratory, BigDFT is a density functional theory (DFT) massively parallel electronic structure code using a wavelet basis set with the capability to use a linear scaling method.
Using Graphics Processing Units (GPU) can boost considerably BigDFT. The article 'Accurate, Large-Scale and Affordable Hybrid-PBE0 Calculations with GPU-Accelerated Supercomputers' (see https://arxiv.org/pdf/1712.07973.pdf) shows some capabilities of GPU-accelerated BigDFT.
In order to simplify the BigDFT installation, we provide a Docker container for BigDFT in collaboration with the NVIDIA company. Docker container makes it possible to isolate an application into a small, lightweight execution environment that share the operating system kernel and provide all necessary components for the given application.
The Docker contained for BigDFT ready to use with GPU is available in the NVIDIA web page https://www.nvidia.com/en-us/data-center/gpu-accelerated-applications/bigdft