qc-cuGBasis 1.0.2.post2

High performance CUDA/Python library for computing quantum chemistry density-based descriptors for larger systems using GPUs.

About

CuGBasis is a free, and open-source C++/CUDA and Python library for computing efficient computation of scalar, vector, and matrix quantities using NVIDIA GPU's in quantum chemistry. It is highly-optimized and vectorized, making it useful for cases where efficiency matters.

CuGBasis can compute the molecular orbitals, electron density (and its derivatives), electrostatic potentials and many other types of quantum chemistry descriptors and can read various wave-function formats (wfn, wfx, molden and fchk) using IOData and supports up-to g-type orbitals.

See the website for more information: cuGBasis

To report any issues or ask questions, either open an issue or email [e-mail].

Installation

Python 3.9 (or higher), CMake and CUDA is mandatory for installation. qc-cuGBasis can be installed using pip:

pip install qc-cuGBasis

For more detailed installations, please see the website.

Citation

Please use the following citation in any publication:

 @article{cugbasis,
    author = {Tehrani, Alireza and Richer, Michelle and Heidar-Zadeh, Farnaz},
    title = "{CuGBasis: High-performance CUDA/Python library for efficient computation of quantum chemistry density-based descriptors for larger systems}",
    journal = {The Journal of Chemical Physics},
    volume = {161},
    number = {7},
    pages = {072501},
    year = {2024},
    month = {08},
    issn = {0021-9606},
    doi = {10.1063/5.0216781},
    url = {https://doi.org/10.1063/5.0216781},
}