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

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About

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

CuGBasis can read various wave-function formats (wfn, wfx, molden and fchk) using IOData and supports up-to g-type orbitals. Please see the website for more information.

To report any issues or ask questions, either open an issue or email qcdevs@gmail.com.

See the website for more information: cuGBasis

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},
}