Metadata-Version: 2.1
Name: cadishi
Version: 1.1.1
Summary: High performance distance histogram calculation framework for CPUs and GPUs
Home-page: https://gitlab.mpcdf.mpg.de/MPIBP-Hummer/Cadishi
Author: Juergen Koefinger, Max Linke, Klaus Reuter
Author-email: khr@mpcdf.mpg.de
License: UNKNOWN
Description: 
        CADISHI
        =======
        
        Introduction
        ------------
        
        CADISHI \-- CAlculation of DIStance HIstograms \-- is a software package
        that enables scientists to compute (Euclidean) distance histograms
        efficiently. Any sets of objects that have 3D Cartesian coordinates may
        be used as input, for example, atoms in molecular dynamics datasets or
        galaxies in astrophysical contexts. CADISHI drives the high-performance
        kernels pydh (CPU) and cudh (GPU, optional) to do the actual histogram
        computation. The kernels pydh and cudh are part of CADISHI and are
        written in C++ and CUDA.
        
        For more information, we refer to our publication:
        
        K. Reuter, J. Koefinger; CADISHI: Fast parallel calculation of
        particle-pair distance histograms on CPUs and GPUs; [Comp. Phys. Comm.
        (236), 274 (2019)](https://doi.org/10.1016/j.cpc.2018.10.018).
        
        A preprint of the paper is available on
        [arXiv.org](https://arxiv.org/abs/1808.01478).
        
        Documentation
        -------------
        
        Documentation is available at [http://cadishi.readthedocs.io/en/latest/
        \<http://cadishi.readthedocs.io/en/latest/\>](). Alternatively, you may
        access the local copy at [doc/html/index.html]{.title-ref} after having
        cloned the repository.
        
        License and Citation
        --------------------
        
        The CADISHI package is released under the permissive MIT license. See
        the file [LICENSE.txt]{.title-ref} for details.
        
        Copyright 2015-2019 Klaus Reuter (MPCDF), Juergen Koefinger (MPIBP)
        
        In case you're using CADISHI for own academic or non-academic research,
        we kindly request that you cite CADISHI in your publications and
        presentations. We suggest the following citation as appropriate:
        
        K. Reuter, J. Koefinger; CADISHI: Fast parallel calculation of
        particle-pair distance histograms on CPUs and GPUs; Computer Physics
        Communications (2018); \<<https://doi.org/10.1016/j.cpc.2018.10.018>\>.
        
Platform: UNKNOWN
Description-Content-Type: text/markdown
