1 # COMpatible PArticle Discretization and REmap Toolkit
5 The Compadre Toolkit provides a performance portable solution for the parallel evaluation of computationally dense kernels. The toolkit specifically targets the Generalized Moving Least Squares (GMLS) approach, which requires the inversion of small dense matrices. The result is a set of weights that provide the information needed for remap or entries that constitute the rows of some globally sparse matrix.
7 This toolkit focuses on the 'on-node' aspects of meshless PDE solution and remap, namely the parallel construction of small dense matrices and their inversion. What it does **not** provide is the tools for managing fields, inverting globally sparse matrices, or neighbor search that requires orchestration over many MPI processes. This toolkit is designed to be easily dropped-in to an existing MPI (or serial) based framework for PDE solution or remap, with minimal dependencies ([Kokkos](https://github.com/kokkos/kokkos) and [KokkosKernels](https://github.com/kokkos/kokkos-kernels)).
9 ### Generalized Moving Least Squares (GMLS)
11 A GMLS problem requires the specification of a target functional  (Compadre::TargetOperation), a reconstruction space  (Compadre::ReconstructionSpace), and a sampling functional  (Compadre::SamplingFunctional).
13 The Compadre Toolkit is designed to efficiently assemble, factorize, and solve large batches of minimization problems having the form:
15 
17 https://www.codecogs.com/latex/eqneditor.php
18 \[\large \begin{align*}
19 p^{*}& =& \underset{p \in V}{\text{arg min}}\;\frac{1}{2}\sum_{j=1}^N (\lambda_j(u)-\lambda_j(p))^{2}\omega(\tau;\lambda_j)\\\\
20 &&\tau(u) \approx \tau(p^{*})
25 Details about building and using the Compadre toolkit can be found on the [Wiki](https://github.com/SNLComputation/compadre/wiki).
28 [Recent Changes](https://github.com/SNLComputation/compadre/wiki/Changelog)
31 [Installation of Kokkos and KokkosKernels](https://github.com/SNLComputation/compadre/wiki/Kokkos-and-KokkosKernels) [Either automatically configured and built, or user installation location provided]
33 [Installation of Compadre](https://github.com/SNLComputation/compadre/wiki/Building-Compadre)
35 ## Documentation and Tutorials
36 The toolkit is documented by Doxygen. <b>[Documentation is available online](https://snlcomputation.github.io/compadre/index.html)</b> or can be compiled from source.
37 To compile from source: 1.) install doxygen software on your computer, 2.) execute '>> make doc' after having installed the Compadre Toolkit. HTML and Latex documentation will be generated in the <b>doc/</b> folder, in-source.
39 ## Citing the Software
41 If you write a paper using results obtained with the help of the Compadre Toolkit, please cite the following reference which is applicable to every version of the Compadre Toolkit:
44 @software{compadre_toolkit,
45 author = {Paul Kuberry and
48 title = {Compadre Toolkit},
51 doi = {10.11578/dc.20190411.1},
52 url = {https://github.com/SNLComputation/compadre}
56 If you are using a particular release of the Compadre Toolkit and would like to help others to reproduce your results, please cite that release specifically. A reference to the most recent release is:
58 @software{compadre_toolkit_v1_3_0,
59 author = {Paul Kuberry and
62 title = {Compadre Toolkit},
67 doi = {10.5281/zenodo.4499105},
68 url = {https://doi.org/10.5281/zenodo.4499105}
73 ! DOI: 10.11578/dc.20190411.1