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Acknowledgements
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Contributors
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.. todo:: Make sure contribution section cross references are correct.

This book includes contributions from the VTK-m community including the
VTK-m development team and the user community.
We would like to thank the following people for their significant
contributions to this text:

.. NOTE: Also make sure that the contribution list is updated in index.rst

**Vicente Bolea**, **Nickolas Davis**, **Matthew Letter**, and **Nick Thompson** for their help keeping the user's guide up to date with the |VTKm| source code.

**Sujin Philip**, **Robert Maynard**, **James Kress**, **Abhishek Yenpure**, **Mark Kim**, and **Hank Childs** for their descriptions of numerous filters.

.. Sujin Philip: Surface normals, normals in Marching Cubes
.. Robert Maynard: Gradient, warp scalars, warp vectors, histogram, extract structured
.. James Kress: Point transform
.. Abhishek Yenpure: Point merge
.. Mark Kim: ZFP compression
.. Hank Childs: Mesh Quality Metrics

**Allison Vacanti** for her documentation of..

.. several |VTKm| features in the `Extract Component Arrays`_ and `SwizzleArrays`_ sections as well as select filters.

.. Allie Vacanti filters: Surface normals.

**David Pugmire** for his documentation of..

.. partitioned data sets (Section \ref{sec:DataSets:PartitionedDataSet}) and select filters.

.. Dave Pugmire filters: Streamlines, point transform, coordinate system transforms, add ghost cells, remove ghost cells.

**Abhishek Yenpure** and **Li-Ta Lo** for their documentation of locator structures in :chapref:`locators:Locators`.

.. Abhishek Yenpure: General cell locators and BoundingIntervalHierarchy
.. Li-Ta Lo: General point locators and uniform grid point locator, particle density

**Li-Ta Lo** for his documentation of random array handles and particle
density filters.

.. ArrayHandleRandomUniformBits.

**James Kress** for his documentation on |VTKm|'s testing classes.

**Manish Mathai** for his documentation of rendering features..

.. (Chapter~\ref{chap:Rendering}).


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Funding
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This project has been funded in whole or in part with Federal funds from the Department of Energy, including from Oak Ridge National Laboratory, Los Alamos National Laboratory, and Sandia National Laboratories.

This manuscript has been authored in part by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE).
The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes.

Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia LLC, a wholly owned subsidiary of Honeywell International Inc. for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

This research was supported by the Exascale Computing Project (17-SC-20-SC), a joint project of the U.S.
Department of Energy's Office of Science and National Nuclear Security Administration, responsible for delivering a capable exascale ecosystem, including software, applications, and hardware technology, to support the nation's exascale computing imperative.

This work was supported in part by the U.S. Department of Energy (DOE) RAPIDS SciDAC project under contract number DE-AC05-00OR22725 and by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of the U.S. Department of Energy Office of Science and the National Nuclear Security Administration.

This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725.

This research used resources of the Argonne Leadership Computing Facility, a U.S. Department of Energy (DOE) Office of Science user facility at Argonne National Laboratory and is based on research supported by the U.S. DOE Office of Science-Advanced Scientific Computing Research Program, under Contract No. DE-AC02-06CH11357.
