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Update gpu Barnes-Hut code with latest version from Martin Burtscher.
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insertinterestingnamehere committed Aug 20, 2020
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5 changes: 4 additions & 1 deletion lonestar/scientific/gpu/barneshut/CMakeLists.txt
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# This app has to be built with -O1 to avoid a compiler bug.
set(CMAKE_CUDA_FLAGS_RELEASE "-O1 -DNDEBUG")
set(CMAKE_CUDA_FLAGS_RELWITHDEBINFO "-O1 -g -DNDEBUG")
app_scientific_gpu(bh barneshut)
add_test_gpu(barneshut rmat15 rmat15.out bh 50000 2 0)
add_test(NAME barneshut COMMAND barneshut-gpu 50000 2 0)
56 changes: 30 additions & 26 deletions lonestar/scientific/gpu/barneshut/LICENSE.md
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CUDA BarnesHut v3.1: Simulation of the gravitational forces
in a galactic cluster using the Barnes-Hut n-body algorithm
L-BH v4.5: Simulation of the gravitational forces in a star cluster using
the Barnes-Hut n-body algorithm.

Copyright (c) 2013, Texas State University-San Marcos. All rights reserved.
Copyright (c) 2010-2020 Texas State University. All rights reserved.

Redistribution and use in source and binary forms, with or without modification,
are permitted for academic, research, experimental, or personal use provided that
the following conditions are met:
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:

* Redistributions of source code must retain the above copyright notice,
this list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
* Neither the name of Texas State University-San Marcos nor the names of its
contributors may be used to endorse or promote products derived from this
software without specific prior written permission.

For all other uses, please contact the Office for Commercialization and Industry
Relations at Texas State University-San Marcos <http://www.txstate.edu/ocir/>.
* Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
* Neither the name of Texas State University nor the names of its
contributors may be used to endorse or promote products derived from
this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED
IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT,
INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE
OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED
OF THE POSSIBILITY OF SUCH DAMAGE.
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL TEXAS STATE UNIVERSITY BE LIABLE FOR ANY
DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

Authors: Martin Burtscher and Sahar Azimi

URL: The latest version of this code is available at
https://userweb.cs.txstate.edu/~burtscher/research/ECL-BH/.

Author: Martin Burtscher <[email protected]>
Publication: This work is described in detail in the following paper.
Martin Burtscher and Keshav Pingali. An Efficient CUDA Implementation of the
Tree-based Barnes Hut n-Body Algorithm. Chapter 6 in GPU Computing Gems
Emerald Edition, pp. 75-92. January 2011.
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