A Dinesh dineshadepu

Kokkos installation

add the following to the bashrc file

Add the following line to the bashrc

export KOKKOS_INSTALL_DIR=/home/username/post_doc/softwares/kokkos/build/install

Execute the following in the terminal

The current documentation is given after installation

For Linux 64, Open MPI is built with CUDA awareness but this support is disabled by default.                                                                              
To enable it, please set the environment variable OMPI_MCA_opal_cuda_support=true before                                                                                  
launching your MPI processes. Equivalently, you can set the MCA parameter in the command line:                                                                            
mpiexec --mca opal_cuda_support 1 ...                                                
                                                                                     
In addition, the UCX support is also built but disabled by default.                  
To enable it, first install UCX (conda install -c conda-forge ucx). Then, set the environment

Install Kokkos, for GPU build

Install benchmark

Can be found https://github.com/google/benchmark#requirements here

Install Boost

Download from https://www.boost.org/users/history/version_1_82_0.html
Unzip and create a folder 'install'
Installation instructions are https://www.boost.org/doc/libs/1_83_0/more/getting_started/unix-variants.html#prepare-to-use-a-boost-library-binary

Install ArborX

ffmpeg -i 3d_dam_break.webm -vf "crop=trunc(iw/2)*2:trunc(ih/2)*2" 3d_dam_break.mp4

ffmpeg -i dinesh_2024_single_particle_swelling_N_15_buoyancy_check.webm -vf "crop=trunc(iw/2)*2:trunc(ih/2)*2" dinesh_2024_single_particle_swelling_N_15_buoyancy_check.mp4

ffmpeg -i fifty_bodies_500_density_sph_representation.webm -vf "crop=trunc(iw/2)*2:trunc(ih/2)*2" fifty_bodies_500_density_sph_representation.gif

To make movies out of images png, such as simulations movies of PySPH

Documentation for Analyzing Particle Simulation Output Using HDF5

This section provides a step-by-step guide on how to analyze and visualize the output data from a particle simulation using HDF5 files. We will demonstrate how to load the results, process the data, and plot the variation of a specific quantity (in this case, the position of a particle) over time using Python libraries such as h5py and matplotlib.

	/****************************************************************************
	* Copyright (c) 2018-2022 by the Cabana authors *
	* All rights reserved. *
	* *
	* This file is part of the Cabana library. Cabana is distributed under a *
	* BSD 3-clause license. For the licensing terms see the LICENSE file in *
	* the top-level directory. *
	* *
	* SPDX-License-Identifier: BSD-3-Clause *
	****************************************************************************/

	# trace generated using paraview version 5.11.1
	#import paraview
	#paraview.compatibility.major = 5
	#paraview.compatibility.minor = 11

	#### import the simple module from the paraview
	from paraview.simple import *

	import os, sys
	#### disable automatic camera reset on 'Show'

	/****************************************************************************
	* Copyright (c) 2018-2022 by the Cabana authors *
	* All rights reserved. *
	* *
	* This file is part of the Cabana library. Cabana is distributed under a *
	* BSD 3-clause license. For the licensing terms see the LICENSE file in *
	* the top-level directory. *
	* *
	* SPDX-License-Identifier: BSD-3-Clause *
	****************************************************************************/

	https://gitlab.com/pypr/adaptive_sph/-/blob/master/code/fpc_auto.py#L795

	https://gitlab.com/pypr/adaptive_sph/-/blob/master/code/fpc_auto.py#L435