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# FiniteVolumeGPU
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This is a HIP version of the [FiniteVolume code](#https://github.com/babrodtk/FiniteVolumeGPU) (work in progress). It is a Python software package that implements several finite volume discretizations on Cartesian grids for the shallow water equations and the Euler equations.
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## Setup
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A good place to start exploring this codebase is the notebooks. Complete the following steps to run the notebooks:
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1. Install conda (see e.g. Miniconda or Anaconda)
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2. Change directory to the repository root and run the following commands
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3. conda env create -f conda_environment.yml
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4. conda activate ShallowWaterGPU
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5. jupyter notebook
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Make sure you are running the correct kernel ("conda:ShallowWaterGPU"). If not, change kernel using the "Kernel"-menu in the notebook.
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If you do not need to run notebooks you may use the conda environment found in conda_environment_hpc.yml
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## Troubleshooting
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Have a look at the conda documentation and https://towardsdatascience.com/how-to-set-up-anaconda-and-jupyter-notebook-the-right-way-de3b7623ea4a
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## Setup on LUMI-G
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Here is a step-by-step guide on installing packages on LUMI-G
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### Step 0: load modules
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ml LUMI/23.03
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ml lumi-container-wrapper
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ml cray-python/3.9.13.1
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### Step 1: run conda-container
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Installation via conda can be done as:
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conda-containerize new --prefix MyCondaEnv conda_environment_lumi.yml
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where the file `conda_environment_lumi.yml` contains packages to be installed.
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### Step 2: Set the env. variable to search for binaries
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export the bin path: export PATH="$PWD/MyCondaEnv/bin:$PATH"
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### An alternative: Convert to a singularity container with cotainr
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cotainr build my_container.sif --system=lumi-g --conda-env=conda_environment_lumi.yml
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