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