# 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
```