refactor!: drop Landau (GPL)

[henryiii]

Dropping GPL code in this branch. Checking CI.

Commands on Della (outside of Della, any computer with CUDA 11+ and CMake 3.18+ should be fine. If you don't have CMake, add pip install cmake right after the environment activation):

ml cudatoolkit/11.6

# If Minuit is not installed, it needs to be built and installed
git clone https://github.com/root-project/root --branch=v6-26-02
cmake -Sroot/math/minuit2 -Bbuild-minuit2 -DCMAKE_INSTALL_PREFIX=$HOME/minuit2
cmake --build build-minuit2
cmake --install build-minuit2

git clone https://github.com/GooFit/GooFit.git --branch=hackathon-2022 --recurse-submodules
cd GooFit
python3 -m venv .venv
source .venv/bin/activate
pip install -U pip setuptools wheel
pip install -r python/examples/requirements.txt
cmake -S. -Bbuild -DGOOFIT_DEVICE=CUDA -DMinuit2_ROOT=$HOME/minuit2 -DCMAKE_CUDA_ARCHITECTURES=80 -DGOOFIT_FORCE_LOCAL_THRUST=OFF

cmake --build build -j2
# run on a GPU node
cmake --build build -t test

SLURM: (click to expand)

#!/bin/bash
# GPU job

#SBATCH --job-name=goofit-job    # create a short name for your job
#SBATCH -o goofit.out            # Name of stdout output file (%j expands to jobId)
#SBATCH --nodes=1                # node count
#SBATCH --ntasks=1               # total number of tasks across all nodes
#SBATCH --cpus-per-task=1        # cpu-cores per task (>1 if multi-threaded tasks)
#SBATCH --gres=gpu:1             # number of gpus per node
#SBATCH --mem=4G                 # total memory (RAM) per node
#SBATCH --time=01:00:00          # total run time limit (HH:MM:SS)

module purge
module load cudatoolkit/11.6
source .venv/bin/activate

echo "Job $SLURM_JOB_ID execution at: `date`"

cmake --build build -t test

This should start up an interactive job:

salloc --nodes=1 --ntasks=1 --mem=4G --time=00:20:00 --gres=gpu:1

[JuanBSLeite]

The requirements.txt is inside python/examples folder.

pip install -r python/examples/requirements.txt