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One thing to think about here is using more GPU node time than we need to. For NDLAr, larnd-sim needs the 80 GB NERSC nodes and the conversion step takes O (~ few hours) for each 10^16 POT (on CPU node). It's probably good practise to only rely on these 80 GB nodes only when we need to. If we put the conversion step in the larnd-sim grid script that's increasing the amount of time we are using the GPU nodes quite a bit.
The script run-convert2h5/convert_edepsim_roottoh5.py should be moved into larnd-sim. It is producing input h5 files especially formatted to work with larnd-sim and is therefore more appropriate there.
Then the entire run-convert2h5 could be removed and the conversion can happen at the beginning of the run-larnd-sim/run_larnd_sim.sh script.
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