Most scientific runs are scaled where you run multiple replicates. And not all scientific runs are high-performance in the HPC sense. Even if your code is HPC

Most scientific runs are scaled where you run multiple replicates. And not all scientific runs are high-performance in the HPC sense. Even if your code is HPC in the HPC sense, and requires CUDA, and 40,000 cores, you should consider creating a release flag where an end user can do at least single "slow" run on a CPU on a reduced dataset, in single threaded mode, to sanity check the results and at least verify that the computational and algorithmic pipeline is sound at the most basic level. I used to be a scientist. I get it, getting scientists to do this is like pulling teeth, but it's the least you could do to give other people confidence in your results.