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We show how to parallelize a loop using the multiprocessing and mpi4py. The setup allows to seamlessly switch between shared and distributed memory computing.

We collect resources and demonstrate parallelization with numba. Our focus lies on the analysis of nested parallelism and the working example is inspired by respy.

We show how to set up a main-child application. We use the example of uncertainty propagation using respy as the motivating use-case.

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