Improving parallel MC use-case example #26
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On Windows one needs to use multiprocessing.Manager to create the barrier to be shared across workers, and passed to worker initialization routine as argument. Also passed batch_size to routines as keyword argument, and in parallel_mc.py passed mc_worker_func to worker initialization routine as keyword argument, which assigns to process-global variable for reuse by subsequent MC computation tasks.
samaid
approved these changes
Mar 22, 2023
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Very nice! I saw this paper too |
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This PR fixes the implementation to run on Windows following excellent article from super-fast-python.
It also updates
README.mddocument to identify which script to run to solve which problem, and providesample outputs.