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Curious if you know how well Ray works with multithreaded python libraries? For example, when using jax with ray, I have to ensure the import ordering imports ray first, as forking a threaded process leads to deadlocks in Python. Do you know how to ensure that ray handles forking the python interpreter correctly?

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Multi-threaded libraries (e.g., numpy and PyTorch on CPUs come to mind) are well supported. In scenarios where many processes are each running heavily multi-threaded computations, it can help to pin specific processes to specific cores (e.g., using tools like psutil) to avoid contention.

The scenario where a Ray task forks is probably not very well supported. You can certainly start a subprocess from within a Ray task, but I think forking could easily cause issues.

You can definitely use Ray + Jax, but you probably need to avoid forking a process within a Ray worker.

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