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Parallel Computing in Python using mpi4py Stephen Weston Yale Center for Research Computing Yale University June 2017. Parallel Computing modules There are many Python modules available that support Parallel Computing . See for a list, but a number of the projects appear to be dead. mpi4py multiprocessing jug Celery dispy Parallel Python Notes: multiprocessing included in the Python distribution since version Celery uses different transports/message brokers including RabbitMQ, Redis, Beanstalk IPython includes Parallel Computing support Cython supports use of OpenMP. S. Weston (Yale) Parallel Computing in Python using mpi4py June 2017 2 / 26. Multithreading support Python has supported multithreaded programming since version However, the C implementation of the Python interpreter (CPython) uses a Global Interpreter Lock (GIL) to synchronize the execution of threads.

S. Weston (Yale)Parallel Computing in Python using mpi4pyJune 2017 25 / 26. K-Means example: alternate ending Instead of sending all of the results to rank 0, we can perform an \allreduce" on the distortion values so that all of the workers know which worker has the best result. Then the winning worker can broadcast its centroids to everyone else.

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