From the course: Python: Programming Efficiently

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Introduction to parallel programming

Introduction to parallel programming - Python Tutorial

From the course: Python: Programming Efficiently

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Introduction to parallel programming

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Moore's law is no more CPU speed center and sister densities have stopped increasing exponentially as they head for several decades. Now competing speed increases by architectural improvements and by packing multiple computing cores inside the same CPU. This means that the program that takes full advantage of modern process source must be able to run in parallel or multiple course. Unfortunately, Python at least as implemented in the standard C Python interpreter was not designed to exploit parallelism natively C python does support running concurrent threads which shared the same code and the same variables. But this can never really be executed in parallel. When one is running, the others are suspended and that's because C Python has no other protection against objects being corrupted in memory where multiple threads modify them at the same time, compiled Python libraries. Typically those that do math can and will use…

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