Python NumPy and SciPy In Multithreading

Python is a strong language, particularly for developing AI and machine learning applications

Python libraries called NumPy and SciPy were created especially for scientific computing and numerical processing, respectively

An efficient math library like the Intel oneAPI Math Kernel Library helps speed Python modules like NumPy and SciPy for data-parallelism

Thus, nested parallelism is formed, where a parallel portion calls a function that calls another parallel region

Despite enabling substantial mathematical and data-focused C-extension accelerations, NumPy and SciPy remain a fixed set of mathematical tools

It supports a variety of threading runtimes, including workqueue, OpenMP, and Intel oneAPI Threading Building Blocks (oneTBB)

OneTBB is an open-source, cross-platform C++ library that was created with threading composability and optional/nested parallelism in mind

Threading composability is more readily attained when oneTBB is used as the work scheduler

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