Techniques Employed to Accelerate NumPy & SciPy in Intel® Distribution for Python | Intel Software

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Get high performance Python at your fingertips with the free Intel® Distribution for Python, and experience significant speedups for NumPy and SciPy with the Intel® Math Kernel Library (Intel® MKL). NumPy and SciPy are at the heart of scientific computing with Python. Oleksandr will spotlight the key areas and functionality in these Intel optimized packages for Fast Fourier Transforms (FFTs), Arithmetic & Transcendental (umath) functions and Memory optimizations, that deliver out-of-the-box performance speedups. Learn about Intel® MKL – a powerful performance library for numerical computing, and how it accelerates NumPy and SciPy, and ways to use it directly from the Intel® Distribution for Python.

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Intel® Distribution for Python* 2017 Update 2 Accelerates Five Key Areas for Impressive Performance Gains: http://intel.ly/2sv0Ry9

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