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Tricks for Efficient Multicore Computing

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Tricks for Efficient Multicore Computing
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43
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CC Attribution 3.0 Unported:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
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Production PlaceErlangen, Germany

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In this presentation you will learn about: - The concurrent.futures API of Python 3 - Threads vs forked processes vs spawned processes (pros and cons) - The impact of the GIL on CPU-bound Python programs - Bad interactions of fork-based multiprocessing and OpenMP runtimes - BLAS-based parallelism (e.g. MKL, OpenBLAS) - Memory bandwidth bound operations, arithmetic intensity and the roofline model.