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A path to multi(arbitrary)-precision, distributed scientific computation with Python3.
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kiwi_pycon_2016
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Next: 1 Brainstorm your own Artificial Neural Network in Python
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Author(s):
Boris Daszuta
Location
Conference 1
Date
sep Fri 09
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Start
15:30
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Duration
40:00
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16:10
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https://kiwi.pycon.org/schedule/presentation/138/
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On occasion scientific computations at double(quadruple) precision are simply not sufficient. In lieu of the usual NumPy and SciPy one can instead make use of mpmath or SymPy. For a 'large-scale' calculation one must appeal to parallelism and indeed distributed resources (eg. Dask-distributed). We describe a package that provides for library delegation based on calculation requirements at runtime.
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