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PyHEP 2020 TensorFlow2 and zfit
High performance computing in Python
PyHEP 2020 Python GPU Libraries
PyHEP 2021: Uproot and Awkward Array tutorial
High Performance Python II
High Performance Python I
PyHEP 2020 iminuit
PyHEP 2020 Nanoevents Demo
Video of the course High-Performance Computing with Python - 1
PyHEP 2020 Boost-Histogram
Efficient Python for High Performance Parallel Computing | SciPy 2015 Tutorial | Mike McKerns
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Last Updated: October 17, 2026
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Henry Schreiner gives a tutorial for This hands-on workshop will teach you how to profile and optimize The main uproot developer, Jim Pivarski, walks thought a tutorial and answers many questions as part of the Enric Tejedor and Stefan Wunsch describe the new PyROOT that is the default for ROOT 6.22, with a talk and examples. Part of ... Jonas Eschle discusses the opportunities afforded by TensorFlow2 and how they will be used by zfit. Part of the Software requirements: opengeohub/py-geo docker image (gdal, rasterio, geopandas, eumap). Open Data Science Europe ... Adrian Oeftiger shows how to use GPU binding libraries for Uproot provides an easy way to get data from ROOT files into arrays and DataFrames, and Awkward Array lets you manipulate ... Travis Oliphant In this tutorial, I will cover how to write very fast Ian Ozsvald At EuroPython 2011 I ran a very hands-on tutorial for Hans Dembinski looks at the past and future of the iminuit package during the CSCS organized an online course on " Henry Schreiner and Hans Dembinski look at the boost-histogram package during the ... there's a lot of strategies for for then accelerating the uh the code to to parallel and