This is the second part in a series of talks about using modern C++ for high-performance data science. In the first talk of the series (https://youtu.be/YPQUIkSIFhw), we covered Xeus-Cling (https://github.com/arminms/xeus-cling-jupyter) and G3P (https://github.com/arminms/g3p). In the second part, after some updates about xeus-cling-jupyter (e.g. support for C++20), we learn how to use a parallel random number library like Ranx (https://github.com/arminms/ranx), together with STL's algorithms and distributions, for generating random numbers. The whole series is available as an executable book (https://executablebooks.org) at https://arminms.github.io/high-performance-data-science-with-modern-cpp .
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This webinar was presented by Armin Sobhani (SHARCNET) on November 19th, 2025, as a part of a series of regular biweekly General Interest webinars ran by SHARCNET. The webinars cover different high performance computing (HPC) topics, are approximately 45 minutes in length, and are delivered by experts in the relevant fields. Further details can be found on this web page: https://helpwiki.sharcnet.ca/wiki/Online_Seminars .
SHARCNET is a consortium of 19 Canadian academic institutions who share a network of high performance computers (http://www.sharcnet.ca). SHARCNET is a part of Compute Ontario (http://computeontario.ca/) and Digital Research Alliance of Canada (https://alliancecan.ca).
