Ignite the performance of common Python & Pandas constructs by using NumPy powered by oneAPI. This series will go into detail about how to apply key Intel architectural innovations and libraries via the smart application of NumPy techniques to achieve amazing performance gains.
We’ll delve into NumPy: aggregations, universal functions, broadcasting and fancy slicing, sorting, and other techniques powered by oneAPI. Learn how to achieve performance gains by replacing Python loop-centric or list comprehension applications with smarter equivalents that are more maintainable, more efficient, and much faster on current and future innovations in Intel hardware and oneAPI software libraries.
For more info, see: https://www.alcf.anl.gov/aurora-learning-paths-intel-ai-analytics-toolkit
- Bob Chesebrough, Intel Solution Architect
- Praveen Kundurthy, Intel Developer Evangelist
The virtual series is scheduled Wednesdays from 1:30 - 3:30 p.m. US Central.
- Module 1: May 17, 2023
Aggregations, universal functions, and broadcasting
- Module 2: June 14, 2023
- NumPy “where” and “select” to boost ndarray and Pandas “apply” constructs
- Module 3: July 12, 2023
Revisiting NumPy aggregations with the Data-parallel extension for Numba
Please see the Event Website linked below for a detailed Agenda of each Module.
If you do not already have an Intel DevCloud account, please visit this link to sign up prior to the first session.
Aurora Learning Paths: Accelerate Python Loops with the Intel AI Analytics Toolkit
Registration for this event is currently open.