Python is a very popular programming language for scientific computing, but since Python programs are interpreted, they are inherently slower than equivalent code written in compiled languages. A wide variety of packages, tools, and strategies have been developed over the years to overcome this limitation, to support both the development of hybrid codes that combine interpreted and compiled pieces, and the construction of parallel codes that leverage multiple computing resources concurrently. This 30-minute webinar followed by Q & A will provide an overview of some of these approaches, to help point users toward different solutions that might work best for their particular codes. The webinar is intended as an introduction and complement to online training materials in the Cornell Virtual Workshop that address these issues in greater detail (https://cvw.cac.cornell.edu/python), and will be delivered in a Jupyter notebook that is available in an accompanying repository (https://github.com/CornellCAC/CVW_PyHP). This webinar was first delivered on 5/28/2020, offered again due to oversubscription.

This webinar will use the Zoom conferencing system. Registrants will receive connection details via email one day prior to the event.