GPU programming: Speeding up Python code with Numba [online, PYT301]

Learn to accelerate your Python functions on CPU and GPU using Numba.
About this Event

Python isn't optimized for high-performance computing and can't be used “as is” on graphics processing units (GPUs). You can overcome these shortcomings by using one the Python just-in-time compilers such as Numba, which combines the ease of Python development with the power of a compiled language that targets both CPUs and GPUs.

In this workshop, you will gain insights into using Numba to accelerate your code on GPUs, to create simple GPU programs and to understand the core principles of GPU programming.

Registration

Academic participant: $10 (This rate applies to anyone studying, teaching or working at a university or CEGEP)
Non-academic participant: $200 (This rate applies to anyone who does not fit the academic profile)

➔ If you are not sure which rate is right for you, please contact us by e-mail at [email protected]

Prerequisites

PYT101 completion or understanding the basics of Python programming

Course plan

Why use GPUs for computing?
Understanding difference between CPU and GPU
Very short intro to CUDA

Instructor

Nikolaï Sergueev, analyst in advanced research computing at Calcul Québec.

Language

English

Technical prerequisites

We will use the Zoom platform. Because this event is a practical workshop, it is very useful having a secondary screen where you would get the instructor window on one screen and your own window on your main screen.

We will use the Jupyter Lab interface. Make sure you have a modern Web browser like Google Chrome, Firefox, Edge or Safari.

Notes

A certificate of participation will be send to each participant who attends at least 60% of the workshop.
The workshop is not recorded.
The workshop could be canceled if the number of registrations is too low.

Contact

For any question, please write to [email protected]