Booking required
Booking deadline: Wednesday 28 August 2019

This course explores how to use Numba—the just-in-time, type-specializing Python function compiler—to accelerate Python programs to run on massively parallel NVIDIA GPUs.

You’ll learn how to::

Use Numba to compile CUDA kernels from NumPy universal functions (ufuncs)
Use Numba to create and launch custom CUDA kernels
Apply key GPU memory management techniques

Upon completion, you’ll be able to use Numba to compile and launch CUDA kernels to accelerate your Python applications on NVIDIA GPUs.

This workshop is fully hands-on with multiple coding exercises, thus previous Python experience would be beneficial. However, CUDA is covered entirely by the material; attendees that have never used CUDA before will gain everything required to be immediately productive with CUDA Python, while more experienced CUDA developers will have an opportunity to focus on and experiment with the more advanced features that maximize performance.

Seating is limited to 40 and prior registration is required by NVIDIA to reserve sufficient hardware resources in their cloud. Please reserve your place by Wednesday, August 28. Lunch will not be provided.

The workshop will be given by Dr Georgios Varisteas, Research Associate in the SEDAN Research Group, and a certified NVIDIA DLI instructor.

Photography

Please note that a photographer will be present at this event. The images may be published by the University, e.g. on its social media, its website and in print products. If you do not wish to be photographed, please alert the organisers and the photographer.

Data processing policy

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Workshop - NVIDIA Fundamentals of Accelerated Computing with CUDA Python