NVIDIA Fundamentals of Accelerated Computing with CUDA Python

The NVIDIA Deep Learning Institute (DLI) and Advanced Research Computing, University of Birmingham invite you to attend a hands-on CUDA Python workshop on Wednesday 11th March (09:00-17:00) at The University of Birmingham, exclusively for verifiable academic students, staff, and researchers.

NVIDIA DLI offers hands-on training for developers, data scientists, and researchers looking to solve challenging problems with deep learning and accelerated computing.

This workshop teaches you the fundamental tools and techniques for running GPU-accelerated Python applications using CUDA® GPUs and the Numba compiler.

At the conclusion of the workshop, you’ll have an understanding of the fundamental tools and techniques for GPU-accelerated Python applications with CUDA and Numba:

• GPU-accelerate NumPy ufuncs with a few lines of code.
• Configure code parallelization using the CUDA thread hierarchy.
• Write custom CUDA device kernels for maximum performance and flexibility.
• Use memory coalescing and on-device shared memory to increase CUDA kernel bandwidth.

Course Prerequisites:

• Basic Python competency, including familiarity with variable types, loops, conditional statements, functions, and array manipulations
• NumPy competency, including the use of ndarrays and ufuncs
• No previous knowledge of CUDA programming is required

Please note that our courses are for research staff and research students only. Taught students - undergraduate and postgraduate - are not eligible to attend.

Workshop Setup Instructions:

Will be provided by email to attendees. This workshop is brought to you by: