Accelerating Python using the GPU is much easier than you might think. We will explore the powerful CUDA-enabled Python ecosystem in this tutorial through hands-on examples using some of the most popular accelerated scientific computing libraries.

Topics include: - Introduction to General Purpose GPU Computing - GPU vs CPU - Which processor is best for which tasks - Introduction to CUDA - How to use CUDA with Python - Using Numba to write kernel functions - CuPy - cuDF

No prior experience with GPU's is necessary, but attendees should be familiar with Python.