GPU-Accelerated Computing with Python
February 22, 2022
2:00 PM - 4:00 PM
Calendar
Download iCal FileDescription
Python is the Lingua Franca of Data today and is being increasingly used in scientific computations. This workshop introduces Python GPU tools for porting and writing code that runs on GPUs. The primary tools, Numba and CuPy, are presented with examples. A Jupyter notebook is used along with a set of lecture slides.
Numba—a Python compiler from Anaconda that can compile Python code for execution on CUDA®-capable GPUs—provides Python developers with an easy entry into GPU-accelerated computing and for using increasingly sophisticated CUDA code with a minimum of new syntax and jargon. With CUDA Python and Numba, you get the best of both worlds: rapid iterative development with Python combined with the speed of a compiled language targeting both CPUs and NVIDIA GPUs.
CuPy is an open-source array library for GPU-accelerated computing with Python. Most operations perform well on a GPU using CuPy out of the box. CuPy speeds up some operations more than 100X.
This workshop speaker will be Kristopher Keipert, senior solutions architect at NVIDIA.
Registration
Registration for this training is closed.
Date posted
Jan 20, 2022
Date updated
Feb 22, 2022