NVIDIA Workshop 2021: Fundamentals of Accelerated Computing with CUDA Python
Nvidia Workshop Spring 2021: Fundamentals of Accelerated Computing with CUDA Python
Thursday, May 20, 2021
This course explored how to use Numba—the just-in-time, type-specializing Python function compiler—to accelerate Python programs to run on massively parallel NVIDIA GPUs. Participants learned 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, users were able to use Numba to compile and launch CUDA kernels to accelerate Python applications on NVIDIA GPUs.
- 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.
Hardware Requirements: Desktop or laptop computer capable of running the latest version of Chrome or Firefox. Each participant will be provided with dedicated access to a fully configured, GPU-accelerated server in the cloud.
For more info: Accelerated Computing with CUDA Python Workshop | NVIDIA
Workshop provided by Nvidia, Research Computing and UF Informatics Institute. Any questions, please contact Ying Zhang at firstname.lastname@example.org.