GPU Programming with CUDA and Python Training Course
CUDA (Compute Unified Device Architecture) is a parallel computing platform and API created by Nvidia.
This instructor-led, live training (online or onsite) is aimed at developers who wish to use CUDA to build Python applications that run in parallel on NVIDIA GPUs.
By the end of this training, participants will be able to:
- Use the Numba compiler to accelerate Python applications running on NVIDIA GPUs.
- Create, compile and launch custom CUDA kernels.
- Manage GPU memory.
- Convert a CPU based application into a GPU-accelerated application.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Course Outline
Introduction
Overview of CUDA Features and Architecture
Setting up the Development Environment
Parallel Programming Fundamentals
Working with the Numba Compiler
Building a Custom CUDA Kernel
Troubleshooting
Summary and Conclusion
Requirements
- Python programming experience
- Experience with NumPy (ndarrays, ufuncs, etc.)
Audience
- Developers
Open Training Courses require 5+ participants.
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Testimonials (1)
Very interactive with various examples, with a good progression in complexity between the start and the end of the training.
Jenny - Andheo
Course - GPU Programming with CUDA and Python
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