GPU Programming with CUDA and Python Training Course

Course Code

cudapython

Duration

14 hours (usually 2 days including breaks)

Requirements

  • Python programming experience
  • Experience with NumPy (ndarrays, ufuncs, etc.)

Audience

  • Developers

Overview

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

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