Welcome to the repository for the "Fundamentals of Accelerated Computing with CUDA Python" course by NVIDIA Deep Learning Institute (DLI).
The "Fundamentals of Accelerated Computing with CUDA Python" course is designed to introduce you to the fundamentals of parallel programming using CUDA Python, a powerful framework for harnessing the computational power of NVIDIA GPUs. Whether you're a beginner or an experienced developer, this course will equip you with the knowledge and skills to accelerate your Python applications using GPU parallelism.
Key topics covered in this course include:
- GPU architecture fundamentals
- CUDA programming basics
- Parallelism and thread management
- Memory management and optimization
- Performance tuning techniques
This repository contains assessments and exercises from the course, helping you practice and reinforce what you've learned.
This GitHub repository serves as a central location for all the assessments and exercises related to the "Fundamentals of Accelerated Computing with CUDA Python" course. It includes hands-on coding assignments and practical exercises to help you gain hands-on experience in GPU programming using CUDA Python.
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Assessments: This directory contains the assessment exercises provided as part of the course. You can use these to test your understanding and practice your skills.
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Exercises: In this directory, you'll find additional coding exercises and examples to further enhance your knowledge of CUDA Python programming.
To get started with the course materials and exercises, clone this repository to your local machine. You can then navigate to the specific directories for assessments or exercises and follow the instructions provided in the course materials.
Before diving into this course, it's recommended that you have a basic understanding of Python programming. Familiarity with GPU concepts and CUDA will be helpful but is not required.
We hope you find this repository and the course materials valuable for learning and mastering CUDA Python programming. Feel free to contribute, ask questions, or provide feedback through issues and pull requests.
Happy coding!