NVIDIA Accelerated Computing Hub

This repository is a home for open learning materials related to GPU computing. You will find user guides, tutorials, and other works freely available for all learners interested in GPU computing.

The intention is to create a living project where documents, examples, best practices, optimizations, and new features can become both visible and accessible to users quickly and easily.

Tutorials and Syllabi

The following interactive tutorials are available and can be used on NVIDIA Brev or Google Colab. See the documentation for more information on creating and deploying Brev Launchables using this content.

Content	Docker Compose	Brev Instance	Brev Provider
CUDA Tile Tutorial	docker-compose.yml	1xB300, 1xB200, or 1xRTXPro6000	Any Blackwell provider; none have Flexible Ports yet
CUDA C++ Tutorial	docker-compose.yml	L40S, L4, or T4	Crusoe or any other with Flexible Ports
Standard Parallelism Tutorial	docker-compose.yml	4xL4, 2xL4, 2xL40S, or 1x L40S	GCP, AWS, or any other with Flexible Ports and Linux 6.1.24+, 6.2.11+, or 6.3+ (for HMM)
Accelerated Python Tutorial	docker-compose.yml	L40S, L4, or T4; 4xL4 or 2xL4 for distributed	Crusoe or any other with Flexible Ports
nvmath-python Tutorial	docker-compose.yml	4xL4, 2xL4, 2xL40S, or 1x L40S	Crusoe or any other with Flexible Ports
CUDA Python Tutorial - CuPy, cuDF, CCCL, & Kernels - 8 Hours	docker-compose.yml	L40S, L4, or T4	Crusoe or any other with Flexible Ports
CUDA Python Tutorial - cuda.core & CCCL - 2 Hours	docker-compose.yml	L40S, L4, or T4	Crusoe or any other with Flexible Ports
PyHPC Tutorial - NumPy, CuPy, & mpi4py - 4 Hours	docker-compose.yml	4xL4, 2xL4, 2xL40S, or 1x L40S	Crusoe or any other with Flexible Ports
GPU Deployment Tutorial

License

All written materials (user guides, documentation, presentations) are subject to Creative Commons CC BY-NC-SA 4.0.

All codes (notebook code, coding examples) are subject to Apache License, Version 2.0.

Contact

For additional help, please use NVIDIA's CUDA Developer Forums.