NVIDIA CUDA Toolkit
The NVIDIA® CUDA® Toolkit provides a development environment for creating high-performance, GPU-accelerated applications. With it, you can develop, optimize, and deploy your applications on GPU-accelerated embedded systems, desktop workstations, enterprise data centers, cloud-based platforms, and supercomputers. The toolkit includes GPU-accelerated libraries, debugging and optimization tools, a C/C++ compiler, and a runtime library.
The Features of CUDA 13.1
CUDA Tile: A New Era of GPU Programming
NVIDIA CUDA Tile is a tile-based GPU programming model based on the foundation of the CUDA Tile IR specification and tools including cuTile.
Learn More About CUDA Tile
New Release, New Benefits
CUDA Toolkit 13.1, now available for general use, introduces CUDA Tile—a tile-based programming model—green contexts in the runtime API, MPS enhancements, and developer tool updates.
Learn More About CUDA Toolkit 13.1
Tile Programming in Python
cuTile Python is an expression of the CUDA Tile programming model in Python. It is built on top of the CUDA Tile IR specification and allows you to write tile kernels in Python.
Learn More About cuTile Python
Tutorials
Explore essential video tutorials covering CUDA Toolkit installation on Windows and WSL, ensuring compatibility, upgrading Jetson™ devices, and optimizing applications through profiling and debugging.
Accelerating Applications With Parallel Algorithms | CUDA C++
Watch Video (2:05:26)CUDA Upgrades for Jetson Devices
Watch Video (19:05)Profiling and Debugging Applications
Watch Video (10:30)Installing CUDA Toolkit on Windows and WSL
Watch Video (2:56)GTC Digital Webinars
Dive deeper into the latest CUDA features.
What’s CUDA All About Anyway?
Learn about the CUDA ecosystem that helps developers solve real-world challenges.
Watch NowCUDA—New Features and Beyond
Learn what's new in the CUDA Toolkit, including the latest and greatest features in the CUDA language, compiler, libraries, and tools—and get a sneak peek at what's coming up over the next year.
Watch Now
How to Write a CUDA Program: The Parallel Programming Edition
Learn more about how to write CUDA programs.
Watch NowCustomer Stories
See how developers, scientists, and researchers are using CUDA today.
Using HPC to Explore the Universe
Wes Armour, director at the Oxford e-Research Centre, discusses the role of GPUs in processing large amounts of astronomical data collected by the Square Kilometre Array and how CUDA is the best-suited option for their signal processing software.
Watch Video (1:47)
Opening a New Era of Drug Discovery With Amber
David Cerutti and Taisung Lee from Rutgers University share how Amber, harnessing CUDA, is advancing multiple scientific domains and opening a new era of drug discovery and design.
Watch Video (2:02)
Visualizing and Simulating Atomic Structures
John Stone, senior research programmer at the Beckman Institute at the University of Illinois, Urbana-Champaign, discusses how CUDA and GPUs are used to process large datasets to visualize and simulate high-resolution atomic structures.
Watch Video (2:15)
Free Tools and Trainings for Developers
Get exclusive access to hundreds of SDKs, technical trainings, and opportunities to connect with millions of like-minded developers, researchers, and students.
Learn More
Resources
CUDA Documentation and Release Notes
Documentation library containing in-depth technical information on the CUDA Toolkit.
Learn More About CUDA Toolkit 13.1
Accelerated Computing Hub
The Accelerated Computing Hub provides essential best practices, optimization guides, and developer tools to maximize the performance of your CUDA-accelerated applications.
Learn More About Accelerated Computing Hub
CUDA Toolkit in the NGC Catalog
CUDA containers are available to download from NGC™—along with other NVIDIA GPU-accelerated SDKs and AI models—to help accelerate your applications.
Learn More About CUDA Containers
CUDA Technical Blogs
An archive of CUDA technical blogs covering key features and capabilities, written by engineers for engineers.
Learn More About CUDA Tech Blogs
CUDA-X™ Libraries
A suite of AI, data science, and math libraries developed to help developers accelerate their applications.
Learn More About CUDA-X Libraries
Training
Self-paced or instructor-led CUDA training courses for developers through the NVIDIA Deep Learning Institute (DLI).
Learn More About Accelerated Computing - Training
Nsight Developer Tools
NVIDIA Nsight Compute and Nsight System suite of tools designed to help developers optimize and increase performance of their applications.
Learn More About Nsight Tools
Sample CUDA Code
GitHub repository of sample CUDA code to help developers learn and ramp up development of their GPU-accelerated applications.
Learn More About CUDA Samples
NVIDIA Developer Forums
An information exchange to help developers get answers to their technical questions directly from NVIDIA engineers.
Learn More About Developer Forums
Bug Submission
NVIDIA Engineering’s own bug tracking tool and database where developers can submit technical bugs.
Learn More About Bug Submission Tool