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
Built-In Capabilities for Easy Scaling
Using built-in capabilities for distributing computations across multi-GPU configurations, you can develop applications that scale from single-GPU workstations to cloud installations with thousands of GPUs.
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New Release, New Benefits
CUDA Toolkit 13.0, now available for general use, introduces foundational enhancements for a tile-based programming model, unification of the developer experience on Arm platforms, updates to NVIDIA Nsight™ developer tools, improvements in math libraries, NVCC compiler, and Accelerated Python.
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Support for NVIDIA Blackwell
Support for the NVIDIA Blackwell architecture includes next-generation Tensor Cores and Transformer Engine, the high-speed NVIDIA NVLink™ Switch, mixed-precision modes including support for FP4, and standard C++/Fortran/Python parallel language constructs.
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Tutorials
CUDA Developer Tools is a series of tutorial videos designed to get you started using NVIDIA Nsight™ tools for CUDA development. It explores key features for CUDA profiling, debugging, and optimizing.
CUDA Compatibility
Watch VideoCUDA Upgrades for Jetson Devices
Watch VideoProfiling and Debugging Applications
Watch VideoInstalling CUDA Toolkit on Windows and WSL
Watch VideoGTC 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.
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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.
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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.
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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.
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CUDA Ecosystem
Explore the top compute and graphics packages with built-in CUDA integration.
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.
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Resources
CUDA Documentation and Release Notes
Documentation library containing in-depth technical information on the CUDA Toolkit.
CUDA 13 Features Revealed
A technical blog on the CUDA Toolkit 13.0’s features and capabilities.
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.
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All CUDA Technical Blogs
An archive of CUDA technical blogs covering key features and capabilities, written by engineers for engineers.
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CUDA-X™ Libraries
A suite of AI, data science, and math libraries developed to help developers accelerate their applications.
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Training
Self-paced or instructor-led CUDA training courses for developers through the NVIDIA Deep Learning Institute (DLI).
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Nsight Developer Tools
NVIDIA Nsight Compute and Nsight System suite of tools designed to help developers optimize and increase performance of their applications.
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Sample CUDA Code
GitHub repository of sample CUDA code to help developers learn and ramp up development of their GPU-accelerated applications.
NVIDIA Developer Forums
An information exchange to help developers get answers to their technical questions directly from NVIDIA engineers.
Bug Submission
NVIDIA Engineering’s own bug tracking tool and database where developers can submit technical bugs.
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