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 12
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.
New Release, New Benefits
CUDA 12 introduces support for the NVIDIA Hopper™ and Ada Lovelace architectures, Arm® server processors, lazy module and kernel loading, revamped dynamic parallelism APIs, enhancements to the CUDA graphs API, performance-optimized libraries, and new developer tool capabilities.
Support for Hopper
Support for the Hopper architecture includes next-generation Tensor Cores and Transformer Engine, the high-speed NVIDIA NVLink® Switch, mixed-precision modes, second-generation Multi-Instance GPU (MIG), advanced memory management, and standard C++/Fortran/Python parallel language constructs.
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.
GTC Digital Webinars
Dive deeper into the latest CUDA features.
Inside the NVIDIA Hopper Architecture
Explore what's new with the NVIDIA Hopper architecture and its implementation in the NVIDIA H100 Tensor Core GPU.Watch Now
CUDA—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.
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.
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.
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.
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.
CUDA Documentation and Release Notes
Documentation library containing in-depth technical information on the CUDA Toolkit.
CUDA 12 Features Revealed
A technical blog on the CUDA Toolkit 12.0’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.
All CUDA Technical Blogs
An archive of CUDA technical blogs covering key features and capabilities, written by engineers for engineers.
A suite of AI, data science, and math libraries developed to help developers accelerate their applications.
Self-paced or instructor-led CUDA training courses for developers through the NVIDIA Deep Learning Institute (DLI).
Nsight Developer Tools
NVIDIA Nsight Compute and Nsight System suite of tools designed to help developers optimize and increase performance of their applications.
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.
NVIDIA Engineering’s own bug tracking tool and database where developers can submit technical bugs.