NVIDIA CUDA Toolkit

  



  1. Nvidia Cuda Toolkit Download
  2. Nvidia Cuda Toolkit V10
  3. Nvidia Cuda Toolkit 11

Release Notes The Release Notes for the CUDA Toolkit. EULA The CUDA Toolkit End User License Agreement applies to the NVIDIA CUDA Toolkit, the NVIDIA CUDA Samples, the NVIDIA Display Driver, NVIDIA Nsight tools (Visual Studio Edition), and the associated documentation on CUDA APIs, programming model and development tools.

Release Highlights

Easier Application Porting

  • GPUDirect RDMA is a technology introduced in Kepler-class GPUs and CUDA 5.0 that enables a direct path for data exchange between the GPU and a third-party peer device using standard features of PCI Express.
  • The CUDA Toolkit from NVIDIA provides everything you need to develop GPU-accelerated applications. The CUDA Toolkit includes GPU-accelerated libraries, a compiler, development tools and the CUDA runtime. The CUDA container images provide an easy-to-use distribution for CUDA supported platforms and architectures. End User License Agreements.
  • Cuda website CUDA™ is a parallel computing platform and programming model invented by NVIDIA. It enables dramatic increases in computing performance by harnessing the power of the graphics processing unit (GPU).
  • Share GPUs across multiple threads
  • Use all GPUs in the system concurrently from a single host thread
  • No-copy pinning of system memory, a faster alternative to cudaMallocHost()
  • C++ new/delete and support for virtual functions
  • Support for inline PTX assembly
  • Thrust library of templated performance primitives such as sort, reduce, etc.
  • NVIDIA Performance Primitives (NPP) library for image/video processing
  • Layered Textures for working with same size/format textures at larger sizes and higher performance

Faster Multi-GPU Programming

  • Unified Virtual Addressing
  • GPUDirect v2.0 support for Peer-to-Peer Communication

New & Improved Developer Tools

  • Automated Performance Analysis in Visual Profiler
  • C++ debugging in CUDA-GDB for Linux and MacOS
  • GPU binary disassembler for Fermi architecture (cuobjdump)
  • Parallel Nsight 2.0 now available for Windows developers with new debugging and profiling features.

Watch the CUDA Toolkit 4.0 Feature and Overview Webinar (or just the slides) for an overview of some of the exciting new features of this release.
Check out the NEW CUDA 4.0 Math Library Performance Review

Find all the latest versions of other Libraries and Tools on our Tools & EcoSystem Page

CUDA

Please download the lastest CUDA Toolkit 4.0 Errata Update.

The latest released NVIDIA Drivers are always available at www.nvidia.com/drivers
For previous releases, see the CUDA Toolkit Release Archive
Get yourself fully trained- check out the latest CUDA Webinars
Become a CUDA Registered Developer, report bugs, engage with NVIDIA engineering
Jump to: [Windows][ Linux ] [ MacOS ]

Nvidia cuda toolkit 10.1

Nvidia Cuda Toolkit Download

Windows 7, VISTA, Windows XPDownloads
Developer Drivers for WinXP (270.81)
Support for XP on notebooks is being phased out and is not available for this release. See Release Notes and Getting Started Guides for more information.
Developer Drivers for WinVista and Win7 (270.81)
Notebook Developer Drivers for WinVista and Win7 (275.33)
CUDA Toolkit
  • C/C++ compiler
  • Visual Profiler
  • GPU-accelerated BLAS library
  • GPU-accelerated FFT library
  • GPU-accelerated Sparse Matrix library
  • GPU-accelerated RNG library
  • Additional tools and documentation
*NEW* CUDA Toolkit 4.0 Build Customization BUG FIX Update
Fixes error message '$(CUDABuildTasksPath) property is not valid'
download
GPU Computing SDK - complete package including all code samples32-bit64-bit
browse online
Parallel Nsight 2.0 download
Learn about additional tools, libraries, and more…CUDA Ecosystem
CUDA Tools SDK (APIs for 3rd party performance analysis tools and cluster management solutions)
Cuda
LinuxDownloads
Developer Drivers for Linux (270.41.19)
CUDA Toolkit
  • C/C++ compiler
  • CUDA-GDB debugger
  • Visual Profiler
  • GPU-accelerated BLAS library
  • GPU-accelerated FFT library
  • GPU-accelerated Sparse Matrix library
  • GPU-accelerated RNG library
  • Additional tools and documentation
CUDA Toolkit for Fedora 1332-bit, (Visual Profiler_Patch)
64-bit, (Visual Profiler Patch)
CUDA Toolkit for RedHat Enterprise Linux 6.064-bit, (Visual Profiler Patch)
CUDA Toolkit for RedHat Enterprise Linux 5.532-bit, (Visual Profiler Patch)
64-bit, (Visual Profiler Patch)
CUDA Toolkit for RedHat Enterprise Linux 4.8
CUDA Toolkit for Ubuntu Linux 10.1032-bit, (Visual Profiler Patch)
64-bit, (Visual Profiler Patch)
CUDA Toolkit for OpenSUSE 11.232-bit, (Visual Profiler Patch)
64-bit, (VP Patch -coming soon)
CUDA Toolkit for SUSE Linux Enterprise Server 11 SP132-bit, (Visual Profiler Patch)
64-bit, (Visual Profiler Patch)
GPU Computing SDK - complete package including all code samplesdownload
browse online
Learn about additional tools, libraries, and more…CUDA Ecosystem
CUDA Tools SDK (APIs for 3rd party debuggers, performance analysis tools and cluster management solutions)
Mac OS XDownloads
Developer Drivers (4.0.50) for MacOS (requires OS ver. 10.6.8 or higher)download
CUDA Toolkit (requires OS version 10.6.7 or higher)
  • C/C++ compiler
  • CUDA-GDB debugger
  • Visual Profiler
  • GPU-accelerated BLAS library
  • GPU-accelerated FFT library
  • GPU-accelerated Sparse Matrix library
  • GPU-accelerated RNG library
  • Additional tools and documentation
GPU Computing SDK - complete package including all code samplesdownload
Browse Online
Learn about additional tools, libraries, and more…CUDA Ecosystem
CUDA Tools SDK (APIs for 3rd party debuggers and performance analysis tools)download
8.0

Develop, Optimize and Deploy GPU-Accelerated Apps

The NVIDIA® CUDA® Toolkit provides a development environment for creating high performance GPU-accelerated applications. With the CUDA Toolkit, you can develop, optimize, and deploy your applications on GPU-accelerated embedded systems, desktop workstations, enterprise data centers, cloud-based platforms and HPC supercomputers. The toolkit includes GPU-accelerated libraries, debugging and optimization tools, a C/C++ compiler, and a runtime library to build and deploy your application on major architectures including x86, Arm and POWER.

Using built-in capabilities for distributing computations across multi-GPU configurations, scientists and researchers can develop applications that scale from single GPU workstations to cloud installations with thousands of GPUs.

Nvidia Cuda Toolkit V10



Cuda

CUDA 11 Features

Nvidia Cuda Toolkit 11

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