The NVIDIA® CUDA® Toolkit provides a comprehensive development environment for C and C++ developers building GPU-accelerated applications. The CUDA Toolkit includes a compiler for NVIDIA GPUs, math libraries, and tools for debugging and optimizing the performance of your applications. You’ll also find programming guides, user manuals, API reference, and other documentation to help you get started quickly accelerating your application with GPUs.
Dramatically simplify parallel programming*New* 64-bit ARM Support
- Develop or recompile your applications to run on 64-bit ARM systems with NVIDIA GPUs.
- Enabling applications to access CPU and GPU memory without the need to manually copy data learn more.
- Automatically accelerate applications’ BLAS and FFTW calculations.
- Use cuFFT callbacks for higher performance.
- cublasXT - a new BLAS GPU library that automatically scales performance across up to 8 GPUs in a single node, and supporting larger workloads. The re-designed FFT GPU library scales up to 2 GPUs in a single node, allowing larger transform sizes and higher throughput.
- Support for Microsoft Visual Studio 2013
- Improved debugging for CUDA FORTRAN
- Replay feature in Visual Profiler and nvprof
- nvprune utiliy to optimize the size of object files
Productivity and Performance ImprovementsC++11 support makes it easier for C++ developers to accelerate their applications
- Write less code with ‘auto’ and ‘lambda’, especially when using the Thrust template library.
- Significant acceleration for Computer Vision, CFD, Computational Chemistry, and Linear Optimization applications.
- Key LAPACK dense solvers 3-6x faster than MKL.
- Dense solvers include Cholesky, LU, SVD and QR
- Sparse direct solvers 2-14x faster than CPU-only equivalents.
- Sparse solvers include direct solvers and eigensolvers
- Improve performance by removing conditional logic and only evaluating special cases when necessary.
Learn more about the GPU-accelerated libraries and development tools included in the CUDA Toolkit
If you develop applications in languages other than C or C++, please review the Getting Started Page for a language solution that meets your needs. The CUDA Toolkit complements and fully supports programming with OpenACC directives.
The latest version of the CUDA Toolkit is always available at www.nvidia.com/getcuda
NVIDIA GPU Computing Registered Developers get early access to the next CUDA Toolkit release, and access to NVIDIA’s online bug reporting and feature request system.