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.
Check out this in depth Parallel Forall, ProTips Blog: New Features in CUDA 7.5
CUDA 7.0 HighlightsC++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
New in CUDA 7.516-bit floating point (FP16) data format
- Store up to 2x larger datasets in GPU memory
- Reduce memory bandwidth requirements by up to 2x
- New mixed precision cublasSgemmEX() routine supports 2x larger matrices
- Optimized dense matrix x sparse vector routines - ideal for Natural Language Processing
- Quickly identify the specific lines of source code limiting the performance of GPU code
- Apply advanced performance optimizations more easily
The CUDA Toolkit 7.5 release candidate (RC) is now available for all developers.
Learn more about the GPU-accelerated libraries and development tools included in the CUDA Toolkit
- cuFFT – Fast Fourier Transforms Library
- cuBLAS – Complete BLAS library
- cuSolver – Collection of dense and sparse direct solvers
- cuSPARSE – Sparse Matrix library
- cuRAND – Random Number Generator
- NPP – Thousands of Performance Primitives for Image & Video Processing
- Thrust – Templated Parallel Algorithms & Data Structures
- CUDA Math Library – high performance math routines
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
CUDA Registered Developers get early access to the next CUDA Toolkit release, and access to NVIDIA’s online bug reporting and feature request system.