NVIDIA CUDA™ technology is the only C language environment that unlocks the processing power of GPUs to solve the most complex computation-intensive challenges. NVIDIA’s CUDA development tools are consisted of three key components to help you get started:

1. The latest CUDA driver
2. A complete CUDA toolkit
3. CUDA SDK code samples

The CUDA™ Toolkit is a C language development environment for CUDA-enabled GPUs. The CUDA development environment includes:

• nvcc C compiler
• CUDA FFT and BLAS libraries for the GPU
• Profiler
• gdb debugger for the GPU
• CUDA runtime driver (also available in the standard NVIDIA GPU driver)
• CUDA programming manual

The CUDA Developer SDK provides examples with source code to help you get started with CUDA. Examples include:

• Parallel bitonic sort
• Matrix multiplication
• Matrix transpose
• Performance profiling using timers
• Parallel prefix sum (scan) of large arrays
• Image convolution
• 1D DWT using Haar wavelet
• OpenGL and Direct3D graphics interoperation examples
• CUDA BLAS and FFT library usage examples
• CPU-GPU C- and C++-code integration
• Binomial Option Pricing
• Black-Scholes Option Pricing
• Monte-Carlo Option Pricing
• Parallel Mersenne Twister (random number generation)
• Parallel Histogram
• Image Denoising
• Sobel Edge Detection Filter
• MathWorks MATLAB® Plug-in (click here to download)

SDK code samples are available for download. Installation of the CUDA toolkit is required before running these precompiled examples.