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