NVIDIA CUDA SDK - Image/Video Processing and Data Compression

The CUDA Developer SDK provides examples with source code, utilities, and white papers to help you get started writing software with CUDA. The SDK includes dozens of code samples covering a wide range of applications including:

Simple techniques such as C++ code integration and efficient loading of custom datatypes
How-To examples covering CUDA BLAS and FFT libraries, texture fetching in CUDA, and CUDA interoperation with the OpenGL and Direct3D graphics APIS
Linear algebra primitives such as matrix transpose and matrix-matrix multiplication
Data-parallel algorithms such as parallel prefix sum of large arrays
Performance: profiling using timers and bandwidth tests
Advanced application examples such as image convolution, Black-Scholes options pricing and binomial options pricing

Refer to the following READMEs for more information ( Linux , Windows )

This code is released free of charge for use in derivative works, whether academic, commercial, or personal. (Full License)

The NVIDIA CUDA Toolkit is required to run and compile code samples. Please obtain the CUDA Toolkit here

Quick Links:

Data-Parallel Algorithms	Computational Finance
Performance Strategies	Linear Algebra
Physically-Based Simulation	CUDA Basic Topics
Graphics Interop	Image/Video Processing and Data Compression
CUDA Advanced Topics


256-bin Histogram This sample demonstrates efficient implementation of 256-bin histogram.		or later Whitepaper Download - Windows Download - Linux


64-bin Histogram This sample demonstrates efficient implementation of 64-bin histogram.		or later Whitepaper Download - Windows Download - Linux


Separable Convolution This sample implements a separable convolution filter of a 2D signal with a gaussian kernel.		or later Whitepaper Download - Windows Download - Linux


Texture-based Separable Convolution Texture-based implementation of a separable 2D convolution with a gaussian kernel. Used for performance comparison against convolutionSeparable.		or later Download - Windows Download - Linux


FFT-Based 2D Convolution This sample demonstrates how 2D convolutions with very large kernel sizes can be efficiently implemented using FFT transformations.		or later Whitepaper Download - Windows Download - Linux


Image denoising This sample demonstrates two adaptive image denoising technqiues: KNN and NLM, based on computation of both geometric and color distance between texels. While both techniques are implemented in the DirectX SDK using shaders, massively speeded up variation of the latter techique, taking advantage of shared memory, is implemented in addition to DirectX counterparts.		or later Whitepaper Download - Windows Download - Linux


DirectX Texture Compressor (DXTC) High Quality DXT Compression using CUDA. This example shows how to implement an existing computationally-intensive CPU compression algorithm in parallel on the GPU, and obtain an order of magnitude performance improvement.		or later Whitepaper Download - Windows Download - Linux


Post-Process in OpenGL This sample shows how to post-process an image rendered in OpenGL using CUDA.		or later Download - Windows Download - Linux


Box Filter Fast image box filter using CUDA with OpenGL rendering.		or later Download - Windows Download - Linux


Fast Walsh Transform Naturally(Hadamard)-ordered Fast Walsh Tranform for batched vectors of arbitrary eligible(power of two) lengths		or later Download - Windows Download - Linux


Sobel Filter This sample implements the Sobel edge detection filter for 8-bit monochrome images.		or later Download - Windows Download - Linux


Simple Texture (Driver Version) Simple example that demonstrates use of textures in CUDA using the driver API.		or later Download - Windows Download - Linux


Simple Texture Simple example that demonstrates use of textures in CUDA.		or later Download - Windows Download - Linux


Simple CUFFT Example of using CUFFT. In this example, CUFFT is used to compute the 1D-convolution of some signal with some filter by transforming both into frequency domain, multiplying them together, and transforming the signal back to time domain.		or later Download - Windows Download - Linux


1D Discrete Haar Wavelet Decomposition Discrete Haar wavelet decomposition for 1D signals with a length which is a power of 2.		or later Download - Windows Download - Linux