
256bin Histogram
This sample demonstrates efficient implementation of 256bin histogram. 

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64bin Histogram
This sample demonstrates efficient implementation of 64bin histogram. 

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Separable Convolution
This sample implements a separable convolution filter of a 2D signal with a gaussian kernel. 

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Texturebased Separable Convolution
Texturebased implementation of a separable 2D convolution with a gaussian kernel. Used for performance comparison against convolutionSeparable. 

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Bitonic Sort
Bitonic sort is a very simple parallel sorting algorithm that is very
efficient when sorting a small number of elements:
http://citeseer.ist.psu.edu/blelloch98experimental.html
This implementation is based on:
http://www.toolsofcomputing.com/tc/CS/Sorts/bitonic_sort.htm


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Line of Sight
This sample is an implementation of a simple lineofsight algorithm: Given a height map and a ray originating at some observation point, it computes all the points along the ray that are visible from the observation point. The implementation is based on the parallel scan primitive provided by the CUDPP library (http://www.gpgpu.org/developer/cudpp/). 

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NBody Simulation
This sample demonstrates efficient allpairs simulation of a gravitational nbody simulation in CUDA. This sample accompanies the GPU Gems 3 chapter "Fast NBody Simulation with CUDA". 

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Parallel Reduction
A parallel sum reduction that computes the sum of large arrays of values. This sample demonstrates several important optimization stratezies for parallel algorithms like reduction. 

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Mandelbrot
This sample uses CUDA to compute and display the Mandelbrot set interactively. It also illustrates the use of "double single" arithmetic to improve precision when zooming a long way into the pattern. Thanks to Mark Granger of NewTek who submitted this sample to the SDK! 

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Fast Walsh Transform
Naturally(Hadamard)ordered Fast Walsh Tranform for batched vectors of arbitrary eligible(power of two) lengths 

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Scan
This example demonstrates an efficient CUDA implementation of parallel prefix sum, also known as "scan". Given an array of numbers, scan computes a new array in which each element is the sum of all the elements before it in the input array. 

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Scan of Large Arrays
This example demonstrates an efficient CUDA implementation of parallel prefix sum (also known as "scan") for arbitrarysized arrays. Given an array of numbers, scan computes a new array in which each element is the sum of all the elements before it in the input array. 

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