The GPU Computing SDK includes 100+ code samples, utilities, whitepapers, and additional documentation to help you get started developing, porting, and optimizing your applications for the CUDA architecture. You can get quick access to many of the SDK resources on this page, SDK documentation, or download the complete SDK.
Please note that you may need to install the latest NVIDIA drivers and CUDA Toolkit to compile and run the code samples.Refer to the SDK release notes for more information.
There are several sets of code samples included in the GPU Computing SDK download packages, please follow the links to browse the other examples:
- CUDA C/C++ Code Samples
- DirectCompute Code Samples
- CUDA Library Samples<<
- CUDA Toolkit & SDK Documentation
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 MersenneTwisterGP11213This sample demonstrates the Mersenne Twister random number generator GP11213 in cuRAND. |
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GrabCut with NPP CUDA Implementation of Rother et al. GrabCut approach using the 8 neighborhood NPP Graphcut primitive introduced in CUDA 4.1. (C. Rother, V. Kolmogorov, A. Blake. GrabCut: Interactive Foreground Extraction using Iterated Graph Cuts. ACM Transactions on Graphics (SIGGRAPH'04), 2004) |
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Download - Windows (x86) |
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Histogram Equalization with NPP This SDK sample demonstrates how to use NPP for histogram equalization for image data. |
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Download - Windows (x86) |
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FreeImage and NPP Interopability A simple SDK sample demonstrate how to use FreeImage library with NPP. |
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Download - Windows (x86) |
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Box Filter with NPP A NPP SDK sample that demonstrates how to use NPP FilterBox function to perform a Box Filter. |
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Download - Windows (x86) |
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Image Segmentation using Graphcuts with NPP This sample that demonstrates how to perform image segmentation using the NPP GraphCut function. |
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Download - Windows (x86) |
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Preconditioned Conjugate Gradient This sample implements a preconditioned conjugate gradient solver on GPU using CUBLAS and CUSPARSE library. |
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Download - Windows (x86) |
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CUDA C Monte Carlo: Single Asian Option This sample uses Monte Carlo to simulate Single Asian Options using the NVIDIA CURAND library. |
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Download - Windows (x86) |
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CUDA C Monte Carlo Estimation of Pi (batch QRNG) This sample uses Monte Carlo simulation for Estimation of Pi (using batch QRNG). This sample also uses the NVIDIA CURAND library. |
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Download - Windows (x86) |
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CUDA C Monte Carlo Estimation of Pi (batch PRNG) This sample uses Monte Carlo simulation for Estimation of Pi (using batch PRNG). This sample also uses the NVIDIA CURAND library. |
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Download - Windows (x86) |
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CUDA C Monte Carlo Estimation of Pi (batch inline QRNG) This sample uses Monte Carlo simulation for Estimation of Pi (using batch inline QRNG). This sample also uses the NVIDIA CURAND library. |
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Download - Windows (x86) |
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CUDA C Monte Carlo Estimation of Pi (inline PRNG) This sample uses Monte Carlo simulation for Estimation of Pi (using inline PRNG). This sample also uses the NVIDIA CURAND library. |
or later
Download - Windows (x86) |
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CUDA C Random Fog This sample illustrates pseudo- and quasi- random numbers produced by CURAND. |
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Download - Windows (x86) |
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ConjugateGradient This sample implements a conjugate gradient solver on GPU using CUBLAS and CUSPARSE library. |
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Download - Windows (x86) |
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batchCUBLAS A SDK sample that demonstrates how using batched CUBLAS API calls to improve overall performance. |
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Download - Windows (x86) |
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Simple CUBLAS Example of using CUBLAS using the new CUBLAS API interface available in CUDA 4.0. |
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Download - Windows (x86) |
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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 (x86) |
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