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NVIDIA OpenCL SDK - Linear Algebra

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

Refer to the following README for related SDK information ( README )

The latest NVIDIA display drivers are required to run code samples. Please obtain the latest display driver here.

The NVIDIA CUDA Toolkit is required to compile code samples. Please obtain the CUDA Toolkit from CUDA Zone.

Select the category to view:

Select a category All Code Samples      Machine Vision      Linear Algebra      Machine vision      Imaging      Parallel Reduction      Infinite Response Filter      OpenCL Advanced Topics      CUDA Advanced Topics      Computer Vision      Data-Parallel Algorithms      Computational Finance      Graphics Interop      Image Processing      Performance Strategies      Image/Video Processing and Data Compression      OpenCL Basic Topics      OpenCL Topics      Physically-Based Simulation

OpenCL Vector Addition  Element by element addition of two 1-dimensional arrays. Implemented in OpenCL for CUDA GPU's, with functional comparison against a simple C++ host CPU implementation.		or later Download - Windows (x86) Download - Windows (x64) Download - Linux/Mac
OpenCL Dot Product  Dot Product (scalar product) of set of input vector pairs. Implemented in OpenCL for CUDA GPU's, with functional comparison against a simple C++ host CPU implementation.		or later Download - Windows (x86) Download - Windows (x64) Download - Linux/Mac
OpenCL Matrix Vector Multiplication  Simple matrix-vector multiplication example showing increasingly optimized implementations.		or later Download - Windows (x86) Download - Windows (x64) Download - Linux/Mac
OpenCL Matrix Transpose  Efficient matrix transpose.		or later Download - Windows (x86) Download - Windows (x64) Download - Linux/Mac
OpenCL Matrix Multiplication  This sample implements matrix multiplication and is exactly the same as Chapter 6 of the programming guide. It has been written for clarity of exposition to illustrate various OpenCL programming principles, not with the goal of providing the most performant generic kernel for matrix multiplication. CUBLAS provides high-performance matrix multiplication.		or later Download - Windows (x86) Download - Windows (x64) Download - Linux/Mac
OpenCL Separable Convolution  This sample implements convolution filter of a 2D image with arbitrary separable kernel.		or later Download - Windows (x86) Download - Windows (x64) Download - Linux/Mac

Last Update: 2/28/2010