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NVIDIA CUDA SDK - Linear Algebra



FFT Ocean Simulation For a direct link to this sample, right-click and copy the URL (shortcut) of this link icon.

This sample simulates an Ocean heightfield using CUFFT and renders the result using OpenGL.
  Minimum Required GPU
Minimum Required GPUor later
Minimum Required GPU




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Separable Convolution For a direct link to this sample, right-click and copy the URL (shortcut) of this link icon.

This sample implements a separable convolution filter of a 2D signal with a gaussian kernel.
  Minimum Required GPU
Minimum Required GPUor later
Minimum Required GPU



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Texture-based Separable Convolution For a direct link to this sample, right-click and copy the URL (shortcut) of this link icon.

Texture-based implementation of a separable 2D convolution with a gaussian kernel. Used for performance comparison against convolutionSeparable.
  Minimum Required GPU
Minimum Required GPUor later
Minimum Required GPU




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FFT-Based 2D Convolution For a direct link to this sample, right-click and copy the URL (shortcut) of this link icon.

This sample demonstrates how 2D convolutions with very large kernel sizes can be efficiently implemented using FFT transformations.
  Minimum Required GPU
Minimum Required GPUor later
Minimum Required GPU



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Matrix Transpose For a direct link to this sample, right-click and copy the URL (shortcut) of this link icon.

Efficient matrix transpose.
  Minimum Required GPU
Minimum Required GPUor later
Minimum Required GPU




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Scalar Product For a direct link to this sample, right-click and copy the URL (shortcut) of this link icon.

This sample calculates scalar products of a given set of input vector pairs.
  Minimum Required GPU
Minimum Required GPUor later
Minimum Required GPU




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Fast Walsh Transform For a direct link to this sample, right-click and copy the URL (shortcut) of this link icon.

Naturally(Hadamard)-ordered Fast Walsh Tranform for batched vectors of arbitrary eligible(power of two) lengths
  Minimum Required GPU
Minimum Required GPUor later
Minimum Required GPU




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Eigenvalues For a direct link to this sample, right-click and copy the URL (shortcut) of this link icon.

The computation of all or a subset of all eigenvalues is an important problem in linear algebra, statistics, physics, and many other fields. This sample demonstrates a parallel implementation of a bisection algorithm for the computation of all eigenvalues of a tridiagonal symmetric matrix of arbitrary size with CUDA.
  Minimum Required GPU
Minimum Required GPUor later
Minimum Required GPU



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Matrix Multiplication (Driver Version) For a direct link to this sample, right-click and copy the URL (shortcut) of this link icon.

This sample implements matrix multiplication using the CUDA driver API. It has been written for clarity of exposition to illustrate various CUDA programming principles, not with the goal of providing the most performant generic kernel for matrix multiplication. CUBLAS provides high-performance matrix multiplication.
  Minimum Required GPU
Minimum Required GPUor later
Minimum Required GPU




Download - Windows x86
Download - Windows x64
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Simple CUBLAS For a direct link to this sample, right-click and copy the URL (shortcut) of this link icon.

Example of using CUBLAS.
  Minimum Required GPU
Minimum Required GPUor later
Minimum Required GPU




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Matrix Multiplication For a direct link to this sample, right-click and copy the URL (shortcut) of this link icon.

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 CUDA programming principles, not with the goal of providing the most performant generic kernel for matrix multiplication. CUBLAS provides high-performance matrix multiplication.
  Minimum Required GPU
Minimum Required GPUor later
Minimum Required GPU




Download - Windows x86
Download - Windows x64
Download - Linux/Mac

Last Update: 06/15/2009