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https://github.com/NVIDIA/CUDALibrarySamples

CUDA Library Samples
https://github.com/NVIDIA/CUDALibrarySamples

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CUDA Library Samples

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# CUDA Library Samples

CUDA Library Samples contains examples demonstrating the use of
features in the
* math and image processing libraries,
* cuBLAS,
* cuTENSOR,
* cuSPARSE,
* cuSOLVER,
* cuFFT,
* cuRAND,
* NPP,
* nvJPEG
* nvCOMP
* etc.

## About

The CUDA Library Samples are released by NVIDIA Corporation as Open Source software under the
3-clause "New" BSD license.

More information can be found about our libraries under [GPU Accelerated Libraries](https://developer.nvidia.com/gpu-accelerated-libraries).

## Library Examples

* [cuBLAS - GPU-accelerated basic linear algebra (BLAS) library](cuBLAS/)
* [cuBLASLt - Lightweight GPU-accelerated basic linear algebra (BLAS) library](cuBLASLt/)
* [cuBLASMp - Multi-process GPU-accelerated basic linear algebra (BLAS) library](cuBLASMp/)
* [cuBLASDx - GPU-accelerated device-side API extensions for BLAS calculations](MathDx/cuBLASDx)
* [cuDSS - GPU-accelerated linear solvers](cuDSS/)
* [cuFFT - GPU-accelerated library for Fast Fourier Transforms](cuFFT/)
* [cuFFTMp - Multi-process GPU-accelerated library for Fast Fourier Transforms](cuFFTMp/)
* [cuFFTDx - GPU-accelerated device-side API extensions for FFT calculations](MathDx/cuFFTDx)
* [cuRAND - GPU-accelerated random number generation (RNG)](cuRAND/)
* [cuSOLVER - GPU-accelerated dense and sparse direct solvers](cuSOLVER/)
* [cuSOLVERMp - Multi-process GPU-accelerated dense and sparse direct solvers](cuSOLVERMp/)
* [cuSPARSE - GPU-accelerated BLAS for sparse matrices](cuSPARSE/)
* [cuSPARSELt - Lightweight GPU-accelerated BLAS for sparse matrices](cuSPARSELt/)
* [cuTENSOR - GPU-accelerated tensor linear algebra library](cuTENSOR/)
* [cuTENSORMg - Multi-GPU GPU-accelerated tensor linear algebra library](cuTENSORMg/)
* [NPP - Provides GPU-accelerated image, video, and signal processing functions](NPP/)
* [nvJPEG - High performance GPU-accelerated library for JPEG encode/decoding](nvJPEG/)
* [nvJPEG2000 - High performance GPU-accelerated library for JPEG2000 encoding/decoding](nvJPEG2000/)
* [nvTIFF - GPU-accelerated TIFF encoding/decoding](nvTIFF/)
* [nvCOMP - GPU-accelerated data compression and decompression library](nvCOMP/)

## Copyright

Copyright (c) 2022-2024 NVIDIA CORPORATION AND AFFILIATES. All rights reserved.

```
Redistribution and use in source and binary forms, with or without modification, are permitted
provided that the following conditions are met:
* Redistributions of source code must retain the above copyright notice, this list of
conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright notice, this list of
conditions and the following disclaimer in the documentation and/or other materials
provided with the distribution.
* Neither the name of the NVIDIA CORPORATION nor the names of its contributors may be used
to endorse or promote products derived from this software without specific prior written
permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR
IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND
FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
STRICT LIABILITY, OR TOR (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
```