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https://github.com/arrayfire/arrayfire

ArrayFire: a general purpose GPU library.
https://github.com/arrayfire/arrayfire

arrayfire c c-plus-plus cpp cuda gpgpu gpu hpc opencl performance scientific-computing

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ArrayFire: a general purpose GPU library.

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README 

        



ArrayFire is a general-purpose tensor library that simplifies the software

development process for the parallel architectures found in CPUs, GPUs, and

other hardware acceleration devices. The library serves users in every

technical computing market.



Several of ArrayFire's benefits include:



* Hundreds of accelerated [tensor computing

  functions](https://arrayfire.org/docs/group__arrayfire__func.htm), in the

  following areas:

    * Array handling

    * Computer vision

    * Image processing

    * Linear algebra

    * Machine learning

    * Standard math

    * Signal Processing

    * Statistics

    * Vector algorithms

* [Easy to use](http://arrayfire.org/docs/gettingstarted.htm), stable,

  [well-documented](http://arrayfire.org/docs) API

* Rigorous benchmarks and tests ensuring top performance and numerical accuracy

* Cross-platform compatibility with support for CUDA, oneAPI, OpenCL, and

  native CPU on Windows, Mac, and Linux

* Built-in visualization functions through

  [Forge](https://github.com/arrayfire/forge)

* Commercially friendly open-source licensing

* Enterprise support from [ArrayFire](http://arrayfire.com)



ArrayFire provides software developers with a high-level abstraction of data

that resides on the accelerator, the `af::array` object. Developers write code

that performs operations on ArrayFire arrays, which, in turn, are automatically

translated into near-optimal kernels that execute on the computational device.



ArrayFire runs on devices ranging from low-power mobile phones to high-power

GPU-enabled supercomputers. ArrayFire runs on CPUs from all major vendors

(Intel, AMD, ARM), GPUs from the prominent manufacturers (AMD, Intel, NVIDIA,

and Qualcomm), as well as a variety of other accelerator devices on Windows,

Mac, and Linux.



# Getting ArrayFire



Instructions to [install][32] or to build ArrayFire from source can be found on

the [wiki][1].



### Conway's Game of Life Using ArrayFire



Visit the [Wikipedia page][2] for a description of Conway's Game of Life.



Conway's Game of Life



```cpp

static const float h_kernel[] = { 1, 1, 1, 1, 0, 1, 1, 1, 1 };

static const array kernel(3, 3, h_kernel, afHost);



array state = (randu(128, 128, f32) > 0.5).as(f32); // Init state

Window myWindow(256, 256);

while(!myWindow.close()) {

    array nHood = convolve(state, kernel); // Obtain neighbors

    array C0 = (nHood == 2);  // Generate conditions for life

    array C1 = (nHood == 3);

    state = state * C0 + C1;  // Update state

    myWindow.image(state);    // Display

}

```

The complete source code can be found [here][3].



### Perceptron



Perceptron



```cpp

array predict(const array &X, const array &W) {

    return sigmoid(matmul(X, W));

}



array train(const array &X, const array &Y,

        double alpha = 0.1, double maxerr = 0.05,

        int maxiter = 1000, bool verbose = false) {

    array Weights = constant(0, X.dims(1), Y.dims(1));



    for (int i = 0; i < maxiter; i++) {

        array P   = predict(X, Weights);

        array err = Y - P;

        if (mean(abs(err) < maxerr) break;

        Weights += alpha * matmulTN(X, err);

    }

    return Weights;

}

...



array Weights = train(train_feats, train_targets);

array test_outputs  = predict(test_feats, Weights);

display_results(test_images, test_outputs,

                      test_targets, 20);

```



The complete source code can be found [here][31].



For more code examples, visit the [`examples/`][4] directory.



# Documentation



You can find the complete documentation [here](http://www.arrayfire.com/docs/index.htm).



Quick links:



* [List of functions](http://www.arrayfire.org/docs/group__arrayfire__func.htm)

* [Tutorials](http://arrayfire.org/docs/tutorials.htm)

* [Examples](http://www.arrayfire.org/docs/examples.htm)

* [Blog](http://arrayfire.com/blog/)



# Language support



ArrayFire has several official and community maintained language API's:



[![C++][5]][6] [![Python][7]][8] [![Rust][9]][10] [![Julia][27]][28]†

[![Nim][29]][30]†



†  Community maintained wrappers



__In-Progress Wrappers__



[![.NET][11]][12] [![Fortran][13]][14] [![Go][15]][16]

[![Java][17]][18] [![Lua][19]][20] [![NodeJS][21]][22] [![R][23]][24] [![Ruby][25]][26]



# Contributing



The community of ArrayFire developers invites you to build with us if you are

interested and able to write top-performing tensor functions. Together we can

fulfill [The ArrayFire

Mission](https://github.com/arrayfire/arrayfire/wiki/The-ArrayFire-Mission-Statement)

for fast scientific computing for all.



Contributions of any kind are welcome! Please refer to [the

wiki](https://github.com/arrayfire/arrayfire/wiki) and our [Code of

Conduct](33) to learn more about how you can get involved with the ArrayFire

Community through

[Sponsorship](https://github.com/arrayfire/arrayfire/wiki/Sponsorship),

[Developer

Commits](https://github.com/arrayfire/arrayfire/wiki/Contributing-Code-to-ArrayFire),

or [Governance](https://github.com/arrayfire/arrayfire/wiki/Governance).



# Citations and Acknowledgements



If you redistribute ArrayFire, please follow the terms established in [the

license](LICENSE). If you wish to cite ArrayFire in an academic publication,

please use the following [citation document](.github/CITATION.md).



ArrayFire development is funded by AccelerEyes LLC and several third parties,

please see the list of [acknowledgements](ACKNOWLEDGEMENTS.md) for an

expression of our gratitude.



# Support and Contact Info



* [Slack Chat](https://join.slack.com/t/arrayfire-org/shared_invite/MjI4MjIzMDMzMTczLTE1MDI5ODg4NzYtN2QwNGE3ODA5OQ)

* [Google Groups](https://groups.google.com/forum/#!forum/arrayfire-users)

* ArrayFire Services:  [Consulting](http://arrayfire.com/consulting)  |  [Support](http://arrayfire.com/download)   |  [Training](http://arrayfire.com/training)



# Trademark Policy



The literal mark "ArrayFire" and ArrayFire logos are trademarks of AccelerEyes

LLC (dba ArrayFire). If you wish to use either of these marks in your own

project, please consult [ArrayFire's Trademark

Policy](http://arrayfire.com/trademark-policy/)



[1]: https://github.com/arrayfire/arrayfire/wiki

[2]: https://en.wikipedia.org/wiki/Conway%27s_Game_of_Life

[3]: https://github.com/arrayfire/arrayfire/blob/master/examples/graphics/conway_pretty.cpp

[4]: https://github.com/arrayfire/arrayfire/blob/master/examples/

[5]: https://img.shields.io/badge/c++-%2300599C.svg?style=for-the-badge&logo=c%2B%2B&logoColor=white

[6]: http://arrayfire.org/docs/gettingstarted.htm#gettingstarted_api_usage

[7]: https://img.shields.io/badge/python-%2314354C.svg?style=for-the-badge&logo=python&logoColor=white

[8]: https://github.com/arrayfire/arrayfire-python

[9]: https://img.shields.io/badge/rust-%23000000.svg?style=for-the-badge&logo=rust&logoColor=white

[10]: https://github.com/arrayfire/arrayfire-rust

[11]: https://img.shields.io/badge/.NET-5C2D91?style=for-the-badge&logo=.net&logoColor=white

[12]: https://github.com/arrayfire/arrayfire-dotnet

[13]: https://img.shields.io/badge/F-Fortran-734f96?style=for-the-badge

[14]: https://github.com/arrayfire/arrayfire-fortran

[15]: https://img.shields.io/badge/go-%2300ADD8.svg?style=for-the-badge&logo=go&logoColor=white

[16]: https://github.com/arrayfire/arrayfire-go

[17]: https://img.shields.io/badge/java-%23ED8B00.svg?style=for-the-badge&logo=java&logoColor=white

[18]: https://github.com/arrayfire/arrayfire-java

[19]: https://img.shields.io/badge/lua-%232C2D72.svg?style=for-the-badge&logo=lua&logoColor=white

[20]: https://github.com/arrayfire/arrayfire-lua

[21]: https://img.shields.io/badge/javascript-%23323330.svg?style=for-the-badge&logo=javascript&logoColor=%23F7DF1E

[22]: https://github.com/arrayfire/arrayfire-js

[23]: https://img.shields.io/badge/r-%23276DC3.svg?style=for-the-badge&logo=r&logoColor=white

[24]: https://github.com/arrayfire/arrayfire-r

[25]: https://img.shields.io/badge/ruby-%23CC342D.svg?style=for-the-badge&logo=ruby&logoColor=white

[26]: https://github.com/arrayfire/arrayfire-rb

[27]: https://img.shields.io/badge/j-Julia-cb3c33?style=for-the-badge&labelColor=4063d8

[28]: https://github.com/JuliaComputing/ArrayFire.jl

[29]: https://img.shields.io/badge/n-Nim-000000?style=for-the-badge&labelColor=efc743

[30]: https://github.com/bitstormGER/ArrayFire-Nim

[31]: https://github.com/arrayfire/arrayfire/blob/master/examples/machine_learning/perceptron.cpp

[32]: https://github.com/arrayfire/arrayfire/wiki/Getting-ArrayFire

[33]: https://github.com/arrayfire/arrayfire/wiki/Code-Of-Conduct