ArrayFire alternatives and similar libraries
Based on the "Concurrency" category
-
Thrust
A parallel algorithms library which resembles the C++ Standard Template Library (STL). [Apache2] -
ck
Concurrency primitives, safe memory reclamation mechanisms and non-blocking data structures. [BSD] -
HPX
A general purpose C++ runtime system for parallel and distributed applications of any scale. [Boost] -
moderngpu
moderngpu is a productivity library for general-purpose computing on GPUs. It is a header-only C++ library written for CUDA. The unique value of the library is in its accelerated primitives for solving irregularly parallel problems. [FreeBSD & Copyright, Sean Baxter] -
continuable
Async C++14 platform independent continuation chainer providing light and allocation aware futures -
CUB
CUB provides state-of-the-art, reusable software components for every layer of the CUDA programming mode. [New BSD] -
SPSCQueue.h
A bounded single-producer single-consumer wait-free and lock-free queue written in C++11 -
Easy Creation of GnuPlot Scripts from C++
A simple C++17 library to quickly plot your data with GnuPlot
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README
ArrayFire is a general-purpose library that simplifies the process of developing software that targets parallel and massively-parallel architectures including CPUs, GPUs, and other hardware acceleration devices.
Several of ArrayFire's benefits include:
- Easy to use, stable, well-documented API
- Rigorously tested for performance and accuracy
- Commercially friendly open-source licensing
- Commercial support from ArrayFire
- Read about more benefits on arrayfire.com
ArrayFire provides software developers with a high-level
abstraction of data which resides on the accelerator, the af::array object.
Developers write code which performs operations on ArrayFire arrays which, in turn,
are automatically translated into near-optimal kernels that execute on the computational
device.
ArrayFire is successfully used 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 (NVIDIA, AMD, and Qualcomm), as well as a variety of other accelerator devices on Windows, Mac, and Linux.
Installation
You can install the ArrayFire library from one of the following ways:
Official installers
Execute one of our official binary installers for Linux, OSX, and Windows platforms.
Build from source
Build from source by following instructions on our wiki.
Examples
The following examples are simplified versions of
helloworld.cpp
and
conway_pretty.cpp,
respectively. For more code examples, visit the
examples/
directory.
Hello, world!
array A = randu(5, 3, f32); // Create 5x3 matrix of random floats on the GPU
array B = sin(A) + 1.5; // Element-wise arithmetic
array C = fft(B); // Fourier transform the result
float d[] = { 1, 2, 3, 4, 5, 6 };
array D(2, 3, d, afHost); // Create 2x3 matrix from host data
D.col(0) = D.col(end); // Copy last column onto first
array vals, inds;
sort(vals, inds, A); // Sort A and print sorted array and corresponding indices
af_print(vals);
af_print(inds);
Conway's Game of Life
Visit the Wikipedia page for a description of Conway's Game of Life.
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); // Generate starting 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
}
Documentation
You can find our complete documentation here.
Quick links:
Language support
ArrayFire has several official and third-party language API`s:
Native
Official wrappers
We currently support the following language wrappers for ArrayFire:
Wrappers for other languages are a work-in-progress: .NET, Fortran, Go, Java, Lua, NodeJS, R, Ruby
Third-party wrappers
The following wrappers are being maintained and supported by third parties:
Contributing
Contributions of any kind are welcome! Please refer to CONTRIBUTING.md to learn more about how you can get involved with ArrayFire.
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 ArrayFire LLC and several third parties, please see the list of [acknowledgements](ACKNOWLEDGEMENTS.md) for further details.
Support and Contact Info
- Slack Chat
- Google Groups
- ArrayFire Services: Consulting | Support | 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
*Note that all licence references and agreements mentioned in the ArrayFire README section above
are relevant to that project's source code only.