# ArrayFire Python Bindings

[ArrayFire](https://github.com/arrayfire/arrayfire) is a high performance library for parallel computing with an easy-to-use API. It enables users to write scientific computing code that is portable across CUDA, OpenCL and CPU devices. This project provides Python bindings for the ArrayFire library.

## Status
|  OS     | Tests   |
|:-------:|:-------:|
| Linux   | [![Build Status](http://ci.arrayfire.org/buildStatus/icon?job=arrayfire-wrappers/python-linux)](http://ci.arrayfire.org/view/All/job/arrayfire-wrappers/job/python-linux/)      |
| Windows | [![Build Status](http://ci.arrayfire.org/buildStatus/icon?job=arrayfire-wrappers/python-windows)](http://ci.arrayfire.org/view/All/job/arrayfire-wrappers/job/python-windows/)  |
| OSX     | [![Build Status](http://ci.arrayfire.org/buildStatus/icon?job=arrayfire-wrappers/python-osx)](http://ci.arrayfire.org/view/All/job/arrayfire-wrappers/job/python-osx/)          |

## Example

```python
import arrayfire as af

# Display backend information
af.info()

# Generate a uniform random array with a size of 5 elements
a = af.randu(5, 1)

# Print a and its minimum value
af.display(a)

# Print min and max values of a
print("Minimum, Maximum: ", af.min(a), af.max(a))
```

## Sample outputs

On an AMD GPU:

```
Using opencl backend
ArrayFire v3.0.1 (OpenCL, 64-bit Linux, build 17db1c9)
[0] AMD     : Spectre
-1- AMD     : AMD A10-7850K Radeon R7, 12 Compute Cores 4C+8G

[5 1 1 1]
0.4107
0.8224
0.9518
0.1794
0.4198

Minimum, Maximum:  0.17936542630195618 0.9517996311187744
```

On an NVIDIA GPU:

```
Using cuda backend
ArrayFire v3.0.0 (CUDA, 64-bit Linux, build 86426db)
Platform: CUDA Toolkit 7, Driver: 346.46
[0] Tesla K40c, 12288 MB, CUDA Compute 3.5
-1- GeForce GTX 750, 1024 MB, CUDA Compute 5.0

Generate a random matrix a:
[5 1 1 1]
0.7402
0.9210
0.0390
0.9690
0.9251

Minimum, Maximum:  0.039020489901304245 0.9689629077911377
```

Fallback to CPU when CUDA and OpenCL are not availabe:

```
Using cpu backend
ArrayFire v3.0.0 (CPU, 64-bit Linux, build 86426db)

Generate a random matrix a:
[5 1 1 1]
0.0000
0.1315
0.7556
0.4587
0.5328

Minimum, Maximum:  7.825903594493866e-06 0.7556053400039673
```

Choosing a particular backend can be done using `af.backend.set( backend_name )`  where backend_name can be one of: "_cuda_", "_opencl_", or "_cpu_". The default device is chosen in the same order of preference.

## Requirements

Currently, this project is tested only on Linux and OSX. You also need to have the ArrayFire C/C++ library installed on your machine. You can get it from the following sources.

- [Download and install binaries](https://arrayfire.com/download)
- [Build and install from source](https://github.com/arrayfire/arrayfire)

Please check the following links for dependencies.

- [Linux dependencies](http://www.arrayfire.com/docs/using_on_linux.htm)
- [OSX dependencies](http://www.arrayfire.com/docs/using_on_osx.htm)

## Getting started

**Install the last stable version:**

```
pip install arrayfire
```

**Install the development version:**

```
pip install git+git://github.com/arrayfire/arrayfire.git@devel
```

**Installing offline**

```
cd path/to/arrayfire-python
python setup.py install
```

**Post Installation**

Please follow [these instructions](https://github.com/arrayfire/arrayfire-python/wiki) to ensure the arrayfire-python can find the arrayfire libraries.

## Acknowledgements

The ArrayFire library is written by developers at [ArrayFire](http://arrayfire.com) LLC
with [contributions from several individuals](https://github.com/arrayfire/arrayfire_python/graphs/contributors).

The developers at ArrayFire LLC have received partial financial support
from several grants and institutions. Those that wish to receive public
acknowledgement are listed below:

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The following section contains acknowledgements for grant funding. In most
circumstances, the specific phrasing of the text is mandated by the grant
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### Grants

This material is based upon work supported by the DARPA SBIR Program Office
under Contract Numbers W31P4Q-14-C-0012 and W31P4Q-15-C-0008.
Any opinions, findings and conclusions or recommendations expressed in this
material are those of the author(s) and do not necessarily reflect the views of
the DARPA SBIR Program Office.
