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https://github.com/rindow/rindow-math-matrix
The fundamental package for scientific matrix operation
https://github.com/rindow/rindow-math-matrix
acceleration array gpu hpc machine-learning mathematics n-dimensional openblas opencl php php8 scientific-computing
Last synced: 24 days ago
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The fundamental package for scientific matrix operation
- Host: GitHub
- URL: https://github.com/rindow/rindow-math-matrix
- Owner: rindow
- License: bsd-3-clause
- Created: 2020-02-02T14:30:53.000Z (almost 5 years ago)
- Default Branch: master
- Last Pushed: 2024-04-30T11:02:55.000Z (6 months ago)
- Last Synced: 2024-09-28T20:40:46.052Z (about 1 month ago)
- Topics: acceleration, array, gpu, hpc, machine-learning, mathematics, n-dimensional, openblas, opencl, php, php8, scientific-computing
- Language: PHP
- Homepage: https://rindow.github.io/mathematics/
- Size: 583 KB
- Stars: 10
- Watchers: 4
- Forks: 3
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
The fundamental package for scientific matrix operation
=======================================================
Status:
[](https://github.com/rindow/rindow-math-matrix/actions)
[](https://packagist.org/packages/rindow/rindow-math-matrix)
[](https://packagist.org/packages/rindow/rindow-math-matrix)
[](https://packagist.org/packages/rindow/rindow-math-matrix)
Rindow Math Matrix is the fundamental package for scientific matrix operation
- A powerful N-dimensional array object
- Sophisticated (broadcasting) functions
- BLAS functions
- Functions useful for machine learning
- Tools for integrating C/C++ through the FFI (OpenBLAS,Rindow-Matlib,CLBlast etc.)
- GPU support on your laptop without n-vidia (OpenCL with Intel,AMD etc.)
- Useful linear algebra and random number capabilities
Please see the documents on [Rindow mathematics project](https://rindow.github.io/mathematics/) web pages.
Requirements
============
- PHP 8.1 or PHP8.2 or PHP8.3
- PHP7.2, PHP7.3, PHP7.4 and PHP 8.0 are not supported in this release. Please use Release 1.1, which supports them.
### Strong recommend ###
You can perform very fast N-dimensional array operations in conjunction
- [rindow-math-matrix-matlibffi](https://github.com/rindow/rindow-math-matrix-matlibffi): plug-in drivers for OpenBLAS,Rindow-Matlib,OpenCL,CLBlast for FFI
- Pre-build binaries
- [Rindow matlib](https://github.com/rindow/rindow-matlib/releases)
- [OpenBLAS](https://github.com/xianyi/OpenBLAS/releases)
- [CLBlast](https://github.com/CNugteren/CLBlast/releases)
Please see the [rindow-math-matrix-matlibffi](https://github.com/rindow/rindow-math-matrix-matlibffi) to setup plug-in and pre-build binaries.
How to Setup
============
Set it up using composer.
```shell
$ composer require rindow/rindow-math-matrix
```
You can use it as is, but you will need to speed it up to process at a practical speed.
And then, Set up pre-build binaries for the required high-speed calculation libraries. Click [here](https://github.com/rindow/rindow-math-matrix-matlibffi) for details.
```shell
$ composer require rindow/rindow-math-matrix-matlibffi
```
Sample programs
===============
```php
array([[1,2],[3,4]]);
$b = $mo->array([[2,3],[4,5]]);
$c = $mo->cross($a,$b);
echo $mo->toString($c,indent:true)."\n";
```
```shell
$ php sample.php
[
[10,13],
[22,29]
]
```