https://github.com/rindow/rindow-math-matrix-matlibffi
Rindow Math Matrix's Drivers for Matlib with PHP FFI
https://github.com/rindow/rindow-math-matrix-matlibffi
acceleration array gpu hpc machine-learning mathematics n-dimensional openblas opencl php php8 scientific-computing
Last synced: about 2 months ago
JSON representation
Rindow Math Matrix's Drivers for Matlib with PHP FFI
- Host: GitHub
- URL: https://github.com/rindow/rindow-math-matrix-matlibffi
- Owner: rindow
- License: bsd-3-clause
- Created: 2024-03-20T04:51:29.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-04-29T06:49:58.000Z (about 1 year ago)
- Last Synced: 2025-01-26T00:18:46.706Z (5 months 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: 15.6 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
Rindow Math Matrix's Drivers for Matlib with PHP FFI
====================================================
Status:
[](https://github.com/rindow/rindow-math-matrix-matlibffi/actions)
[](https://packagist.org/packages/rindow/rindow-math-matrix-matlibffi)
[](https://packagist.org/packages/rindow/rindow-math-matrix-matlibffi)
[](https://packagist.org/packages/rindow/rindow-math-matrix-matlibffi)
This package is matlib drivers for Rindow-math-matrix. These drivers act as adapters to drive PHP FFI. Each PHP C Libraries requires a separate download and installation of a binary file appropriate for your environment's PHP version and OS version.
Rindow Math Matrix is the fundamental package for scientific matrix operation
- A powerful N-dimensional array object
- Sophisticated (broadcasting) functions
- Tools for integrating C/C++ through the FFI
- Useful linear algebra and random number capabilities
Please see the documents on [Rindow mathematics projects](https://rindow.github.io/mathematics/) web pages.
Rindow Math Matrix's repository is [here](https://github.com/rindow/rindow-math-matrix/).
Requirements
============
- PHP 8.1 or PHP8.2 or PHP8.3 or PHP8.4
- Rindow Math Matrix v2.0 or later
- Rindow Matlib 1.0.0 or later
- OpenBLAS 0.3.20 or later(Linux/Windows), vecLib(macOS)
- OpenCL 1.1 or later
- CLBlast 1.5.2 or later
### Download pre-build binaries from each projects
You can perform very fast N-dimensional array operations in conjunction.
Download the pre-build binary files from each project's release page.
- Pre-build binaries
- [Rindow Matlib](https://github.com/rindow/rindow-matlib/releases)
- [OpenBLAS](https://github.com/OpenMathLib/OpenBLAS/releases)
- [CLBlast](https://github.com/CNugteren/CLBlast/releases)
Setup for Windows
=================
Download the binary file, unzip it, and copy it to the execution directory.
- rindow-matlib-X.X.X-win64.zip
- OpenBLAS-X.X.X-x64.zip
- CLBlast-X.X.X-windows-x64.zip
Add FFI extension to php.ini
```shell
C:\TMP> cd \path\to\php\directory
C:\PHP> notepad php.ini
extension=ffi
```
```shell
C:\TMP> PATH %PATH%;\path\to\binary\directories\bin
C:\TMP> cd \your\progject\directory
C:\PRJ> composer require rindow/rindow-math-matrix
C:\PRJ> composer require rindow/rindow-math-matrix-matlibffi
C:\PRJ> vendor/bin/rindow-math-matrix
Service Level : Accelerated
Buffer Factory : Rindow\Math\Buffer\FFI\BufferFactory
BLAS Driver : Rindow\OpenBLAS\FFI\Blas(THREAD)
LAPACK Driver : Rindow\OpenBLAS\FFI\Lapack
Math Driver : Rindow\Matlib\FFI\Matlib(THREAD)
OpenCL Factory : Rindow\OpenCL\FFI\OpenCLFactory
CLBlast Factory : Rindow\CLBlast\FFI\CLBlastFactory
```
The OpenCL 1.2 environment is already set up if you are using the Windows standard driver.
If you add the -v option as shown below, the driver loading status at boot time will be displayed.
It will help with troubleshooting.
```shell
C:\PRJ> vendor/bin/rindow-math-matrix -v
```
Setup for Linux
===============
Install each library using the apt command.
Make sure FFI extension is enabled.
```shell
$ php -m | grep FFI
FFI
```
Download the pre-build binary file.
- https://github.com/rindow/rindow-matlib/releases
Please install using the apt command.
```shell
$ sudo apt install ./rindow-matlib_X.X.X_amd64.deb
```
Since rindow-matlib currently uses ptheads, so you should choose the pthread version for OpenBLAS as well.
In version 1.0 of Rindow-matlib we recommended the OpenMP version, but now we have changed our policy and are recommending the pthread version.
This issue does not occur on Windows.
```shell
$ sudo apt install libopenblas0 liblapacke
```
If you want to use GPU, install the OpenCL environment.
In addition, there are the following drivers.
- mesa-opencl-icd
- beignet-opencl-icd
- intel-opencl-icd
- nvidia-opencl-icd-xxx
- pocl-opencl-icd
```shell
$ sudo apt install clinfo
$ sudo apt install mesa-opencl-icd
$ sudo mkdir -p /usr/local/usr/lib
$ sudo ln -s /usr/lib/clc /usr/local/usr/lib/clc
```
And then, Install the fast matrix calculation library for OpenCL.
If you use Ubuntu22.04 or Debian 12 or later, You can install it from distribution packages.
```shell
$ sudo apt install libclblast1
```
If You use Ubuntu20.04 or Debian 11, You need to download clblast from Github and make deb file.
Please download the CLBlast installation script from the rindow-clblast-ffi release page.
```shell
$ wget https://github.com/rindow/rindow-clblast-ffi/releases/download/X.X.X/clblast-packdeb.zip
$ unzip clblast-packdeb.zip
$ sh clblast-packdeb.sh
$ sudo apt install ./clblast_X.X.X_amd64.deb
```
> *CAUTION*: However, The rindow-matlib v1.1 do not support Ubuntu 20.04/Debian 11. If you want to use Ubuntu 20.04, please build it from source code or use rindow-matlib v1.0.
And then, Install the rindow-math-matrix on your project directory.
```shell
$ composer require rindow/rindow-math-matrix
$ composer require rindow/rindow-math-matrix-matlibffi
$ vendor/bin/rindow-math-matrix
Service Level : Accelerated
Buffer Factory : Rindow\Math\Buffer\FFI\BufferFactory
BLAS Driver : Rindow\OpenBLAS\FFI\Blas(THREAD)
LAPACK Driver : Rindow\OpenBLAS\FFI\Lapack
Math Driver : Rindow\Matlib\FFI\Matlib(THREAD)
OpenCL Factory : Rindow\OpenCL\FFI\OpenCLFactory
CLBlast Factory : Rindow\CLBlast\FFI\CLBlastFactory
```
If you add the -v option as shown below, the driver loading status at boot time will be displayed.
It will help with troubleshooting.
```shell
$ vendor/bin/rindow-math-matrix -v
```
Setup for macOS
===============
Install each library using the apt command.
Make sure FFI extension is enabled.
```shell
$ php -m | grep FFI
FFI
```
Download the pre-build binary file.
- https://github.com/rindow/rindow-matlib/releases
Please install using the apt command.
```shell
$ curl https://github.com/rindow/rindow-matlib/releases/download/X.X.X/rindow-matlib-X.X.X-Darwin-XXXX.tar.gz -O -L
$ tar -xzf rindow-matlib-XXX-Darwin-XXX.tar.gz
$ sudo cp -r usr/include /usr/local/
$ sudo cp -r usr/lib /usr/local/
```
If you want to use OpenMP mode instead of native thread mode, instantiate OpenMP. In most cases OpenMP mode is not needed.
```shell
$ brew install libomp
```
And then, Install the rindow-math-matrix on your project directory.
```shell
$ composer require rindow/rindow-math-matrix
$ composer require rindow/rindow-math-matrix-matlibffi
$ vendor/bin/rindow-math-matrix
Service Level : Advanced
Buffer Factory : Rindow\Math\Buffer\FFI\BufferFactory
BLAS Driver : Rindow\OpenBLAS\FFI\Blas(THREAD)
LAPACK Driver : Rindow\OpenBLAS\FFI\Lapack
Math Driver : Rindow\Matlib\FFI\Matlib(THREAD)
```
OpenCL is not supported on macOS.
### Check driver status
You can check the driver settings by running the sample below.
```php
service()->info();
```
```shell
$ php status.php
Service Level : Accelerated
Buffer Factory : Rindow\Math\Buffer\FFI\BufferFactory
BLAS Driver : Rindow\OpenBLAS\FFI\Blas(THREAD)
LAPACK Driver : Rindow\OpenBLAS\FFI\Lapack
Math Driver : Rindow\Matlib\FFI\Matlib(THREAD)
OpenCL Factory : Rindow\OpenCL\FFI\OpenCLFactory
CLBlast Factory : Rindow\CLBlast\FFI\CLBlastFactory
```
### Troubleshooting for Linux
Since rindow-matlib currently uses ptheads, so you should choose the pthread version for OpenBLAS as well.
In version 1.0 of Rindow-matlib we recommended the OpenMP version, but now we have changed our policy and are recommending the pthread version.
Using the OpenMP version of OpenBLAS can cause conflicts and become unstable and slow.
This issue does not occur on Windows.
If you have already installed the OpenMP version of OpenBLAS, you can delete it and install pthread version.
```shell
$ sudo apt install libopenblas0-pthread liblapacke
$ sudo apt remove libopenblas0-openmp
```
But if you can't remove it, you can switch to it using the update-alternatives command.
```shell
$ sudo update-alternatives --config libopenblas.so.0-x86_64-linux-gnu
$ sudo update-alternatives --config liblapack.so.3-x86_64-linux-gnu
```
If you really want to use the OpenMP version of OpenBLAS, please switch to the OpenMP version of rindow-matlib.
```shell
$ sudo update-alternatives --config librindowmatlib.so
There are 1 choices for the alternative librindowmatlib.so (providing /usr/lib/librindowmatlib.so).
Selection Path Priority Status
------------------------------------------------------------
* 0 /usr/lib/rindowmatlib-thread/librindowmatlib.so 95 auto mode
1 /usr/lib/rindowmatlib-openmp/librindowmatlib.so 95 manual mode
2 /usr/lib/rindowmatlib-serial/librindowmatlib.so 90 manual mode
3 /usr/lib/rindowmatlib-thread/librindowmatlib.so 100 manual mode
Press to keep the current choice[*], or type selection number: 1
```
Choose the "rindowmatlib-openmp".
Acceleration with GPU
=====================
You can use GPU acceleration on OpenCL.
*Note:*
This OpenCL support extension works better in your environment and helps speed up your laptop environment without n-NVIDIA.
Tested on Coffee Lake iGPU.
In the Windows environment, Integrated GPU usage was more effective than CPU, and it worked comfortably.
However, OLD AMD APU on Linux, libclc used in linux standard mesa-opencl-icd is very buggy and slow.
If you have testable hardware, please test using the proprietary driver.
It now works comfortably with various adjustments on Windows Standard OpenCL Driver. However, the old Intel Integrated GPU is not very high compared to its CPU performance, so please use the right person in the right place.
And it worked fine and fast in Ubuntu 24.04 + intel-opencl-icd environment.