Intel® Compute Libraries for GPU

Introduction

Intel® Compute Libraries for GPU (Intel® clGPU) is a framework and repository for implementation of compute libraries (e.g. BLAS) accelerated using Intel® Processor Graphics. It provides ability to develop efficient and optimized kernels for Intel GPU and mechanism of their execution.

This technical preview includes Intel® clBLAS - Basic Linear Algebra Subprograms (BLAS) implementation optimized for Intel® GPU.

As with any technical preview, APIs may change in future updates.

License

Intel® clGPU is licensed under Apache License Version 2.0.

Attached licenses

Intel® clGPU uses 3rd-party components licensed under following licenses:

• googletest under Google* License
• OpenCL™ ICD and C++ Wrapper under Khronos™ License

Project structure

• include/iclgpu - core library API
• include/iclBLAS - Intel® clBLAS API
• core - the core library implementation
• libs/blas - Intel® clBLAS API implementation

Documentation

The online Intel® clGPU documentation is at GitHub pages

Module specific documentation:

• Intel® clGPU Core Library
• Intel® clBLAS API

There is also inline documentation available that can be generated with Doxygen.

Support

Please report issues and suggestions via GitHub issues.

How to Contribute

We welcome community contributions to Intel® clGPU. If you have an idea how to improve the library:

• Share your proposal via GitHub issues
• Ensure you can build the product and run all the examples with your patch
• In the case of a larger feature, create a test
• Submit a pull request

We will review your contribution and, if any additional fixes or modifications are necessary, may provide feedback to guide you. When accepted, your pull request will be merged into our internal and GitHub repositories.

System Requirements

Intel® clGPU supports Intel® HD Graphics and Intel® Iris® Graphics and is optimized for

• Codename Skylake:
  • Intel® HD Graphics 510 (GT1, client market)
  • Intel® HD Graphics 515 (GT2, client market)
  • Intel® HD Graphics 520 (GT2, client market)
  • Intel® HD Graphics 530 (GT2, client market)
  • Intel® Iris® Graphics 540 (GT3e, client market)
  • Intel® Iris® Graphics 550 (GT3e, client market)
  • Intel® Iris® Pro Graphics 580 (GT4e, client market)
  • Intel® HD Graphics P530 (GT2, server market)
  • Intel® Iris® Pro Graphics P555 (GT3e, server market)
  • Intel® Iris® Pro Graphics P580 (GT4e, server market)
• Codename Apollolake:
  • Intel® HD Graphics 500
  • Intel® HD Graphics 505
• Codename Kabylake:
  • Intel® HD Graphics 610 (GT1, client market)
  • Intel® HD Graphics 615 (GT2, client market)
  • Intel® HD Graphics 620 (GT2, client market)
  • Intel® HD Graphics 630 (GT2, client market)
  • Intel® Iris® Graphics 640 (GT3e, client market)
  • Intel® Iris® Graphics 650 (GT3e, client market)
  • Intel® HD Graphics P630 (GT2, server market)
  • Intel® Iris® Pro Graphics 630 (GT2, server market)

Intel® clGPU currently uses OpenCL™ with multiple Intel® OpenCL™ extensions and requires Intel® Graphics Driver to run.

Intel® clGPU requires CPU with Intel® SSE/Intel® AVX support.

The software dependencies are:

• CMake* 3.5 or later
• C++ compiler with partiall or full C++14 standard support compatible with:
  • GNU* Compiler Collection 5.2 or later
  • Visual C++ 2015 (MSVC++ 19.0) or later
• python™ 2.7 or later (scripts are both compatible with python™ 2.7.x and python™ 3.x)
• (optional) Doxygen* 1.8.13 or later Needed for manual generation of documentation from inline comments.

• The software was validated on:

  • CentOS* 7.2 with GNU* Compiler Collection 5.2 (64-bit only), using Intel® Graphics Compute Runtime for OpenCL™ Linux driver package .

  • Windows® 10 and Windows® Server 2012 R2 with MSVC 14.0, using Intel® Graphics Driver for Windows® [15.60] driver package.

    More information on Intel® OpenCL™ drivers can be found here.

We recommend to use these drivers.

Building

Download Intel® clGPU source code or clone the repository to your system:

    git clone  https://github.com/intel/clGPU.git

Satisfy all software dependencies and ensure that the versions are correct before building.

Intel® clGPU uses multiple 3^rd-party components. They are stored in binary form in common subdirectory. Currently they are prepared for MSVC++ and GCC*. They will be cloned with repository.

Intel® clGPU uses a CMake-based build system. You can use CMake command-line tool or CMake GUI (cmake-gui) to generate required solution. For Windows system, you can call in cmd (or powershell):

    @REM Generate 64-bit solution (solution contains multiple build configurations)...
    cmake -E make_directory build && cd build && cmake -G "Visual Studio 14 2015 Win64" ..

Created solution can be opened in Visual Studio 2015 or built using appropriate msbuild tool (you can also use cmake --build . to select build tool automatically).

For Unix and Linux systems:

    @REM Create GNU makefile for release and build it...
    cmake -E make_directory build && cd build && cmake -DCMAKE_BUILD_TYPE=Release .. && make
    @REM Create Ninja makefile for debug and build it...
    cmake -E make_directory build && cd build && cmake -G Ninja -DCMAKE_BUILD_TYPE=Debug .. && ninja -k 20

CMake solution offers multiple options which you can specify using normal CMake syntax (-D<option-name>=<value>):

Generating documentation

Documentation is provided inline and can be generated in HTML format with Doxygen. We recommend to use latest Doxygen* and GraphViz*.

Documentation templates and configuration files are stored in docs subdirectories. You can generate documentation for the core library and Intel® clBLAS separately.

* Other names and brands may be claimed as the property of others.

Copyright © 2018, Intel® Corporation