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Releases: xlang-foundation/xlang

release-0.9.0: Merge pull request #287 from xlang-foundation/Jit

01 Sep 03:23
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Support below OS:
Windows 10, Windows 11
Ubuntu
Raspberry OS, Raspberry Ubuntu

release-0.8.0

04 Dec 05:03
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XLang™

XLang™ is a cutting-edge language designed for AI and IoT applications, offering exceptional dynamic and high-performance capabilities. It stands out with its innate ability for distributed computing. XLang™ excels in seamless integration with popular languages like C++, Python, and JavaScript, bridging the gap across various operating systems.

Performance-wise, XLang™ is notably efficient, running approximately 3 to 5 times faster than Python, especially in AI and deep learning contexts. It features a fully optimized tensor computing architecture, enabling users to effortlessly construct neural networks through tensor expressions. XLang™ automates the generation of tensor data flow graphs and compiles them for specific targets. Particularly in GPU environments utilizing CUDA, it can enhance inference and training performance by about 6 to 10 times.

Building XLang™:

  • For Windows:

    • Clone the repository: git clone https://github.com/xlang-foundation/xlang.git
    • Open the XLang™ folder with Visual Studio.
    • Select a configuration (e.g., Local Machine/x64-Debug, WSL:Ubuntu/WSL-GCC-Debug).
    • Build using Visual Studio's build menu.
  • For Linux (Ubuntu):

    • Install prerequisites:
      • UUID: sudo apt-get install uuid-dev
      • OpenSSL (for HTTP plugin): sudo apt-get install libssl-dev
      • Python3 (optional for Python library integration): sudo apt-get install python3-dev and pip install numpy. To disable, comment out add_subdirectory("PyEng") in CMakeLists.txt.
    • Building steps:
      1. Clone the repository: git clone https://github.com/xlang-foundation/xlang.git
      2. Navigate to the cloned directory: cd xlang
      3. Create and enter the build directory: mkdir out && cd out
      4. Generate build files: cmake ..
      5. Compile: make

Running XLang™:

  • Navigate to the XLang™ executable folder and run the xlang command.
  • For debugging in VS Code, install the XLang™ plugin and start XLang™ with -event_loop -dbg -enable_python. Open or create a .x file, and start debugging from the VS Code menu.

Building for Android:

  • On Windows, install Android Studio.
  • Open the XLang™ project from the xlang\Android folder and build using the Android Studio's Build menu.