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.