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XLang™

XLang™ is a next-generation programming language crafted for AI and IoT applications, designed to deliver dynamic, high-performance computing. It excels in distributed computing and offers seamless integration with popular languages like C++, Python, and JavaScript, making it a versatile choice across diverse operating systems.

Unlike Python or other instruction-based languages, XLang is an expression language. It runs directly from the Abstract Syntax Tree (AST) and parallelly executes expression-based data flows across multiple available execution pipelines.

Key Features

• High Efficiency: XLang™ runs 3 to 5 times faster than Python, particularly in AI and deep learning applications.
• Optimized Tensor Computing: The language includes a fully optimized tensor computing architecture, enabling effortless neural network construction through tensor expressions.
• Performance Boost on GPU: In CUDA-enabled GPU environments, XLang™ can enhance inference and training performance by 6 to 10 times, automating tensor data flow graph generation and target-specific compilation.

If you're interested in contributing to the XLang project, we would love to hear from you. Whether you're a developer, tester, or simply passionate about advancing this technology, please don't hesitate to reach out. For more information or to get involved, send us an email at [email protected], and we'll be happy to provide you with the necessary details.

XLang has been thoroughly tested on Linux platforms, including successful deployment on Raspberry Pi boards. It also works on the Raspberry Pi Pico, offering flexibility for a wide range of projects. However, if you need specific build instructions or have any questions regarding the setup for the Raspberry Pi Pico, please contact us at the same email address. We're here to support you and ensure your experience with XLang is as smooth as possible.

Building XLang™

For optimal performance, please ensure that XLang is built in Release mode. You can do this by running:

cmake -DCMAKE_BUILD_TYPE=Release ..

Windows:

1. Clone the repository:

   git clone https://github.com/xlang-foundation/xlang.git

2. Open the XLang™ folder in Visual Studio.
3. Select your configuration (e.g., Local Machine/x64-Debug, WSL:Ubuntu/WSL-GCC-Debug).
4. Build via Visual Studio's build menu.

Linux (Ubuntu):

1. Install prerequisites:
   • UUID(required): 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
     pip install numpy

     (To disable Python integration, comment out add_subdirectory("PyEng") in CMakeLists.txt.)
2. Clone the repository:

   git clone https://github.com/xlang-foundation/xlang.git

3. Navigate to the cloned directory:

   cd xlang

4. Create and enter the build directory:

   mkdir out && cd out

5. Generate build files:

   cmake ..

6. Compile:

   make

macOS:

1. Install prerequisites:

   • UUID(required): brew install ossp-uuid

   • OpenSSL (for HTTP plugin): brew install openssl

   • Turbo-jpeg(optional for image module): brew install jpeg-turbo

   • Python3 (optional for Python library integration):

     brew install python3
     pip install numpy

     (To disable Python integration, comment out add_subdirectory("PyEng") in CMakeLists.txt.)

2. Clone the repository:

   git clone https://github.com/xlang-foundation/xlang.git

3. Navigate to the cloned directory:

   cd xlang

4. Create and enter the build directory:

   mkdir out && cd out

5. Generate build files:

   cmake ..

6. Compile:

   make

You can also use Xcode to open the XLang folder for compilation.

Running XLang™

Navigate to the XLang™ executable folder and run the xlang command:

$ ./xlang
xlang [-dbg] [-enable_python|-python]
      [-run_as_backend|-backend] [-event_loop]
      [-c "code,use \n as line separator"]
      [-cli]
      [file parameters]
xlang -help | -? | -h for help

Example Commands

• Running a Script File:
  To run an XLang™ script file:

  $ ./xlang my_script.x

• Running Inline Code with Event Loop:
  To execute inline code:

  $ ./xlang -c "print('Hello, XLang!')"

• Running in Command-Line Interface (CLI) Mode:
  To start in CLI mode without executing a file:

  $ ./xlang -cli

Under the test folder, you'll find numerous XLang and Python code examples that can be used for testing. While some files may currently break, we are actively working on improving compatibility with Python syntax and its ecosystem.

Debugging in VS Code:

• Install the XLang™ plugin.
• Start XLang™ with -event_loop -dbg -enable_python.
• Open or create a .x file and begin debugging from the VS Code menu.

Note: Debugging in VS Code has not been tested on Linux and macOS.

Building for Android:

1. On Windows, install Android Studio.
2. Open the XLang™ project from the xlang\Android folder.
3. Build using Android Studio's Build menu.