Features

• ARM Cortex-A based high-performance embedded system training Equipment for Linux-based device driver implementation and application
• Main module is an edge supercomputer with a built-in GPU of up to 21 TOPS level. Applications support popular Al frameworks such as TensorFlow2, PyTorch, Caffe/Caffe2, MXNet, Keras, etc.
  Integrated configuration of main module that supports CUDA artificial intelligence acceleration calculation, speaker, digital array microphone, camera, high-precision environmental sensor, and breadboard
• User circuit configuration is possible through a breadboard, and application sensor modules are provided to integrate with the ARM Cortex-M processor
• High-resolution dual CSI camera with adjustable angle to enable image processing and deep learning-based vision processing leaming is provided Gigabit Ethernet, dual-band Wi-Fi, and Bluetooth for loT service to support PLC equipment and OPC-UA communication
• Support for MQTT-based loT connectivity, OpenCV-based image processing, and QT-based GUI practice in conjunction with device driver
• Support Xeus-python and Cling interpreter for aarch64 and VSCode-based IDE to enable learning C/C++ and Python 3 Linux kernel configuration and build, system call, platform device driver, MISC device driver, and application program implementation contents are provid