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 AI 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 learning is provided
Gigabit Ethernet, dual-band Wi-Fi, and Bluetooth for IoT service to support PLC equipment and OPC-UA communication
Support for MQTT-based IoT 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 provided