Coral Dev Board User Manual

Introducción

The Coral Dev Board is a compact single-board computer designed for quickly prototyping on-device machine learning (ML) products. It features a removable System-on-Module (SoM) and an on-board Edge TPU coprocessor, enabling high-speed ML inferencing with low power consumption. This manual provides essential information for setting up, operating, and maintaining your Coral Dev Board.

Producto terminadoview y componentes

The Coral Dev Board integrates a System-on-Chip (SoC) with ML capabilities and wireless connectivity, running a derivative of Debian Linux called Mendel.

¿Qué hay en la caja?

• Removable system-on-module (SOM)
• 40-pin GPIO expansion header
• Conector de audio de 3.5 mm
• 2 digital PDM microphones
• 2.54mm 4-pin terminal for stereo speakers
• Puerto de alimentación tipo C
• Type-C OTG port
• Type-A 3.0 host
• Micro-B serial console port

Diseño de la placa

Familiarize yourself with the key components of the Coral Dev Board.

Imagen: En ángulo view of the Coral Dev Board, showcasing the heatsink and fan assembly, various ports (USB, HDMI), and the GPIO header. This board is designed for on-device machine learning.

Imagen: de arriba hacia abajo view of the Coral Dev Board, highlighting the central fan and heatsink, along with the various connectors and chips on the board.

Imagen: Abajo view of the Coral Dev Board, showing the underside of the circuit board with various solder points and the "Google" branding.

Imagen: de arriba hacia abajo view of the Coral Dev Board with a standard paperclip placed next to it, illustrating the compact size of the development board.

Configuración

To begin using your Coral Dev Board, you will need to set up the operating system and development environment.

Pasos de configuración inicial

1. Fuente de alimentación: Connect a compatible Type-C power supply to the board's power port.
2. Conexión de pantalla: Connect a display via the HDMI port if you require a graphical interface.
3. Conexión de red: Connect to a network via Ethernet or configure Wi-Fi.
4. Sistema operativo: The board runs Mendel, a derivative of Debian Linux. Refer to the official Coral documentation for detailed instructions on flashing the OS image to an SD card and booting the device.
5. Herramientas de desarrollo: Install the Mendel development tools on your host machine. A 64-bit operating system is required for these tools.
6. Acceso SSH: Configure SSH access for remote login and file transfer. You may need to use the Mendel development tools to push SSH keys.

Entorno del software

The Coral Dev Board is optimized for machine learning inference using TensorFlow Lite models.

• TensorFlow Lite: Ensure your machine learning models are converted to TensorFlow Lite format for optimal performance on the Edge TPU.
• Compatibilidad con Python: Currently, Python is the primary language supported for development. Support for C++ is expected in future releases.

Operating the Coral Dev Board

The core functionality of the Coral Dev Board lies in its ability to perform high-speed machine learning inferencing on-device, thanks to its Google Edge TPU coprocessor.

On-Device ML Inferencing

The Edge TPU is capable of performing 4 trillion operations per second (TOPS), using only 0.5 watts per TOP. This allows for efficient execution of state-of-the-art mobile vision models, such as MobileNet V2 at 400 FPS.

Aplicaciones

The Coral Dev Board is ideal for applications requiring high-performance computer vision with a small footprint and energy efficiency. This includes:

• Automated quality control in manufacturing.
• Robotics and autonomous systems.
• Smart home devices.
• Predictive maintenance.
• Any edge computing scenario where real-time ML inference is critical.

Presupuesto

Mantenimiento

To ensure the longevity and optimal performance of your Coral Dev Board, follow these maintenance guidelines:

• Manténlo limpio: Regularly clean the board with a soft, dry brush or compressed air to remove dust and debris, especially from the fan and heatsink.
• Control de temperatura: Ensure adequate ventilation to prevent overheating. The board is designed to run efficiently, but prolonged high-load operations in confined spaces may require additional cooling.
• Tratar con cuidado: Avoid static discharge by handling the board on an anti-static mat or by wearing an anti-static wrist strap.
• Actualizaciones de software: Periodically check for and install software updates for the Mendel operating system and TensorFlow Lite to benefit from performance improvements and security patches.

Solución de problemas

If you encounter issues with your Coral Dev Board, consider the following common troubleshooting steps:

Problemas comunes y soluciones

1. La placa no se enciende:
   • Verify the Type-C power supply is correctly connected and provides sufficient power.
   • Asegúrese de que la toma de corriente funcione.
2. Sin salida de pantalla:
   • Verifique las conexiones del cable HDMI.
   • Ensure your display supports the board's output resolution. Some small LCDs may not be compatible.
3. Problemas de conectividad de red:
   • For Ethernet, check cable connection and router status.
   • For Wi-Fi, verify network credentials and signal strength.
4. ML Inference Issues:
   • Confirm your models are correctly converted to TensorFlow Lite format.
   • Ensure the Edge TPU is properly recognized by the system.
   • Check for any error messages in your application logs.
5. Rendimiento lento:
   • Verify that your ML models are indeed running on the Edge TPU and not the CPU.
   • Monitor board temperature; excessive heat can lead to throttling.

For more detailed troubleshooting, consult the official Google Coral documentation and community forums.

Garantía y soporte

For information regarding warranty coverage, technical support, and additional resources, please refer to the official Google Coral website or contact Google's customer support. Keep your purchase receipt for warranty claims.