Coral from Google - Introduction - SoM Overview

Coral from Google
Introduction
Getting Started SoM Overview
GStreamer
Example Pipelines
GstInference
Introduction Why use GstInference? Example Pipelines Demos
Camera Drivers
Introduction MIPI Camera connection How to flash Google Coral How to recompile kernel Adding a new camera driver Troubleshooting
Reference Documentation
Contact Us

Features

• Edge TPU System-on-Module (SoM)

   * NXP i.MX 8M SoC (Quad-core Arm Cortex-A53, plus Cortex-M4F)
   * Google Edge TPU ML accelerator coprocessor
   * Cryptographic coprocessor
   * Wi-Fi 2x2 MIMO (802.11b/g/n/ac 2.4/5 GHz)
   * Bluetooth 4.2
   * 8 GB eMMC
   * 1 GB LPDDR4

• USB connections

   * USB Type-C power port (5V DC)
   * USB 3.0 Type-C OTG port
   * USB 3.0 Type-A host port
   * USB 2.0 Micro-B serial console port

• Audio connections

   * 3.5 mm audio jack (CTIA compliant)
   * Digital PDM microphone (x2)
   * 2.54 mm 4-pin terminal for stereo speakers

• Video connections

   * HDMI 2.0a (full size)
   * 39-pin FFC connector for MIPI DSI display (4-lane)
   * 24-pin FFC connector for MIPI CSI-2 camera (4-lane)

• MicroSD card slot
• Gigabit Ethernet port
• 40-pin GPIO expansion header
• Supports Mendel Linux (derivative of Debian)

Download the datasheet here

Performance

Using MobileNet models for face detection the Edge TPU does the inference 70 to 100 times faster than a CPU and frames per second of up to 70 to 100. The table below shows the performance test done to a 64-bit Intel(R) Xeon(R) E5–1650 v4 @ 3.60GHz with and without a Coral USB Accelerator; also with a Quad-core Cortex-A53 @ 1.5GHz embedded system with and without an Edge TPU.

Performance of the Coral board. Image taken from: https://blog.tensorflow.org/2019/03/build-ai-that-works-offline-with-coral.html