The Coral USB Accelerator brings powerful ML inferencing capabilities to existing Linux systems. Featuring the Edge TPU — a small ASIC designed and built by Google— the USB Accelerator provides high performance ML inferencing with a low power cost over a USB 3.0 interface. For example, it can execute state-of-the-art mobile vision models such as MobileNet v2 at 100+ fps, in a power efficient manner. This allows you to add fast ML inferencing to your embedded AI devices in a power-efficient and privacy-preserving way. Models are developed in TensorFlow Lite and then compiled to run on the USB Accelerator.
Edge TPU key benefits
- High-speed TensorFlow Lite inferencing
- Low power
- Small footprint
Coral is a division of Google, that helps you build intelligent ideas with our platform for local AI.
- Google Edge TPU ML accelerator coprocessor
- USB 3.0 Type-C socket
- Supports Debian Linux on host CPU
- Models are built using TensorFlow
- Fully supports MobileNet and Inception architectures though custom architectures are possible
- Compatible with Google Cloud
Edge TPU ML accelerator
ASIC designed by Google that provides high performance ML inferencing for TensorFlow Lite models
Arm 32-bit Cortex-M0+ Microprocessor (MCU)
- Up to 32 MHz max
- 16 KB Flash memory with ECC
- 2 KB RAM
- USB 3.1 (gen 1) port and cable (SuperSpeed, 5Gb/s transfer speed)
- Included cable is USB Type-C to Type-AU
Run on-device ML inferencing on the Edge TPU designed by Google.
Works with Debian Linux
Connect to any Linux-based system with an included USB Type-C cable.
The Coral USB Accelerator must be connected to a host computer with the following specifications:
Any Linux computer with a USB port
- Debian 6.0 or higher, or any derivative thereof (such as Ubuntu 10.0+)
- System architecture of either x86_64 or ARM64 with ARMv8 instruction set
Raspberry Pi is supported
- Only Raspberry pi <2/3 Model B/B+>
- While USB 3.0 provides the fastest performance Raspberry Pi only supports USB 2.0
Supported Operating Systems