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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.
Supports TensorFlow lite
No need to build models from the ground up. Tensorflow Lite models can be compiled to run on USB Accelerator.
The Coral USB Accelerator must be connected to the hostcomputer which is consistent with the following specifications：
All kinds of Linux computer with a USB port
- Debian6.0 or higher，or any derivative thereof（such as Ubuntu10.0+）
- System architecture of either x86_64 or ARM64 with ARMv8 instruction set
- Raspberry Pi2/3 Model B / B+ only
- Also note that to reach the best inference speed, you should use a USB 3.0 port.(unfortunately, Raspberry Pi has only USB 2.0 port)
|ML accelerator||Google Edge TPU coprocessor|
|Connector||USB Type-C* (data/power)|
|Dimensions||65 mm x 30 mm|
* Compatible with Raspberry Pi boards at USB 2.0 speeds only.
Supported Operating Systems
1 x Coral USB Accelerator
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