Hands on with the Coral USB Accelerator

Getting started with Google’s new Edge TPU hardware

I also go “Hands on with the Coral Dev Board” in a companion article.

At last year’s Google Next conference in San Francisco Google announced two new upcoming hardware products both built around Google’s Edge TPU, their purpose-built ASIC designed to run machine learning inferencing at the edge.

Both a development board and a USB Accelerator, with a form-factor along similar lines to the Intel’s Neural Compute Stick, were announced allowing users to run inferences of pre-trained TensorFlow Lite models locally on their own hardware.

The Coral USB Accelerator.

The hardware is now available and has now launched into public Beta under the name Coral and, ahead of the launch, I managed to get my hands onto some early access hardware. I’ve already gotten hands on with the Coral Dev Board, but I also wanted to look at the new Coral USB Accelerator.

Opening the box

Much like the Coral Dev Board, the USB Accelerator comes in a small rather unprepossessing box. Mine was pre-production hardware, and the box came with sticker’ed up saying that “Marking and packaging not final,” which may well explain the AIY Projects branding on my USB Accelerator. Possibly the rebrand to Coral was only a fairly recent decision?

The Coral USB Accelerator

Inside the box is a USB stick and a short USB-C to USB-A cable intended to connect to to your computer. At 65mm × 30mm the USB Accelerator has roughly the same footprint as the Intel Neural Compute Stick, however with a depth of just 8mm the accelerator is much more slimline.

Comparing a first generation Movidius Neural Compute Stick (left), a second generation Intel Neural Compute Stick 2 (middle), and the new Coral USB Accelerator from Google (right).

The size of the USB Accelerator stick doesn’t seem all that important until you realise that the Intel stick was so large it tended to block nearby ports, or with some computers, be hard to use at all.

Gathering the supplies