Google Edge TPU Dev Board: Google Coral USB Accelerator Specs

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If you want to add machine learning capabilities to a standard Linux computer—even a Raspberry Pi single-board computer (SBC)— look no further than the Coral Edge TPU USB Accelerator.

This device measures in at a svelte 30x65x8mm, but its Edge TPU coprocessor is capable of four trillion operations per second. Its USB 3.1 interface (or 2.0 with reduced speeds) enables you to offload machine learning (ML) tasks to the device, allowing it to execute vision models at enhanced speeds. If you'd like to investigate further, you can browse its system performance benchmarks.

These specs are impressive, but how well does it perform? To test this little device, I attempted to use it out with two systems:

- My decade-old Lenovo T60 with Ubuntu Linux installed

- Raspberry Pi 3 Model B

Google Coral & Ubuntu: Linux Test

While I'm usually a Windows user, I keep a Lenovo T60 ThinkPad at the ready for experiments that require Linux (including successfully flashing firmware onto a Coral Dev board). This device was manufactured sometime around 2006, and I've operated it under Ubuntu for a few years after Windows refused to load.

While ancient, this machine qualifies as, per Google's getting started page, "any Linux computer with a USB port." After several generations of OS upgrades, it was able to load the proper firmware. I figured it would have no problem working with the Accelerator.

Unfortunately, after completing the text entry for step one, my computer informed me (in red lettering):

Your platform is not supported

Reading the bullet points under "any Linux computer," I noticed that it also requires a system architecture of either x86-64 or ARM32/64 with ARMv8 instruction set. After a bit of digging, I found that this system sports a 32-bit processor. So, "any Linux computer" isn't exactly the case. If you're having problems with an older machine, this might be your issue.

Fortunately, the Coral Edge TPU USB Accelerator also runs on the Raspberry Pi, with official support for the Pi 3 Model B, which I happen to have. Conveniently, mine was already set up with an install of Raspbian, the official Raspberry Pi OS, on its SD card.

Raspberry Pi & Google Coral: Raspberry Pi 3 Model B Test

One convenient aspect of the Raspberry Pi is that you know your starting point. If you have a Pi with a fresh OS install, all you need to do is follow the instructions. If something does go wrong, getting back to zero is as simple as flashing an SD card and updating.

Based on my background with the Pi, I was confident that Google's Getting Started instructions would work the same way. After I entered the necessary text, the software downloaded and installed without issue. One "gotcha" is that the command in step one that starts with "wget" extends with a scroll bar, and the -O on the same line is a capital letter, not a number.

Next, plug in the Accelerator, then download and run the model to identify a parrot (or more accurately, an Ara Macao or Scarlet Macaw). The program accomplished this with a score of 0.761719, so the Accelerator was doing its job. What seems a little too convenient, however, is that the manufacturers are supplying the model for you to test. I wasn't satisfied with this setup, so I downloaded a few more avian images to see how it performed.

Google Coral Image Identification