
Google Coral Edge TPU - kilovoltaire
https://coral.withgoogle.com/
======
mark_l_watson
It is a small turnoff that you need to use their cloud model ‘compiler’ but I
still think I might get the USB Dev device.

I am retiring in a couple off weeks from my job managing a machine learning
team and I intend on being a ‘gentleman scientist’ studying things of
interest, without worrying about immediate practicality. Of most interest is
local ML using tensorflow.js and devices like the Edge TPU, and also hybrid
symbolic AI and deep neural net systems.

Anyway, good to see competition for edge devices.

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wyldfire
> Upload your model

> It should take about one minute for compilation to complete.

...also, it should take about six months for Google to lose interest in this
product, at which point the product you made when you integrated the Edge TPU
-- is stuck without updates.

~~~
crazygringo
This kind of comment is getting really tired.

Can you show me statistically that Google is any more likely to discontinue
something than any other startup? Or than Apple or Amazon?

A few people got upset about Google discontinuing Reader, but that was a
looong time ago. And they've certainly discontinued other things to... but
just like every other company.

~~~
andyburke
[https://en.wikipedia.org/wiki/List_of_Google_products#Discon...](https://en.wikipedia.org/wiki/List_of_Google_products#Discontinued_products_and_services)

They seem to discontinue a _lot_ of products, including ones with fairly large
user bases. It seems like a valid concern if you're going to try to build
something on top of their stuff.

~~~
deadmutex
They seem to ship a lot of products too:
[https://en.wikipedia.org/wiki/List_of_Google_products](https://en.wikipedia.org/wiki/List_of_Google_products)

Disclaimer: I work at Google.

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ipsum2
Previous discussion:
[https://news.ycombinator.com/item?id=19130896](https://news.ycombinator.com/item?id=19130896)

They mentioned previously that you had to compile your models on the cloud,
and not locally on your computer. Not sure if they've changed this policy.

~~~
aseipp
Doesn't look like it: [https://coral.withgoogle.com/web-
compiler/](https://coral.withgoogle.com/web-compiler/)

The proprietary compiler thing sucks, but it is where a lot of the secret
sauce is, unfortunately. But a binary wouldn't be too much to ask for...

~~~
ipsum2
Well then, its DoA. Not sure why any company would agree to these terms.

~~~
jononor
Agree it might be a dealbreaker for some. But right now there is not that much
competition in the TPU for embedded space. NVidia Jetson and Intel Nervana are
the only ones shipping? So if the TPU allows some company to do something not
possible / much better than with Jetson, they will probably be willing to play
that game.

~~~
monocasa
It's starting to heat up. K210s are supposed to be pretty cool if you can put
your hand on one.

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jononor
The baseboard and SOM module split looks very well done. The module includes
CPU+RAM+EMMC in addition to the TPU, so a custom baseboard can be quite
simple. A lot of audio input, ready for microphone arrays. Curious to see what
role the M4F microcontroller will play, hopefully that is for some sleep/low-
power usage where it can wake up the beefy CPU (and TPU).

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solomatov
I wish Google created a development version of TPU for inference so that it's
possible to debug models locally and then send them for training to the GCP.

~~~
CoolGuySteve
Ya, I feel uneasy about this business model of creating hardware that you have
to connect to a cloud service to actually use. Instead of vendor lock-in or
proprietary drivers or whatever, it's a new form of locality-based lock-in.

Meaning, if I have an application that needs a big hot PCI-E card attached to
a physical server I own somewhere, comparable to GPUs now, the TPU is not for
me. But meanwhile, a bunch of NN research and frameworks on top of TensorFlow
will treat these proprietary things as a first class citizen.

~~~
est31
The lock-in, while bad, only affects the development of new models. These
devices exist so that you can avoid the cloud for inference.

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syntaxing
The Edge TPU devices that Google has been promising since last year is now
available under a new company called Coral. Would love to get one to compare
to my Jetson TX2. The downside is that the unit can only use Tensorflow Lite.

E: Hah, seems like my topic got merged with this one. Interesting how I was
short from OPs post by like a minute a two. Such a coincidence!

~~~
est31
> a new company called Coral.

On that website, each page has the Google logo at the bottom and "Copyright
2019 Google LLC. All rights reserved.". Also, at [1], Google LLC is mentioned
as manufacturer of the devices. At this point, Coral still seems to be a brand
only, not a company. Maybe they just didn't want to harm/affect their "main"
trademark with this. Or they actually do want to create a separate company and
this is the first step.

[1]:
[https://coral.withgoogle.com/legal/](https://coral.withgoogle.com/legal/)

~~~
wyattjoh
Software Eng. with The Coral Project[0] here. Feeling a little odd with the
same color (even the logo a bit) + name combo used for their TPU as we've used
for The Coral Project for years now..

[0]: [https://coralproject.net/](https://coralproject.net/)

~~~
what_ever
I'm sorry but isn't that the Coral color..?

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shereadsthenews
Kinda surprised they went with the internal code name for this.

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Ecco
The datasheet says it features a "Cortex M4 with 16 KB of instruction cache
and 16 KB of data cache". As far as I know, M4 don't have L1 cache. Maybe
they're using an M7? Or there's just simply no cache?

[https://coral.withgoogle.com/tutorials/devboard-
datasheet/](https://coral.withgoogle.com/tutorials/devboard-datasheet/)

~~~
JosephRedfern
I don't think the M4 is a typo. Apparently it's based on the NXP i.MX 8M,
who's block diagram definitley states Cortex-M4 w/ 16K L1 Cache:
[https://www.nxp.com/products/processors-and-
microcontrollers...](https://www.nxp.com/products/processors-and-
microcontrollers/arm-based-processors-and-mcus/i.mx-applications-
processors/i.mx-8-processors/i.mx-8m-family-armcortex-a53-cortex-m4-audio-
voice-video:i.MX8M).

M4 application notes
([http://infocenter.arm.com/help/index.jsp?topic=/com.arm.doc....](http://infocenter.arm.com/help/index.jsp?topic=/com.arm.doc.dai0321a/BIHEADII.html))
says the M{-0..4} doesn't have any internal cache, but that it can be provided
by the SoC. Presumably that's what's happening here -- although it seems weird
that this can be called an L1 Cache (although I'm by no means an expert on
this so can't really comment!).

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yRetsyM
Interesting that it's Debian Linux support only for the peripherals. I'd be
interested to see if that support grows to other os's, especially if it's a
restriction to adoption.

I'm not in the space per-say but what are the predominant OS choices for ML/AI
Devs?

~~~
jononor
I think they just want to get things out quickly. Plenty of people will be
willing to deal with limitations in an early phase. I'm sure that for the USB
stick other Linux systems will follow, and probably Mac/Windows also. For the
SOM they might stick with just Debian I guess. It is normal in embedded to
just have one platform provided by the vendor, and everything else be "at your
own risk".

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dheera
They were handing the USB ones out today to attendees at the TensorFlow Dev
Summit. I'll test mine later.

However I _really_ wish they would make something beefier, to compete with
e.g. Nvidia's Xavier.

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bcatanzaro
Any details on how much this board costs? Also, how many TOPs the Edge TPU
has?

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mitfahrener
Dev Board cost $149.99, says on the website.

~~~
bcatanzaro
Thanks. Somehow I missed that, even though it's in large print at the top. :)

How about the Edge TPU specifications? Did I overlook those too?

