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Google supercharges machine learning tasks with TPU custom chip

cloudplatform.googleblog.com

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Re: Google supercharges machine learning tasks with TPU custom chip

#81

Post by aab0 »

kens wrote: post #66
asimuvPR wrote: post #29

Now this is really interesting. I've been asking myself why this hadn't happened before. Its been all software, software, software for the last decade or so. But now I get it. We are at a point in time where it makes sense to adjust the hardware to the software. Funny how things work. It used to be the other way around.

This is known as the Wheel of Reincarnation. Functionality moves to special-purpose hardware then back to software, and the cycle repeats. (The computer term is from 1968 so this has been happening for a long time.) http://www.catb.org/jargon/html/W/wheel-of-reincarnation.htm...

I've been thinking for a while that with the end of silicon shrinkages, we may start seeing the final cycles of the wheel, with a final stop at mostly specialized hardware for greater power efficiency.

Re: Google supercharges machine learning tasks with TPU custom chip

#82

Post by skaevola »

j1vms wrote: post #58

I wouldn't be surprised if Google is looking to build (or done so already) a highly dense and parallel analog computer with limited precision ADC/DACs. I mean that's simplifying things quite a bit, but it would probably map pretty well to the Tensorflow application.

What are the advantages of analog computing for this application?

Re: Google supercharges machine learning tasks with TPU custom chip

#85

Post by merb »

manigandham wrote: post #70
merb wrote: post #28

Earlier quoted context omitted.

to start a REAL business you SHOULD act boring. for everything else there is google.

...are you saying Google isn't a real business?

no it's just that google has so many shiny things that come and go, if you build a business with shiny new things, you will propably fail if you do that over and over again, just because its shiny and new.

Re: Google supercharges machine learning tasks with TPU custom chip

#87

Post by vgt »

gcr wrote: post #80
abritishguy wrote: post #9

I think this shows a fundamental difference between Amazon (AWS) and Google Cloud. AWSs offerings seem fairly vanilla and boring. Google are offering more and more really useful stuff: - cloud machine learning - custom hardware - live migration of hosts without downtime - Cold storage with access in seconds - bigquery - dataflow

Vanilla? Boring? I read "Vanilla" and "Boring" as "Horray, I don't have to spend time rewriting all this complicated code I already have!" If I'm just dipping my toes into (say) Caffe or Theano, I don't have to rewrite it from scratch. That is a huge advantage---not a disadvantage!---of AWS over google.

Your point is valid, but I think what the OP was saying is that Google is offering all this stuff IN ADDITION to the boring stuff.

Google does boring stuff very well too.. and one can argue much better than AWS as well.. take a look at Quizlet's story: https://quizlet.com/blog/whats-the-best-cloud-probably-gcp

(shamelessly biased Googler)

Re: Google supercharges machine learning tasks with TPU custom chip

#88

Post by retox »

babo wrote: post #79
codecamper wrote: post #5

Earlier quoted context omitted.

I don't see any mention of offering these chips for sale. You can rent them it seems via cloud offerings & that's it.

Sure, but that's the deal. I'll buy the latest nVidia 1080 card as soon as I can but renting these custom chips per minute would be a way better option for me.

GPUs also have this nice side effect of being great at playing games on. Purely as a guess I'd think that the gaming market is bigger than the AI researcher market.

Re: Google supercharges machine learning tasks with TPU custom chip

#89

Post by dekhn »

asimuvPR wrote: post #74
kens wrote: post #66

Earlier quoted context omitted.

This is known as the Wheel of Reincarnation. Functionality moves to special-purpose hardware then back to software, and the cycle repeats. (The computer term is from 1968 so this has been happening for a long time.) http://www.catb.org/jargon/html/W/wheel-of-reincarnation.htm...

Wonder what it will do the the industry term Full Stack Developer . Will people who call themselves that will now need to know about chip design? OT: Cool blog! :)

At some point in the past, Rob Pike mentioned that when we was working on Voyager (that spaceship that almost 40 years after launch, has left the solar system and continues to send back valuable science data), he had a relatively good understanding of the system from the quantum level (transistors are based on quantum theory) to the solar system. He wasn't kidding, either.

Re: Google supercharges machine learning tasks with TPU custom chip

#90

Post by protomok »

euyyn wrote: post #75
BooneJS wrote: post #12

Earlier quoted context omitted.

From the article: "TPU is tailored to machine learning applications, allowing the chip to be more tolerant of reduced computational precision, which means it requires fewer transistors per operation."

Do you reckon that means it's using small floats?

Based on recent blog posts from some Google folks regarding quantizing neural nets I'm going to guess 8-bit fixed point.

For example -> https://petewarden.com/2016/05/03/how-to-quantize-neural-net...

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