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Google supercharges machine learning tasks with TPU custom chip

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Re: Google supercharges machine learning tasks with TPU custom chip

#102
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.

Computing with opamp primitives has somewhat fallen out of favor since you've been away..

The primary cost factor in anything computing is just power. You can always buy more of the things, but power is the ongoing cost and every watt in computing costs you extra in cooling power.

Re: Google supercharges machine learning tasks with TPU custom chip

#103
post #81
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...

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.

Not only power efficiency but software efficiency. Custom chips combined with DSLs are a powerful combination. At the expense of segmentation, of course.

Re: Google supercharges machine learning tasks with TPU custom chip

#104
post #89

Earlier quoted context omitted.

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.

Very interesting fact. But the average programmer is not Rob Pike. How do you see this panning out for the average programmer? Will people need to learn a bit about chips to build more efficient CRUD apps?

Re: Google supercharges machine learning tasks with TPU custom chip

#105
post #96
post #63

I'm happy to hear that this is finally public so I can actually talk about the work I did when I was at Google :-). I'm a bit surprised they announced this, though. When I was there, there was this pervasive attitude that if "we" had some kind of advantage over the outside world, we shouldn't talk about it lest other people get the same idea. To be clear, I think that's pretty bad for the world and I really wished th…

Wouldn't you typically prototype the design on an FPGA and then manufacture an ASIC once you'd worked out the kinks?

I'm suspecting that the design contains a lot of repetitive units, each of which can easily be tested in software. So perhaps testing on an FPGA isn't even needed.

Re: Google supercharges machine learning tasks with TPU custom chip

#107
post #63

I'm happy to hear that this is finally public so I can actually talk about the work I did when I was at Google :-). I'm a bit surprised they announced this, though. When I was there, there was this pervasive attitude that if "we" had some kind of advantage over the outside world, we shouldn't talk about it lest other people get the same idea. To be clear, I think that's pretty bad for the world and I really wished th…

There were no references to this TPU in the TensorFlow source code?

Re: Google supercharges machine learning tasks with TPU custom chip

#108
post #63

I'm happy to hear that this is finally public so I can actually talk about the work I did when I was at Google :-). I'm a bit surprised they announced this, though. When I was there, there was this pervasive attitude that if "we" had some kind of advantage over the outside world, we shouldn't talk about it lest other people get the same idea. To be clear, I think that's pretty bad for the world and I really wished th…

"We have an FPGA, oh but need to go faster, ok, build an ASIC then" is a natural thing to come up with. That's kind of what bitcoin farms did.

Obviously details and plans how it was done is where all the good stuff is, so that being hidden is understandable.

Re: Google supercharges machine learning tasks with TPU custom chip

#110
post #63

I'm happy to hear that this is finally public so I can actually talk about the work I did when I was at Google :-). I'm a bit surprised they announced this, though. When I was there, there was this pervasive attitude that if "we" had some kind of advantage over the outside world, we shouldn't talk about it lest other people get the same idea. To be clear, I think that's pretty bad for the world and I really wished th…

There were no references to this TPU in the TensorFlow source code?

No but if you look at the code it's clearly designed to support pluggable hardware.
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