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Comment by kens | Hacker News Reader

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...

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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.

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?

I think there will always be an API. In the case of Deep Learning you already see Caffe, TensorFlow, etc. readily available for developers.

I don't think the average developer will need to understand chip design but I do think _many_ developers will need to know how to use deep learning frameworks.

It had definitely started as an API side detail. But it might become an industry thing. It allows very easy vendor lock-in for all the *AAS products (PAAS, SAAS, etc). You could be required an add-on for your server or machine to be able to use their product.

Oh, and imagine a Facebook chip. :)

i'm an average programmer but reading "High Performance Computing" http://shop.oreilly.com/product/9781565923126.do made a huge difference for me even when writing more efficient CRUD apps. A big issue is understanding the cost of the operations in the stack you are using and the overheads caused by your stack.

I dunno... I'm not Rob Pike, but I could basically describe computing from the quantum level to the solar system dynamics and electromagnetic influences of a robotic interplanetary craft.

Then again, I've been coding for ~25 years, am an avid amateur astronomer, and have a degree in physics, so maybe the moral here is that some things just just take more time to master, beyond those first 6 weeks in a coding camp learning how to put together your first jQuery.

:-)

Interesting, I hadn't heard of this term before but it sounds about right!

Maybe the next iteration will be assembly instructions specifically for Neural Nets built into CPUs...actually something like a convolution assembly instruction wouldn't even surprise me at this point.

See also the VAX. It had an assembly instruction to evaluate a polynomial based on a table of coefficients in memory: POLY

http://uranium.vaxpower.org/~isildur/vax/week.html

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