'Inexact' Chips Save Power By Fudging the Math

Barence writes "Computer scientists have unveiled a computer chip that turns traditional thinking about mathematical accuracy on its head by fudging calculations. The concept works by allowing processing components — such as hardware for adding and multiplying numbers — to make a few mistakes, which means they are not working as hard, and so use less power and get through tasks more quickly. The Rice University researchers say prototypes are 15 times more efficient and could be used in some applications without having a negative effect."

Re:Graphics cards

[Anonymous Coward]

Big difference between not dealing with full precision and encouraging erroneous behavior by trimming infrequently chunks of hardware.

Seems like nothing new

[CastrTroy]

Seems like nothing new to me. Floating point binary math is basically used for the same reason. It gives us and answer that's close enough, without requiring too much computation time. And it causes all sorts of fun since even simple numbers like 0.1 can't be represented exactly in binary floating point. Binary floating point works well for scientific apps, but fails quite badly at financial apps. I think this is basically taking floating point to the next level where the calculations are even more off. Which might work for certain applications, but for other types of applications would be completely catastrophic. What really bothers me is languages and platforms that provide no ability to work with numbers in a decimal representation.

Re:Turtles all the way down

[L4t3r4lu5]

Oh you misunderstand. It will still return the "right" answer, it'll just be "engineer" right, not "mathematician" right, i.e. "Good enough for all intents and purposes.

Furthermore, posting under the top post when your reply is nothing to do with the OP is considered a faux pas. Minus 50 DKP.

Re:AI Chip

[trum4n]

Humans tend to do fast imprecise math to decided when to cross the street. It looks like that car won't hit me, but i can't say its going to take 4.865 seconds for it to get to the crosswalk. Estimations, even if fudged and almost completely wrong, should play a massive role in AI.

Re:Turtles all the way down

[jythie]

Sounds about right, which would probably be a good thing. Too many programmers are obsessed with getting the mathematically correct answer to a precision that can have no actual impact on whatever they are trying to accomplish (or even worse, is rendered 'wrong' anyway by FP limitations of the language or chip anyway).

Re:AI Chip

[Anonymous Coward]

Did you really want a long-winded answer about how the conditioning of the wetwired neural network in your skull responding to external visual stimuli works? It's not math, it's chemical potentials at the neuron level. At a higher level, it's an estimate of depth perception vs. how fast you think you can walk (or run) across that street. No math involved, just spatial guesstimates of that brain of yours.

Re:Turtles all the way down

[networkBoy]

What about in a RT rendering (game/BD-Rom decode) situation, or a RT communication (Skype) situation?
Both of these do not need exact values, just close enough, and even if there was an error it will be transient and gone almost as fast as it was noticed?
-nB

Re:Whatcouldpossiblygowrong

[Hentes]

If I'm reading the article right, the chips are still deterministic, they just don't care about a few rare edge cases. So whether there is an error or not depends on the input, and in your case all four chips will make the same mistake. What you could try is modify the input a little for each rerun and try to interpolate the result from that, but that won't give you perfect accuracy.

Re:AI Chip

[bmo]

Which is... math.

Just because something doesn't involve digits doesn't mean it's not math. I suggest you look up analogue computers, because that's what you just described - a neural net acting as an analogue computer.

--
BMO

how is that not math?

[Chirs]

It's still math, it's just in the hardware rather than the software.

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