Nearly Perfect is Better than Perfect
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Seems everyone is looking for perfection nowadays. They want to find the perfect mate, have the perfect house and the perfect life. Good luck with all that. Perfect is exceptionally hard if not impossible to obtain. And sometimes, being perfect is less efficient and more wasteful than meeting a goal with some flaws. Take the microchip for example. As this article from Technology Review shows, maybe being imperfect is actually better:
Krishna Palem is a heretic. In the world of microchips, precision and perfection have always been imperative. Every step of the fabrication process involves testing and retesting and is aimed at ensuring that every chip calculates the exact answer every time. But Palem, a professor of computing at Rice University, believes that a little error can be a good thing.
Palem has developed a way for chips to use significantly less power in exchange for a small loss of precision. His concept carries the daunting moniker “probabilistic complementary metal-oxide semiconductor technology”–PCMOS for short. Palem’s premise is that for many applications–in particular those like audio or video processing, where the final result isn’t a number–maximum precision is unnecessary. Instead, chips could be designed to produce the correct answer sometimes, but only come close the rest of the time. Because the errors would be small, so would their effects: in essence, Palem believes that in computing, close enough is often good enough.
Every calculation done by a microchip depends on its transistors’ registering either a 1 or a 0 as electrons flow through them in response to an applied voltage. But electrons move constantly, producing electrical “noise.” In order to overcome noise and ensure that their transistors register the correct values, most chips run at a relatively high voltage. Palem’s idea is to lower the operating voltage of parts of a chip–specifically, the logic circuits that calculate the least significant bits, such as the 3 in the number 21,693. The resulting decrease in signal-to-noise ratio means those circuits would occasionally arrive at the wrong answer, but engineers can calculate the probability of getting the right answer for any specific voltage. “Relaxing the probability of correctness even a little bit can produce significant savings in energy,” Palem says.
What does this mean for us?
Within a few years, chips using such designs could boost battery life in mobile devices such as music players and cell phones. But in a decade or so, Palem’s ideas could have a much larger impact. By then, silicon transistors will be so small that engineers won’t be able to precisely control their behavior: the transistors will be inherently probabilistic. Palem’s techniques could then become important to the continuation of Moore’s Law, the exponential increase in transistor density–and thus in computing power–that has persisted for four decades.
It’s about results. And if mistakes are made, it’s not the end of the world.
So in the future, when we’ve reduced our energy usage but increased our processing speed, you can thank the fact that the little processor is making mistakes for your benefit.
Be grateful that nothing is perfect.
