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Sacrificing Accuracy For Speed and Efficiency In Processors
Skudd writes "Modern computing has always been reliant on accuracy and correct answers. Now, a professor at Rice University in Houston posits that some future applications could be revolutionized by 'probabilistic computing.' Quoting: 'This afternoon, Krishna Palem, speaking at a computer science meeting in San Francisco, will announce results of the first real-world test of his probabilistic computer chip: The chip, which thrives on random errors, ran seven times faster than today's best technology while using just 1/30th the electricity. ... The high density of transistors on existing chips also leads to a lot of background "noise." To compensate, engineers increase the voltage applied to computer circuits to overpower the noise and ensure precise calculations. Palem began wondering how much a slight reduction in the quality of calculations might improve speed and save energy. He soon realized that some information was more valuable than other information. For example, in calculating a bank balance of $13,000.81, getting the "13" correct is much more important than the "81." Producing an answer of $13,000.57 is much closer to being correct than $57,000.81. While Palem's technology may not have a future in calculating missions to Mars, it probably has one in such applications as streaming music and video on mobile devices, he said.'
NEWS FLASH: Binary consists of 1 and 0.
NEWS FLASH: People use computers for calculations with more than single-digit binary results.
"probablistic computing" is another way of saying "sloppy engineering".
No- insisting on excessive precision where an "almost certainly right to within +/- x%" solution would be more than good enough and much simpler to obtain is known as overengineering.
I suspect that the financial examples chosen didn't illustrate the point as well as intended (financial companies generally don't like *any* inaccuracy), but that doesn't change the general principle.
Would you prefer a routing algorithm that gobbled up power and took ages to run for a guaranteed shortest route or one that was far more efficient and 99.9% certain to give a route that was within 3% of the shortest possible distance?
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The author of the linked article has completely misunderstood what this research is about. It is NOT about tolerating errors in the output of computations; that would be completely infeasible. It's about tolerating errors in intermediate values, by using redundancy. For example, three adders made out of unreliable transistors plus a control unit to have them vote, may be smaller and use less power than one adder made out of reliable transistors. However, you can't make everything out of unreliable transistors. In particular, the control unit, and the parts that compare results to each other, have to work reliably and can't be duplicated. That is what is meant by "some information was more valuable than other information", not the low-order bits of a numeric computation.