As computers, data centers and mobile devices become more powerful, their energy requirements are likewise generally increasing.
Possible solutions to the problem include power-saving sleep modes, devices that keep computers from drawing a current when supposedly turned off, and water-cooled processors. EnerJ, a new solution created at the University of Washington, takes a different approach – it supplies less power to regions of the chip that are performing processes that don’t require absolute precision. In lab simulations, it has already cut power consumption by up to 50 percent, although that amount could potentially reach as high as 90 percent.
With some processes, such as password encryption, close isn’t good enough. The chip regions handling those functions, therefore, would still receive maximum power. Other processes, however, are already designed to tolerate small errors. These include things such as games, streaming audio and video, and real-time image recognition on mobile devices. They would be handled by a region receiving less voltage.
“Image recognition already needs to be tolerant of little problems, like a speck of dust on the screen,” said Adrian Sampson, a UW doctoral student in computer science and engineering. “If we introduce a few more dots on the image because of errors, the algorithm should still work correctly, and we can save energy.”
The EnerJ system itself incorporates two interlocking pieces of code, one handling the precise functions, and one allocated to those that still work with errors. A barrier within the system would keep the two parts separate, so the more laid-back code would never accidentally end up being used for functions where precision was crucial.
Conceivably, the same principles could be applied purely to software, as opposed to chips. In programs where exact figures aren’t important, for instance, numbers could be rounded off. In other cases, less accuracy checks could be performed.
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