Img/2012/1/21/pc-small.jpgWashington: Computer scientists have conducted the first systematic power profiles of microprocessors, which could help cut the power consumption of both small cell phones and giant data centres. Their results may point the way to how companies like Google, Apple, Intel and Microsoft can make software and hardware that will lower the energy costs of very small and very large devices.
“The less power cell phones draw, the longer the battery will last,” said Kathryn McKinley, professor of computer science at The University of Texas at Austin.
“For companies like Google and Microsoft, which run these enormous data centers, there is a big incentive to find ways to be more power efficient. More and more of the money they’re spending isn’t going toward buying the hardware, but toward the power the datacenters draw.”
McKinley said that without detailed power profiles of how microprocessors function with different software and different chip architectures, companies are limited in terms of how well they can optimize for energy usage.
The study she conducted with Stephen M. Blackburn of The Australian National University and their graduate students is the first to systematically measure and analyze application power, performance, and energy on a wide variety of hardware.
“We did some measurements that no one else had done before,” asserted McKinley.
“We showed that different software, and different classes of software, have really different power usage.”
McKinley insisted that such an analysis has become necessary as both the culture and the technologies of computing have shifted over the past decade.
Energy efficiency has become a greater priority for consumers, manufacturers and governments because the shrinking of processor technology has stopped yielding exponential gains in power and performance.
The result of these shifts is that hardware and software designers have to take into account tradeoffs between performance and power in a way they did not ten years ago.
“Say you want to get an application on your phone that’s GPS-based,” said McKinley.
“In terms of energy, the GPS is one of the most expensive functions on your phone. A bad algorithm might ping your GPS far more than is necessary for the application to function well. If the application writer could analyze the power profile, they would be motivated to write an algorithm that pings it half as often to save energy without compromising functionality.”
McKinley believes that the future of software and hardware design is one in which power profiles become a consideration at every stage of the process.
This work was recently invited to appear as a Research Highlight in the Communications of the Association for Computer Machinery (CACM).