Researchers at Stanford have developed software that could increase the efficiency of cloud computing by eliciting more work from the available infrastructure at large-scale data centers.
The tool, named Quasar, uses techniques similar to Amazon and Netflix’s recommendation algorithms to determine the amount of computing resources that an application requires to run.
Researcher Christina Delimitrou M.S. ’12 Ph.D. ’17 emphasized the problems with current methods of allocating resources, which require internal users to specify the amount of resources needed for their application. According to Delimitrou, statistics from companies like Google, Microsoft and Twitter suggest that people tend to overestimate their needs by a factor of 10.
“If you measure the utilization [of the current system], it’s at around 10 to 20 percent, which means that about 80 percent of the computing power that you could be getting out of the machines is being wasted,” Delimitrou said.
Instead of asking users how many resources they need, Quasar asks people to specify how fast they want their application to run. The software then translates that performance target into resources based on data from similar applications. For complete post see here
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