Why Even Google Will Embrace Cellphone Chips in the Data Center

Jason Mars is a rarity. He's an outsider with regular access to Google's data centers.
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Inside Google's Douglas County, Georgia data center.Photo: Google/Connie Zhou


Mars is a professor of computer science at the University of California, San Diego, and about five years ago, during a conference for computer science researchers, he met a Googler named Robert Hundt. Among so many other things, Hundt is responsible for a set of tools that track the performance of Google's massive computing facilities -- widely regarded as the most advanced on the internet -- and somewhere along the line, he asked Mars to help him sift through the reams of information produced by these tools.

The UC San Diego professor now spends every summer at Google, looking for new ways of improving the company's online operation, and occasionally, he'll publish his Google research, providing the rest of us with a glimpse behind the curtain. "Basically, I look for ideas for how we can improve the efficiency of Google," he says. "We want to make each query cost less."

Co-authored with Hundt and another UC San Diego researcher, Lingjia Tang, his latest paper is particularly interesting because it indicates that Google's data centers may be moving in a direction the company didn't expect -- the same direction the rest of the big web outfits appear to be headed. According to the paper -- due to be published and presented this summer at a conference in Israel -- Google can save a tremendous amount of money by pairing specific software tasks with specific types of processors.

Today, as Mars explains, Google's data centers don't work that way. The company builds its massive computing facilities for homogeneity. The idea is to run everything on the same hardware. But the reality is that these facilities are more heterogenous than Google intends them to be.

"Google's runtime infrastructure was engineered assuming that all processor cores inside the data center -- hundreds of thousands of cores -- were the same," says Mars, who, together with Tang, runs a research operation at UC San Diego called Clarity Lab. "But it turns out that, because of machines being replaced and upgraded, you get old machines mixed in with new machines, and the processors used by these machines are from different generations."

What Mars and his colleagues discovered is that certain applications performed better on certain processors, and -- using specialized software to examine the phenomenon -- they found that if Google were to more carefully match applications with chips, it could improve the speed of its entire operation by as much as 15 percent. When you're the size of Google, that's an enormous boost. According to Mars, a mere one percent improvement would save millions of dollars.

"It turns out that we want to embrace heterogeneity," Mars says. "There is a huge opportunity to build cheaper data centers that are actually higher in performance."

As much performance as you gain simply by embracing the "accidental" heterogeneity in the data center, he says, you can gain even more by specifically re-engineering a facility for a wide range of processors. Others, including Facebook, have already indicated they intend to move in this direction, embracing a new breed of specialized chips. A big part of this is the rise of processors based on the ARM architecture, which chipmakers can readily modify for particular tasks.

"If you strategically buy the right mixture of machines for your particular applications," Mars says, "you can potentially save millions more."

Jason Mars.

Image: Jason Mars

Today, according to Intel's Jason Waxman, who oversees the sale of Intel chips into data centers, the giants of the web typically buy the fastest chips they can get their hands on. "What they’ve found is that the best way to get power efficiency is just to deliver more performance per server, and fewer servers," he says.

Frank Frankovsky, who oversees hardware design at Facebook, says the social networking giant typically chooses chips in this way. But, like Mars, he believes there's an opportunity to drive down costs even further through specialized ARM chips and other low-power processors based on architectures originally designed for smartphones.

In the past, Google has downplayed the importance of smartphone chips in the data center. But Mars -- an outsider who has seen Google's infrastructure in action -- sees things differently. "This kind of thing," he says, "could fundamentally change the way we build data centers."