"We've removed the components that don't get used very much, and components that fail relatively frequently — such as hard drives and DIMMs — can now be removed and replaced in a few seconds," Facebook said. All the handles and levers that technicians are supposed to touch are colored green, so the machines can be serviced quickly, and even the motherboard can be removed within a minute. "In fact, Big Sur is almost entirely tool-less --the CPU heat sinks are the only things you need a screwdriver for" Facebook says.
It's not sharing the design to be altruistic: Facebook hopes others will try out the hardware and suggest improvements. And if other big companies ask server makers to build their own Big Sur systems, the economies of scale should help drive costs down for Facebook.
Machine learning has come to the fore lately for a couple of reasons. One is that large data sets used to train the systems have become publicly available. The other is that powerful computers have gotten affordable enough to do some impressive AI work.
Facebook pointed to software it developed already that can read stories, answer questions about an image, play games, and learn tasks by observing examples. "But we realized that truly tackling these problems at scale would require us to design our own systems," it said.
Big Sur, named after a stretch of picturesque California coastline, uses GPUs from Nvidia, including its Tesla Accelerated Computing Platform.
Facebook said it will to triple its investment in GPUs so that it can bring machine learning to more of its services.
"Big Sur is twice as fast as our previous generation, which means we can train twice as fast and explore networks twice as large," it said. "And distributing training across eight GPUs allows us to scale the size and speed of our networks by another factor of two."
Google is also rolling out machine learning across more of its services. "Machine learning is a core, transformative way by which we’re rethinking everything we’re doing," Google CEO Sundar Pichai said in October.
Facebook didn't say when it would release the specifications for Big Sur. The next OCP Summit in the U.S. takes place in March, so it might say more about the system more then.
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