Since 2013, Chinese machines have occupied the number one slot in rankings of the world’s most powerful supercomputers. Now America is back on top again. Engineers at the US Department of Energy’s Oak Ridge National Lab in Tennessee have just unveiled Summit, a supercomputer with enough processing power to surpass the current record holder, China’s Sunway TaihuLight.

The new machine is capable, at peak performance, of 200 petaflops—200 million billion calculations a second. To put that in context, everyone on earth would have to do a calculation every second of every day for 305 days to crunch what the new machine can do in the blink of an eye. Summit is 60 percent faster than the TaihuLight and almost eight times as fast as a machine called Titan, which is also housed at Oak Ridge and held the US supercomputing speed record until Summit’s arrival.

But it isn’t just national pride that’s at stake here. Supercomputers are already being used in industry for everything from designing new aircraft to creating new materials. Others are employed by the military to design nuclear weapons, and by scientists to conduct fundamental research. If the most powerful one is in the US, American researchers and the country’s armed forces will have an extra edge.

Node containing chips for the Summit supercomputer. Oak Ridge National Laboratory

The team at Oak Ridge says Summit is the first supercomputer designed from the ground up to run AI applications, such as machine learning and neural networks. It has over 27,000 GPU chips from Nvidia, whose products have supercharged plenty of AI applications, and also includes some of IBM’s Power9 chips, which the company launched last year specifically for AI workloads. There’s also an ultrafast communications link for shipping data between these silicon workhorses.

Bob Picciano of IBM says all this allows Summit to run some applications up to 10 times faster than Titan while using only 50 percent more electrical power. Among the AI-related projects slated to run on the new supercomputer is one that will crunch through huge volumes of written reports and medical images to try to identify possible relationships between genes and cancer. Another will try to identify genetic traits that could predispose people to opioid addiction and other afflictions.