Google's Next Moonshot Is Putting TPUs In Space With 'Project Suncatcher'

Google's new 'Project Suncatcher' aims to launch Tensor Processing Units (TPUs) into space, creating a solar-powered, satellite-based AI network
capable of scaling machine learning beyond Earth's limits. Google says a 'solar panel can be up to 8 times more productive than on earth' for near-continuous power using a 'dawn-dusk sun-synchronous low earth orbit' that reduces the need for batteries and other power generation. 9to5Google reports: These satellites would connect via free-space optical links, with large-scale ML workloads 'distributing tasks across numerous accelerators with high-bandwidth, low-latency connections.' To match data centers on Earth, the connection between satellites would have to be tens of terabits per second, and they'd have to fly in 'very close formation (kilometers or less).'

Google has already conducted radiation testing on TPUs (Trillium, v6e), with 'promising' results: 'While the High Bandwidth Memory (HBM) subsystems were the most sensitive component, they only began showing irregularities after a cumulative dose of 2 krad(Si) -- nearly three times the expected (shielded) five year mission dose of 750 rad(Si). No hard failures were attributable to TID up to the maximum tested dose of 15 krad(Si) on a single chip, indicating that Trillium TPUs are surprisingly radiation-hard for space applications.'

Finally, Google believes that launch costs will 'fall to less than $200/kg by the mid-2030s.' At that point, the 'cost of launching and operating a space-based data center could become roughly comparable to the reported energy costs of an equivalent terrestrial data center on a per-kilowatt/year basis.'

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