Nvidia, the world leader in computer chips used to create artificial intelligence, on Monday unveiled new research explaining how AI can be used to improve chip design.
The process of designing a chip involves deciding where to place tens of billions of tiny switches called transistors on a piece of silicon to create working circuits. The exact location of these transistors has a big impact on the cost, speed and power consumption of the chips.
Chip engineers use complex design software from companies like Synopsys and Cadence Design Systems to help them optimize the placement of these transistors.
On Monday, Nvidia released a paper showing it may be using a combination of AI techniques to find better ways to position large groups of transistors. The article aims to improve a 2021 publication by Google, whose results have since become the subject of controversy.
Nvidia’s research took an existing effort developed by researchers at the University of Texas using what’s called reinforcement learning and added a second layer of artificial intelligence to get even better results.
Nvidia chief scientist Bill Dally said the work matters because improvements in chip manufacturing are declining with costs per transistor in new generations of chip manufacturing technology now higher than in previous generations.
The idea runs counter to Intel co-founder Gordon Moore’s famous prediction that chips would get cheaper and faster.
“You’re not getting savings of that magnitude anymore,” Dally said. “To keep moving forward and deliver more value to customers, we can’t get it from cheaper transistors. We need to get it with smarter design.”
Source: Terra
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