Leveraging AI to help build AI SOCs

By SemiWiki

June 28, 2018

When I first started working in the semiconductor industry back in 1982, I realized that there was a race going on between the complexity of the system being designed and the capabilities of the technology in the tools and systems used to design them. The technology used to design the next generation of hardware was always lagging behind while it was being used to build generationally larger and more complex systems. I liken it to a dragon chasing its own tail. Designers have always really wished they had the next generation computing power available to design the next generation of hardware.

The situation has been this way ever since those days so long ago. However, perhaps the advent of Artificial Intelligence may change that dynamic. AI has an uncanny ability to solve complex problems that cannot addressed by more processors, more memory and more networking. It represents a fundamentally different way of solving problems that have large numbers of variables and complex performance surfaces.

It’s not surprising then to see machine learning making its way into the software and tools used to design SOCs and complex systems. The endgame of this is using machine learning to design machine learning systems. There you have it, AI inception.

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