Internal Integration of AI Chips

Continued work on AI oriented computer chips.

Chip Designed by AI   by Agency for Science, Technology and Research (A*STAR), Singapore from TechXplore

A*STAR researchers have developed a machine learning algorithm that can help designers decide where to place components on an integrated circuit. Credit: Agency for Science, Technology and Research (A*STAR), Singapore

In less than a decade, artificial intelligence (AI) has gone from an obsession of a few ivory tower academics to runaway commercial success, potentially adding around US$13 trillion to the global economy by 2030 according to a McKinsey projection. One reason that AI is taking off now rather than when it was first conceptualized in the late 1950s is the availability of affordable computational power, in turn, made possible by steady advances in chip design.

But for all the technological advances ever smaller and more powerful integrated circuits (IC) have ushered in, designing the chips themselves remains a time-consuming and labor-intensive task. Although electronic design automation (EDA) software automating the placement of transistors on a chip has been available since the 1980s, the input of experienced human engineers is still required in what is largely a trial-and-error process, together with EDA tools to find the optimized sweet spot.

"More specifically, a large number of simulations and verifications are manually performed during the conventional design process. If the specification in any design cycle is not met, the designers have to redesign and verify the performance through simulation again," explained Salahuddin Raju, a Scientist at the Institute of Microelectronics (IME), A*STAR. .... "