Optimizing Power For Learning At The Edge


Learning on the edge is seen as one of the Holy Grails of machine learning, but today even the cloud is struggling to get computation done using reasonable amounts of power. Power is the great enabler—or limiter—of the technology, and the industry is beginning to respond. "Power is like an inverse pyramid problem," says Johannes Stahl, senior director of product marketing at Synopsys. "T... » read more

More Problems Ahead


Semiconductor Engineering sat down to discuss future scaling problems with Lars Liebmann, a fellow at IBM; Adam Brand, managing director of transistor technology at Applied Materials; Karim Arabi, vice president of engineering at Qualcomm; and Srinivas Banna, a fellow for advanced technology architecture at GlobalFoundries. SE: We’re starting to hear talk about octuple patterning. We’ve ... » read more