The automated design of chips is facing growing challenges due to a high volume of smartphones, the increasing functionality, and the corresponding heterogeneity of the chips. In this talk, I will survey how machine learning has recently emerged as a core technique that promises to rescue the reducing gains in power performance and area in this field. In particular, I will focus on the challenges in deploying learning algorithms in electronic design automation and outline the solution that we take at Qualcomm which combines machine learning with combinatorial optimization solvers.

Speaker: Roberto Bondesan, Qualcomm https://scholar.google.com/citations?user=l2z7p3oAAAAJ&hl=en