I-Corps Teams: Machine Learning (ML)-powered Data Analyzer for Radio Frequency Integrated Circuits (RFIC) Design

Massachusetts Institute Of Technology, Cambridge MA

Investigators

Abstract

The broader impact/commercial potential of this I-Corps project is the development of a software platform for radio frequency integrated circuits (RFIC) design with more accurate simulation prediction. The RFIC industry, key for wireless systems, is approximately $50 B, and RFIC companies spend about $15 B on the final trial-and-error fabrication process known as "tape-out". Each tape-out takes 12 weeks and costs ~$1 M, and 3-5 may be required. Significant savings may be realized in both time and cost by reducing design iterations. This I-Corps project is based on the development of RFICs . RFIC’s parasitic effect and poor simulation accuracy requires multiple tape-outs to meet specifications. In the future 5G era, this problem gets worse as mmWave frequency parasitics are even harder to model and more tape-out rounds will be required. Using the technology under development, it may be possible to improve significantly simulation accuracy by combining traditional physics-based models and customized machine-learning (ML) training in RFIC simulation. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.