Articles by Jayaprakash Balachandran

Design of PCB-based PDNs has become a challenge due to rising power consumption, lowering supply voltages, increasing integration density and design complexity. In this paper, we propose an algorithmic procedure using supervised machine learning techniques to provide expert guidance on the PDN design and optimize power supply decoupling capacitors. The proposed method replaces the computationally expensive numerical simulations with faster ANNs.

While a channel may pass a test, the remaining margin and thus its resilience against geometry or material variation in production may not be observable. However, such variations are critical because they may impede the performance or cause high volume manufacturing (HVM) products to fail. This coalition of authors has developed and demonstrated a polynomial chaos expansion (PCE) flow to analyze a full-featured 100GBASE-KR4 link starting from geometry specification to Channel Operating Margin (COM) margin at the receiver. Read on to see their award winning paper on the subject.