collaborators

5 papers

cs.AR2021

Encoder-Decoder Networks for Analyzing Thermal and Power Delivery Networks

Vidya A. Chhabria, Vipul Ahuja, Ashwath Prabhu +3

Power delivery network (PDN) analysis and thermal analysis are computationally expensive tasks that are essential for successful IC design. Algorithmically, both these analyses hav…

cs.AR2021

OpeNPDN: A Neural-network-based Framework for Power Delivery Network Synthesis

Vidya A. Chhabria, Sachin S. Sapatnekar

Power delivery network (PDN) design is a nontrivial, time-intensive, and iterative task. Correct PDN design must account for considerations related to power bumps, currents, blocka…

cs.AR2021

A New, Computationally Efficient "Blech Criterion" for Immortality in General Interconnects

Mohammad Abdullah Al Shohel, Vidya A. Chhabria, Sachin S. Sapatnekar

Traditional methodologies for analyzing electromigration (EM) in VLSI circuits first filter immortal wires using Blech's criterion, and then perform detailed EM analysis on the rem…

cs.AR2020

MAVIREC: ML-Aided Vectored IR-DropEstimation and Classification

Vidya A. Chhabria, Yanqing Zhang, Haoxing Ren +3

Vectored IR drop analysis is a critical step in chip signoff that checks the power integrity of an on-chip power delivery network. Due to the prohibitive runtimes of dynamic IR dro…

cs.AR2020

Thermal and IR Drop Analysis Using Convolutional Encoder-Decoder Networks

Vidya A. Chhabria, Vipul Ahuja, Ashwath Prabhu +3

Computationally expensive temperature and power grid analyses are required during the design cycle to guide IC design. This paper employs encoder-decoder based generative (EDGe) ne…