S
Saibal Mukhopadhyay
Researcher at Georgia Institute of Technology
Publications - 432
Citations - 10232
Saibal Mukhopadhyay is an academic researcher from Georgia Institute of Technology. The author has contributed to research in topics: Computer science & CMOS. The author has an hindex of 40, co-authored 381 publications receiving 8814 citations. Previous affiliations of Saibal Mukhopadhyay include IBM & Purdue University.
Papers
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Journal ArticleDOI
Partitioning Methods for Interface Circuit of Heterogeneous 3-D-ICs Under Process Variation
Duckhwan Kim,Saibal Mukhopadhyay +1 more
TL;DR: The footprint, power, and performance of the interface are analyzed considering the effects of tier-to-tier process variations in 3-D-ICs and technology scaling, and simulation results show that dividing the interface circuit evenly between two tiers reduces footprint but increases power dissipation.
Journal ArticleDOI
Clock Data Compensation Aware Digital Circuits Design for Voltage Margin Reduction
TL;DR: An accurate time-domain behavioral model of timing slack variation due to PSN accounting for the clock-data compensation is presented and shows that the model helps reduce pessimism in estimated timing slack.
Proceedings ArticleDOI
What does ultra low power requirements mean for side-channel secure cryptography?
TL;DR: Case studies are presented to show that the low-power requirement is a challenge as well as an opportunity for improving side-channel resistance and shows the need for future research on low- power and side- channel secure cryptography.
Journal ArticleDOI
A constricting band: an unusual cause of incomplete expansion of Amplatzer septal occluder device.
TL;DR: An unusual problem that was responsible for incomplete expansion of the waist of the device, not yet reported in world literature, was reported, and a polyester band in continuation with the polyester mesh was found constricting the waistof the device.
Journal ArticleDOI
A Task-Driven Feedback Imager with Uncertainty Driven Hybrid Control.
TL;DR: In this article, a closed-loop feedback smart camera from the lens of uncertainty estimation is used to characterize and facilitate the feedback operation, and two modes of control, one that prioritizes false positives and one that pre-empts false negatives, and a hybrid approach combining the two are presented.