activity
20202026
most citedModeling and Predicting Transistor Aging under Workload Dependency using Machine Learning

39 citations · 130 across the 7 of their papers we have counts for

collaborators

8 papers

cs.ET2026

NN-Based Transistor Modeling for Ultra-Fast SPICE Simulation and Standard Cell Library Characterization

Rodion Novkin, Hussam Amrouch

Neural network (NN)-based transistor models have proven to be a promising solution to accelerate device modeling. Although these models demonstrated remarkable speedup in circuit s…

cs.AR2024★ 7 cited

Variability-Aware Approximate Circuit Synthesis via Genetic Optimization

Konstantinos Balaskas, Florian Klemme, Georgios Zervakis +3

One of the major barriers that CMOS devices face at nanometer scale is increasing parameter variation due to manufacturing imperfections. Process variations severely inhibit the re…

cs.LG2022★ 4 cited

GNN4REL: Graph Neural Networks for Predicting Circuit Reliability Degradation

Lilas Alrahis, Johann Knechtel, Florian Klemme +2

Process variations and device aging impose profound challenges for circuit designers. Without a precise understanding of the impact of variations on the delay of circuit paths, gua…

cs.LG2022★ 39 cited

Modeling and Predicting Transistor Aging under Workload Dependency using Machine Learning

Paul R. Genssler, Hamza E. Barkam, Karthik Pandaram +2

The pivotal issue of reliability is one of colossal concern for circuit designers. The driving force is transistor aging, dependent on operating voltage and workload. At the design…

cs.ET2022★ 13 cited

Brain-Inspired Hyperdimensional Computing: How Thermal-Friendly for Edge Computing?

Paul R. Genssler, Austin Vas, Hussam Amrouch

Brain-inspired hyperdimensional computing (HDC) is an emerging machine learning (ML) methods. It is based on large vectors of binary or bipolar symbols and a few simple mathematica…

cs.AR2022★ 16 cited

Automated Design Approximation to Overcome Circuit Aging

Konstantinos Balaskas, Georgios Zervakis, Hussam Amrouch +2

Transistor aging phenomena manifest themselves as degradations in the main electrical characteristics of transistors. Over time, they result in a significant increase of cell propa…

cs.ET2022★ 24 cited

HW/SW Co-design for Reliable TCAM-based In-memory Brain-inspired Hyperdimensional Computing

Simon Thomann, Paul R. Genssler, Hussam Amrouch

Brain-inspired hyperdimensional computing (HDC) is continuously gaining remarkable attention. It is a promising alternative to traditional machine-learning approaches due to its ab…

cs.AR2020★ 27 cited

Hardware Trojan Detection Using Controlled Circuit Aging

Virinchi Roy Surabhi, Prashanth Krishnamurthy, Hussam Amrouch +4

This paper reports a novel approach that uses transistor aging in an integrated circuit (IC) to detect hardware Trojans. When a transistor is aged, it results in delays along sever…