EDBT 2026 Demo / reviewers in the wild / expert
Jack M. Higman
dblp:82/4869
· DBLP profile ↗
4ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 4
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Electronic design automation · 100% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Computational science and engineering · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computational science and engineering › statistical physics
boltzmann equation |
0.0 | 1 | 1993 | A numerical method to compute isotropic band models from anisotropic semiconductor band structures · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 1993 |
Electronic design automation › technology computer-aided design
device simulation |
0.0 | 1 | 1993 | A numerical method to compute isotropic band models from anisotropic semiconductor band structures · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 1993 |
Electronic design automation › technology computer-aided design › device simulation
monte carlo device simulation |
0.0 | 1 | 1993 | A numerical method to compute isotropic band models from anisotropic semiconductor band structures · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 1993 |
Methods — techniques the papers use, named apart from their topics
monte carlo simulation · 0.0isotropic band model · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | Bias-Dependent Variation in FinFET SRAMabstractIn this brief, we investigate device variability in advanced fin field effect transistor (FinFET) static random access memory (SRAM) devices (12 and 7 nm) as a function of drain-to-source (Vds) bias. Drain-induced barrier lowering (DIBL) and the variation in DIBL are found to exhibit a logarithmic dependence with drain bias in the advanced node FinFET devices. Correctly capturing the DIBL and device variation as a function of drain bias is required, as the SRAM operation voltage range is expanded. We show the improved hardware correlation in Vmin yield and the improved slow corner read performance when the Vds-dependent variation is considered. Randy W. Mann, Meixiong Zhao, Oh Sung Kwon, Sanjay Parihar, Muhammed Ahosan Ul Karim, Jack M. Higman, Joseph Versaggi, Rick Carter |
IEEE Trans. Very Large Scale Integr. Syst. | 7 |
| 2019 | An Extrinsic Device and Leakage Mechanism in Advanced Bulk FinFET SRAMabstractA previously unrecognized vertical-extrinsic device in advanced 7-nm FinFET SRAM structures is identified and characterized for the first time. The ON-current for this vertical-extrinsic device is modulated by gate bias and exhibits a process-dependent threshold behavior. The ON-state of this parasitic device can exceed several nanoamperes and become the dominant mechanism in the static power of an SRAM array. Aggressively pushed ground rules used to achieve competitive SRAM density can result in exposure in FinFET-based SRAMs to this parasitic leakage path; n-Well and p-well dopant profiles, alignments, and dimensions must be carefully controlled to avoid this leakage mechanism in high-density FinFET SRAM arrays. Randy W. Mann, Meixiong Zhao, Sanjay Parihar, Qun Gao, Ankur Arya, Carl Radens, Shesh Mani Pandey, Joseph Versaggi, Jack M. Higman, Rick Carter |
IEEE Trans. Very Large Scale Integr. Syst. | 9 |
| 2018 | A Simplified Yield Model for SRAM Repair in Advanced Technology
Xiaoyuan Qi, Raymond J. Rosner, John Hopkins, Jack M. Higman, Rick Mewhirter, Aaron Sinnott, Binod Kumar G. Nair, Ishtiaq Ahsan, Mark Lagus |
IEEE Trans. Very Large Scale Integr. Syst. | 4 |
| 1993 | A numerical method to compute isotropic band models from anisotropic semiconductor band structuresabstractA numerical method for the determination of isotropic band models has been developed and applied to silicon. The resulting model accurately approximates both density of states and group velocity of the corresponding anisotropic band structure, thus providing an excellent agreement with both the collision and nonhomogeneous terms of the Boltzmann transport equation. The model, represented by a simple set of energy-wave vector tables, has been implemented in a Monte Carlo device simulator, but can also be extended to alternative methods for solving the Boltzmann equation. Simulation of homogeneous silicon shows a very good agreement with available experimental data. Comparison with results obtained using the complete anisotropic band structure, both in homogeneous and nonhomogeneous silicon devices, confirms the validity of the model.> Antonio Abramo, Franco Venturi, Enrico Sangiorgi, Jack M. Higman, Bruno Riccò |
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. | 4 |