An Electromigration and Thermal Model of Power Wires for a Priori High-Level Reliability Prediction

In this paper, a simple power-distribution electrothermal model including the interconnect self-heating is used together with a statistical model of average and rms currents of functional blocks and a high-level model of fanout distribution and interconnect wirelength. Following the 2001 SIA roadmap projections, we are able to predict a priori that the minimum width that satisfies the electromigration constraints does not scale like the minimum metal pitch in future technology nodes. As a consequence, the percentage of chip area covered by power lines is expected to increase at the expense of wiring resources unless proper countermeasures are taken. Some possible solutions are proposed in the paper

Toward bio-inspired information processing with networks of nano-scale switching elements

Unconventional computing explores multi-scale platforms connecting molecular-scale devices into networks for the development of scalable neuromorphic architectures, often based on new materials and components with new functionalities. We review some work investigating the functionalities of locally connected networks of different types of switching elements as computational substrates. In particular, we discuss reservoir computing with networks of nonlinear nanoscale components. In usual neuromorphic paradigms, the network synaptic weights are adjusted as a result of a training/learning process. In reservoir computing, the non-linear network acts as a dynamical system mixing and spreading the input signals over a large state space, and only a readout layer is trained. We illustrate the most important concepts with a few examples, featuring memristor networks with time-dependent and history dependent resistances

Analog/RF Circuit Design Techniques for Nanometerscale IC Technologies

CMOS evolution introduces several problems in analog design. Gate-leakage mismatch exceeds conventional matching tolerances requiring active cancellation techniques or alternative architectures. One strategy to deal with the use of lower supply voltages is to operate critical parts at higher supply voltages, by exploiting combinations of thin- and thick-oxide transistors. Alternatively, low voltage circuit techniques are successfully developed. In order to benefit from nanometer scale CMOS technology, more functionality is shifted to the digital domain, including parts of the RF circuits. At the same time, analog control for digital and digital control for analog emerges to deal with current and upcoming imperfections

Charge Trap Transistors (CTT): Turning Logic Transistors into Embedded Non-Volatile Memory for Advanced High-k/Metal Gate CMOS Technologies

While need for embedded non-volatile memory (eNVM) in modern computing systems continues to grow rapidly, the options have been limited due to integration and scaling challenges as well as operational voltage incompatibilities. Introduced in this work is a unique multi-time programmable memory (MTPM) solution for advanced high-k/metal-gate (HKMG) CMOS technologies which turns as-fabricated standard logic transistors into eNVM elements, without the need for any process adders or additional masks. These logic transistors, when employed as eNVM elements, are dubbed “Charge Trap Transistors” (CTTs). The fundamental device physics, principles of operation, and technological breakthroughs required for employing logic transistors as eNVM are presented. Implementation of CTT eNVM in 32 nm, 22 nm, 14 nm, and 7 nm production technologies has been realized and demonstrated in this work. The emerging memory technology landscape and the space that the CTT technology occupies therein are examined.The motivation behind this work is to develop an eNVM technology that is completely process/mask-free, multi-time programmable, operable at low/logic-compatible voltages, scalable, and secure. The CTT technology satisfies all of the aforementioned criteria. CTTs offer a data retention lifetime of > 10 years at 125 �C and an operation temperature range of -55�-125� C. Hardware results demonstrate an endurance of > 10^4 program/erase cycles which is more than adequate for most embedded applications. Hardware security enhancement, on-chip reconfigurable encryption, firmware, BIOS, chip ID, redundancy, repair at wafer and module test and in the field, performance tailoring, and chip configuration are a few of the applications of CTT eNVM. Moreover, the CTT array in its native (unprogrammed) state measures very well as an entropy source for potential PUF (Physically Unclonable Function) applications such as identification, authentication, anti-counterfeiting, secure boot, and cryptographic IP. In addition to the numerous digital applications, CTTs can also be utilized as an analog memory for applications like neuromorphic computing for machine learning (ML) and artificial intelligence (AI)

Characterization of self-heating effects and assessment of its impact on reliability in finfet technology

The systematically growing power (heat) dissipation in CMOS transistors with each successive technology node is reaching levels which could impact its reliable operation. The emergence of technologies such as bulk/SOI FinFETs has dramatically confined the heat in the device channel due to its vertical geometry and it is expected to further exacerbate with gate-all-around transistors. This work studies heat generation in the channel of semiconductor devices and measures its dissipation by means of wafer level characterization and predictive thermal simulation. The experimental work is based on several existing device thermometry techniques to which additional layout improvements are made in state of the art bulk FinFET and SOI FinFET 14nm technology nodes. The sensors produce excellent matching results which are confirmed through TCAD thermal simulation, differences between sensor types are quantified and error bars on measurements are established. The lateral heat transport measurements determine that heat from the source is mostly dissipated at a distance of 1µm and 1.5µm in bulk FinFET and SOI FinFET, respectively. Heat additivity is successfully confirmed to prove and highlight the fact that the whole system needs to be considered when performing thermal analysis. Furthermore, an investigation is devoted to study self-heating with different layout densities by varying the number of fins and fingers per active region (RX). Fin thermal resistance is measured at different ambient temperatures to show its variation of up to 70% between -40°C to 175°C. Therefore, the Si fin has a more dominant effect in heat transport and its varying thermal conductivity should be taken into account. The effect of ambient temperature on self-heating measurement is confirmed by supplying heat through thermal chuck and adjacent heater devices themselves. Motivation for this work is the continuous evolution of the transistor geometry and use of exotic materials, which in the recent technology nodes made heat removal more challenging. This poses reliability and performance concerns. Therefore, this work studies the impact of self-heating on reliability testing at DC conditions as well as realistic CMOS logic operating (AC) conditions. Front-end-of-line (FEOL) reliability mechanisms, such as hot carrier injection (HCI) and non-uniform time dependent dielectric breakdown (TDDB), are studied to show that self-heating effects can impact measurement results and recommendations are given on how to mitigate them. By performing an HCI stress at moderate bias conditions, this dissertation shows that the laborious techniques of heat subtraction are no longer necessary. Self-heating is also studied at more realistic device switching conditions by utilizing ring oscillators with several densities and stage counts to show that self-heating is considerably lower compared to constant voltage stress conditions and degradation is not distinguishable

Physical and Electrical Performance Limits of High-Speed SiGeC HBTs-Part II: Lateral Scaling

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Modeling of Thermally Aware Carbon Nanotube and Graphene Based Post CMOS VLSI Interconnect

This work studies various emerging reduced dimensional materials for very large-scale integration (VLSI) interconnects. The prime motivation of this work is to find an alternative to the existing Cu-based interconnect for post-CMOS technology nodes with an emphasis on thermal stability. Starting from the material modeling, this work includes material characterization, exploration of electronic properties, vibrational properties and to analyze performance as a VLSI interconnect. Using state of the art density functional theories (DFT) one-dimensional and two-dimensional materials were designed for exploring their electronic structures, transport properties and their circuit behaviors. Primarily carbon nanotube (CNT), graphene and graphene/copper based interconnects were studied in this work. Being reduced dimensional materials the charge carriers in CNT(1-D) and in graphene (2-D) are quantum mechanically confined as a result of this free electron approximation fails to explain their electronic properties. For same reason Drude theory of metals fails to explain electronic transport phenomena. In this work Landauer transport theories using non-equilibrium Green function (NEGF) formalism was used for carrier transport calculation. For phonon transport studies, phenomenological Fourier’s heat diffusion equation was used for longer interconnects. Semi-classical BTE and Landauer transport for phonons were used in cases of ballistic phonon transport regime. After obtaining self-consistent electronic and thermal transport coefficients, an equivalent circuit model is proposed to analyze interconnects’ electrical performances. For material studies, CNTs of different variants were analyzed and compared with existing copper based interconnects and were found to be auspicious contenders with integrational challenges. Although, Cu based interconnect is still outperforming other emerging materials in terms of the energy-delay product (1.72 fJ-ps), considering the electromigration resistance graphene Cu hybrid interconnect proposed in this dissertation performs better. Ten times more electromigration resistance is achievable with the cost of only 30% increase in energy-delay product. This unique property of this proposed interconnect also outperforms other studied alternative materials such as multiwalled CNT, single walled CNT and their bundles

Design for Reliability and Low Power in Emerging Technologies

Die fortlaufende Verkleinerung von Transistor-Strukturgrößen ist einer der wichtigsten Antreiber für das Wachstum in der Halbleitertechnologiebranche. Seit Jahrzehnten erhöhen sich sowohl Integrationsdichte als auch Komplexität von Schaltkreisen und zeigen damit einen fortlaufenden Trend, der sich über alle modernen Fertigungsgrößen erstreckt. Bislang ging das Verkleinern von Transistoren mit einer Verringerung der Versorgungsspannung einher, was zu einer Reduktion der Leistungsaufnahme führte und damit eine gleichbleibenden Leistungsdichte sicherstellte. Doch mit dem Beginn von Strukturgrößen im Nanometerbreich verlangsamte sich die fortlaufende Skalierung. Viele Schwierigkeiten, sowie das Erreichen von physikalischen Grenzen in der Fertigung und Nicht-Idealitäten beim Skalieren der Versorgungsspannung, führten zu einer Zunahme der Leistungsdichte und, damit einhergehend, zu erschwerten Problemen bei der Sicherstellung der Zuverlässigkeit. Dazu zählen, unter anderem, Alterungseffekte in Transistoren sowie übermäßige Hitzeentwicklung, nicht zuletzt durch stärkeres Auftreten von Selbsterhitzungseffekten innerhalb der Transistoren. Damit solche Probleme die Zuverlässigkeit eines Schaltkreises nicht gefährden, werden die internen Signallaufzeiten üblicherweise sehr pessimistisch kalkuliert. Durch den so entstandenen zeitlichen Sicherheitsabstand wird die korrekte Funktionalität des Schaltkreises sichergestellt, allerdings auf Kosten der Performance. Alternativ kann die Zuverlässigkeit des Schaltkreises auch durch andere Techniken erhöht werden, wie zum Beispiel durch Null-Temperatur-Koeffizienten oder Approximate Computing. Wenngleich diese Techniken einen Großteil des üblichen zeitlichen Sicherheitsabstandes einsparen können, bergen sie dennoch weitere Konsequenzen und Kompromisse. Bleibende Herausforderungen bei der Skalierung von CMOS Technologien führen außerdem zu einem verstärkten Fokus auf vielversprechende Zukunftstechnologien. Ein Beispiel dafür ist der Negative Capacitance Field-Effect Transistor (NCFET), der eine beachtenswerte Leistungssteigerung gegenüber herkömmlichen FinFET Transistoren aufweist und diese in Zukunft ersetzen könnte. Des Weiteren setzen Entwickler von Schaltkreisen vermehrt auf komplexe, parallele Strukturen statt auf höhere Taktfrequenzen. Diese komplexen Modelle benötigen moderne Power-Management Techniken in allen Aspekten des Designs. Mit dem Auftreten von neuartigen Transistortechnologien (wie zum Beispiel NCFET) müssen diese Power-Management Techniken neu bewertet werden, da sich Abhängigkeiten und Verhältnismäßigkeiten ändern. Diese Arbeit präsentiert neue Herangehensweisen, sowohl zur Analyse als auch zur Modellierung der Zuverlässigkeit von Schaltkreisen, um zuvor genannte Herausforderungen auf mehreren Designebenen anzugehen. Diese Herangehensweisen unterteilen sich in konventionelle Techniken ((a), (b), (c) und (d)) und unkonventionelle Techniken ((e) und (f)), wie folgt: $\textbf{(a)}$ Analyse von Leistungszunahmen in Zusammenhang mit der Maximierung von Leistungseffizienz beim Betrieb nahe der Transistor Schwellspannung, insbesondere am optimalen Leistungspunkt. Das genaue Ermitteln eines solchen optimalen Leistungspunkts ist eine besondere Herausforderung bei Multicore Designs, da dieser sich mit den jeweiligen Optimierungszielsetzungen und der Arbeitsbelastung verschiebt. $\textbf{(b)}$ Aufzeigen versteckter Interdependenzen zwischen Alterungseffekten bei Transistoren und Schwankungen in der Versorgungsspannung durch „IR-drops“. Eine neuartige Technik wird vorgestellt, die sowohl Über- als auch Unterschätzungen bei der Ermittlung des zeitlichen Sicherheitsabstands vermeidet und folglich den kleinsten, dennoch ausreichenden Sicherheitsabstand ermittelt. $\textbf{(c)}$ Eindämmung von Alterungseffekten bei Transistoren durch „Graceful Approximation“, eine Technik zur Erhöhung der Taktfrequenz bei Bedarf. Der durch Alterungseffekte bedingte zeitlich Sicherheitsabstand wird durch Approximate Computing Techniken ersetzt. Des Weiteren wird Quantisierung verwendet um ausreichend Genauigkeit bei den Berechnungen zu gewährleisten. $\textbf{(d)}$ Eindämmung von temperaturabhängigen Verschlechterungen der Signallaufzeit durch den Betrieb nahe des Null-Temperatur Koeffizienten (N-ZTC). Der Betrieb bei N-ZTC minimiert temperaturbedingte Abweichungen der Performance und der Leistungsaufnahme. Qualitative und quantitative Vergleiche gegenüber dem traditionellen zeitlichen Sicherheitsabstand werden präsentiert. $\textbf{(e)}$ Modellierung von Power-Management Techniken für NCFET-basierte Prozessoren. Die NCFET Technologie hat einzigartige Eigenschaften, durch die herkömmliche Verfahren zur Spannungs- und Frequenzskalierungen zur Laufzeit (DVS/DVFS) suboptimale Ergebnisse erzielen. Dies erfordert NCFET-spezifische Power-Management Techniken, die in dieser Arbeit vorgestellt werden. $\textbf{(f)}$ Vorstellung eines neuartigen heterogenen Multicore Designs in NCFET Technologie. Das Design beinhaltet identische Kerne; Heterogenität entsteht durch die Anwendung der individuellen, optimalen Konfiguration der Kerne. Amdahls Gesetz wird erweitert, um neue system- und anwendungsspezifische Parameter abzudecken und die Vorzüge des neuen Designs aufzuzeigen. Die Auswertungen der vorgestellten Techniken werden mithilfe von Implementierungen und Simulationen auf Schaltkreisebene (gate-level) durchgeführt. Des Weiteren werden Simulatoren auf Systemebene (system-level) verwendet, um Multicore Designs zu implementieren und zu simulieren. Zur Validierung und Bewertung der Effektivität gegenüber dem Stand der Technik werden analytische, gate-level und system-level Simulationen herangezogen, die sowohl synthetische als auch reale Anwendungen betrachten