This work introduces SENSOTERIC, a multi-partner project that aims at leveraging the properties of emerging Reconfigurable Field Effect Transistors (RFETs) to develop a sensor platform. RFETs will be used for a generic sensor interface and for a dedicated transducer element. In the first case, our goal is to develop an analog front-end interface that can be tuned at runtime to adapt to different environmental conditions and be used in a broad spectrum of applications. This feature shall be enabled by the polarity-control and negative differential resistance characteristics of the reconfigurable devices employed, that are co-integrable on industrial CMOS processes such as 22 nm FDSOI. In the second case, we want to exploit the intrinsic nature of these doping-free devices to yield better 1/f noise performances when compared to classic CMOS transducers. Moreover, the presence of un-gated areas on top of the channel of these devices makes them the perfect candidates to be functionalized. In this early-stage overview of the project, we will introduce the key features and the vision that make SENSOTERIC a unique contribution towards smart sensing solutions in environmental monitoring and healthcare.

The electrical engineering community, interested to develop bio-inspired circuits, approaching the efficiency of the neural networks, is searching passionately for accurate yet simple electronic neurons, or neuristors for short. In recent years, the advent of volatile memristor devices, typically referred to as threshold switches, which admit a negative differential resistance under suitable polarization, similarly as the sodium and potassium ion channels across neuronal axon membranes, has opened up new exciting opportunities in neuromorphic circuit design, enabling innovative analogue electronic cells, capable to reproduce closely the intricate dynamical behaviors of biological neurons without requiring a disproportionate use of resources. The study, presented in this manuscript, achieves an important milestone in this area of research, demonstrating, through a circuit design approach based upon concepts and techniques from Dynamical System Theory, how to leverage the rich dynamics of a threshold switch, capable to boost a periodic sine-wave current signal of infinitesimal amplitude, while acting as a source of local energy, when poised on a suitable bias point, lying along the negative differential resistance branch of the respective S-shaped DC current-voltage characteristic, to induce, one after the other, the three fundamental bifurcations, governing the evolution of an electrical voltage spike from birth to extinction via the All-to-None effect across a biological axon membrane under a reverse sweep in the net synaptic current, according to the fourth-order Hodgkin-Huxley neuron model, in a second-order three-element circuit of unprecedented simplicity, as the current, generated by a DC source, appearing in parallel to a linear capacitor as well as to the volatile locally-active memristor, is subject to a monotonic increase.

This manuscript sheds light into the fundamental importance of the Principles of Local Activity and Edge of Chaos for the future design of innovative circuits, which, employing biomimetic memristive devices, are ideally suited for the development of energy-efficient artificially-intelligent technical systems. The focus of the work is the design of a Second-Order Reactance-Less Oscillator, across which oscillations may develop if and only if at least one of its two different volatile thermally-activated memristor physical realizations is biased along a negative differential resistance branch of the respective DC locus, which turns it into a source of local energy. Very importantly, the proposed cell is first found to lock in the oscillatory mode out of a local Hopf Supercritical Bifurcation when its design parameters are chosen from the Edge of Chaos region, providing clear evidence for the high degree of excitability it acquires as a result.

While a number of measures have been proposed to protect the integrity of COS hardware, there are some inherent limitations from classical CMOS methods. Those already existing security methods, like logic locking can be improved with emerging technologies such as Reconfigurable Field Effect Transistors (RFETs). RFETs are a special type of doping-free, Schottky transistors which can work as a PFET or NFET as a function of biasing across its gates. In the present study we developed standard cell layouts for dynamic reconfigurable security cells based on three-independent-gated RFETs (TIG-RFETs). They layouts are compatible to an industrial 22nm FDSOI technology, feature the minimum pitch of the baseline technology, and obey all design rules necessary for co-integration. The designs enable a fair area comparison for RFET based digital application for the first time. Based on the sizing constraints from the layouts, a TCAD model of such a TIG-RFET is developed in Sentaurus TCAD to illustrate two biasing schemes for the application of TIGRFETs in this platform: reconfigurability with individual body-bias per transistor and reconfigurability at globally fixed body-bias. Due to the different operation options three variants of reconfigurable 2-XOR-XNOR and 2-NAND-NOR logic cells exhibiting different level of utility are designed. While the smallest dynamic 2-NAND-NOR gate needs roughly double the area of a CMOS 2-NAND gate from the reference library, the smallest 2-XOR-XNOR gate is only 20% larger than a CMOS 2-XOR. To quantify the area overhead for hardware security applications we calculated the number of logic locking gates that can be added per area overhead for a given circuit, here the ISCAS-85 C6288 benchmark circuit, as an example. Dynamic replacement based logic locking with TIG-RFETs shows to allow up to double the number of keys compared to classical CMOS logic locking per area overhead. Therefore, this work allows a realistic view on the application of RFETs in hardware security and its co-integrability along with some design constraints from an industrial PDK.

Power attacks are effective side-channel attacks (SCAs) that exploit weaknesses in the physical implementation of a cryptographic circuit to extract its secret information like encryption key. In recent years, emerging technologies have unlocked new possibilities in designing effective SCA countermeasures with less overhead. Reconfigurable Field-Effect Transistors (RFETs) are a type of beyond-CMOS technology that can be configured at run-time to act as an NFET or PFET transistor and provide two or more independent gates. These features make RFETs potent candidates for implementing hardware security techniques like logic locking and SCA countermeasures. In this paper, we propose REDCAP, a method to add randomness to the power traces of a circuit, employing compact reconfigurable RFET-based gates to make the design resilient against power SCAs. First, we explain the construction and control of reconfigurable blocks with isofunctional configurations inside the circuit. Then, we provide an algorithm to efficiently compose the reconfigurable blocks with other circuit parts to minimize the overhead and enable designers to determine the granularity of the reconfiguration. To evaluate our approach, we performed a Correlation Power Attack (CPA) on the S-box of the Piccolo and PRESENT, two lightweight cryptographic circuits, and the results show that REDCAP can highly enhance the resilience of the circuit against power SCAs.

This multi-partner-project contribution introduces the midway results of the Horizon 2020 FVLLMONTI project. In this project we develop a new and ultra-efficient class of ANN accelerators, the neural network compute cube$(N^{2}C^{2})$, which is specifically designed to execute complex machine learning tasks in a 3D technology, in order to provide the high computing power and ultra-high efficiency needed for future edgeAI applications. We showcase its effectiveness by targeting the challenging class of Transformer ANNs, tailored for Automatic Speech Recognition and Machine Translation, the two fundamental components of speech-to-speech translation. To gain the full benefit of the accelerator design, we develop disruptive vertical transistor technologies and execute design-technology-co-optimization (DTCO) loops from single device, to cell and compute cube level. Further, a hardware-software-co-optimization is executed, e.g. by compressing the executed speech recognition and translation models for energy efficient executing without substantial loss in precision.

The ability to detect correlated events in the environment is an important feat of biological neural networks. Neuromorphic computing strives to mimic this ability for efficient sensory processing. For this purpose, we propose a HfO2-based ferroelectric capacitor (FeCap)-complementary metal oxide semiconductor (CMOS) leaky integrate-and-fire (LIF) neuron able to detect highly correlated events exploiting two different temporal dynamics. The possibility to exploit two time constants increases the versatility of the neuron and its dynamic adaptation while offering a compact and elegant solution for detection of both transient and sustained coincidences. Moreover, the time constants are in biologically relevant time scales, which makes the neuron suitable to solve real-time tasks such as keyword spotting or sensory processing. The proposed FeCap-based LIF (FeLIF) neuron enriches the dynamic of a standard LIF neuron fostering the development of advanced event-based analog neuromorphic hardware.

Side-Channel Attacks (SCAs), which are always considered a severe threat to the security of the cryptographic circuits, today can also be employed to extract IP secrets and neural network models. Hence, developing novel security solutions at different design levels is crucial. In this paper, we explore recent countermeasures at the circuit, algorithmic, and microarchitecture levels. First, we explain how Reconfigurable Field-Effect Transistor (RFET), as a beyond CMOS technology, enables us to provide both IP and data protection against SCAs at the circuit level. Second, we investigate an automated method for generating masked circuits as an algorithmic solution, and then we review machine learning-based SCA detection mechanisms at the microarchitecture level. Finally, we discuss emerging threats of SCAs from the industrial point of view.

Reconfigurable transistors are a new emerging type of device, which offer the promise to improve the resistance of electronic components against know-how theft. In order to enable a product development of such an emerging device, a cross-layer design enablement strategy is needed, as emerging technologies are not necessarily compatible withstandard tools used in the industry. In ‘CirroStrato’, we aim on the development of such a complete flow enabling CMOS co-integration of reconfigurable transistors, ranging from process adjustments, device modeling, library characterization, physical and logical synthesis up towards sophisticated hardware security tests. In this multi-partner-project (MPP) paper, our aim is to elucidate the overall design enablement flow, as well as current research challenges on the individual stages.

Novel non-volatile memory devices based on ferroelectric thin films represent a promising emerging technology that is ideally suited for neuromorphic applications. The physical switching mechanism in such films is the nucleation and growth of ferroelectric domains. Since this has a strong dependence on both pulse width and voltage amplitude, it is important to use precise pulsing schemes for a thorough characterization of their behavior. In this work, we present an on-chip 120 dB programmable range pulse generator, that can generate pulse widths ranging from 10 ns to 10 ms ± 2.5% which eliminates the RLC bottleneck in the device characterisation setup. We describe the pulse generator design and show how the pulse width can be tuned with high accuracy, using Digital to Analog converters. Finally, we present experimental results measured from the circuit, fabricated using a standard 180 nm CMOS technology.

This paper proposes the derivation of a physics-based model of an analog memristive device realized as a bi-layer Al2O3/NB2O5stack. Memristive crossbar arrays implementing matrix-vector multiplications are a central building block of novel computing-in-memory architectures for artificial neural network and neuromorphic computing applications. The presented memristor shows analog, multi-level switching at high resistances without electroforming and is suitable for crossbar operations with low energy consumption. By including a graphical analysis method of the I-V curves obtained in a quasi-static approach, the dynamic behavior is analyzed with regard to ohmic and Poole-Frenkel behavior. Finally, a compact model, represented by an algebraic differential equation, is proposed and verified by fitting calculated solutions to experimental data.

Ferroelectric field effect transistor (FeFET) memory has shown the potential to meet the requirements of the growing need for fast, dense, low-power, and non-volatile memories. In this paper, we propose a memory architecture named crossed-AND (C-AND), in which each storage cell consists of a single ferroelectric transistor. The write operation is performed using different write schemes and different absolute voltages, to account for the asymmetric switching voltages of the FeFET. It enables writing an entire wordline in two consecutive cycles and prevents current and power through the channel of the transistor. During the read operation, the current and power are mostly sensed at a single selected device in each column. The read scheme additionally enables reading an entire word without read errors, even along long bitlines. Our Simulations demonstrate that, in comparison to the previously proposed AND architecture, the C-AND architecture diminishes read errors, reduces write disturbs, enables the usage of longer bitlines, and saves up to 2.92X in memory cell area.

The field of computer hardware stands at the verge of a revolution driven by recent breakthroughs in emerging nanodevices. “Nano Security” is a new Priority Program recently approved by DFG, the German Research Council. This initial-stage project initiative at the crossroads of nano-electronics and hardware-oriented security includes 11 projects with a total of 23 Principal Investigators from 18 German institutions. It considers the interplay between security and nano-electronics, focusing on a dichotomy which emerging nano-devices (and their architectural implications) have on system security. The projects within the Priority Program consider both: potential security threats and vulnerabilities stemming from novel nano-electronics, and innovative approaches to establishing and improving system security based on nano-electronics. This paper provides an overview of the Priority Program's overall philosophy and discusses the scientific objectives of its individual projects.

Ferroelectric tunneling junctions (FTJ) are considered to be the intrinsically most energy efficient memristors. In this work, specific electrical features of ferroelectric hafnium-zirconium oxide based FTJ devices are investigated. Moreover, the impact on the design of FTJ-based circuits for edge computing applications is discussed by means of two example circuits.

The main focus of this paper is the presentation of reliable methods for the determination of the optimum coloring of a graph, commonly known in the literature as vertex coloring problem. It has been shown that networks of capacitively coupled oscillators can be used to solve vertex coloring problems. In this paper we address the negative impact of an unbalanced number of couplings for the oscillators on the performance of the network and compensate for this non-uniform coupling structure by an adjustment in the network itself. The negative effect of the memristor device-to-device variability of the NbOxmemristor on the array functionality will be investigated and reduced via an adaptation of the memristor operating point. The main improvement in network performance is achieved by setting up a control procedure allowing the network to bypass the local solutions and converge to the global one. Two strategies inspired by global optimization algorithms will be proposed to allow the network to overcome sub-optimal solutions, and find the solution corresponding to the absolute minimum of a performance measure function of the vertex coloring problem.

Recently, memory and logic were brought into closer vicinity by introducing Logic-in-Memory circuits based on ferroelectric FETs (FeFET), where the FeFET not only stores logic values in its ferroelectric layer, but also performs logic operations of externally applied inputs with these internally stored values. As one reason for using these structures is to overcome the von-Neumann bottleneck, their logic readout gained a lot of attention, while the storage of the calculated outputs was neglected. In this paper, we propose to utilize two intercoupled memory arrays for this purpose. Between these, three operation modes are possible: pure memory operation, a passing of bits through the structure (logic mode), and conducting a logic operation in cells of the first memory array, whose result is stored in the cells of the second memory array, directly combining the logic and memory capability of these structures. For the latter, we suggest a suitable operation scheme. Electrical measurements of 28nm HKMG FeFET test structures based on hafnium oxide (HfO2) confirm the feasibility of the proposed logic/memory mixed mode.

An early evaluation in terms of circuit design is essential in order to assess the feasibility and practicability aspects for emerging nanotechnologies. Reconfigurable nanotechnologies, such as silicon or germanium nanowire-based reconfigurable field-effect transistors, hold great promise as suitable primitives for enabling multiple functionalities per computational unit. However, contemporary CMOS circuit designs when applied directly with this emerging nanotechnology often result in suboptimal designs. For example, 31% and 71% larger area was obtained for our two exemplary designs. Hence, new approaches delivering tailored circuit designs are needed to truly tap the exciting feature set of these reconfigurable nanotechnologies. To this effect, we propose six functionally enhanced logic gates based on a reconfigurable nanowire technology and employ these logic gates in efficient circuit designs. We carry out a detailed comparative study for a reconfigurable multifunctional circuit, which shows better normalized circuit delay (20.14%), area (32.40%), and activity as the power metric (40%) while exhibiting similar functionality as compared with the CMOS reference design. We further propose a novel design for a 1-bit arithmetic logic unit-based on silicon nanowire reconfigurable FETs with the area, normalized circuit delay, and activity gains of 30%, 34%, and 36%, respectively, as compared with the contemporary CMOS version.

In this paper, we consider devices, circuits, and systems comprised of transistors with integrated ferroelectrics. Said structures are actively being considered by various semiconductor manufacturers as they can address a large and unique design space. Transistors with integrated ferroelectrics could (i) enable a better switch (i.e., offer steeper subthreshold swings), (ii) are CMOS compatible, (iii) have multiple operating modes (i.e., I-V characteristics can also enable compact, 1-transistor, non-volatile storage elements, as well as analog synaptic behavior), and (iv) have been experimentally demonstrated (i.e., with respect to all of the aforementioned operating modes). These device-level characteristics offer unique opportunities at the circuit, architectural, and system-level, and are considered here from device, circuit/architecture, and foundry-level perspectives.

Logic-in-memory circuits promise to overcome the von-Neumann bottleneck, which constitutes one of the limiting factors to data throughput and power consumption of electronic devices. In the following we present four-input logic gates based on only two ferroelectric FETs (FeFETs) with hafnium oxide as the ferroelectric material. By utilizing two complementary inputs, a XOR and a XNOR gate are created. The use of only two FeFETs results in a compact and nonvolatile design. This realization, moreover, directly couples the memory and logic function of the FeFET. The feasibility of the proposed structures is revealed by electrical measurements of HKMG FeFET memory arrays manufactured in 28nm technology.

Edge computing requires highly energy efficient microprocessor units with embedded non-volatile memories to process data at IoT sensor nodes. Ferroelectric non-volatile memory devices are fast, low power and high endurance, and could greatly enhance energy-efficiency and allow flexibility for finer grain logic and memory. This paper will describe the basics of ferroelectric devices for both hysteretic (non-volatile memory) and negative capacitance (steep slope switch) devices, and then project how these can be used in low-power logic cell architectures and fine-grain logic-in-memory (LiM) circuits.

Silicon nanowire reconfigurable field effect transistors (SiNW RFETs) abolish the physical separation of n-type and p-type transistors by taking up both roles in a configurable way within a doping-free technology. However, the potential of transistor-level reconfigurability has not been demonstrated in larger circuits, so far. In this paper, we present first steps to a new compact and efficient design of combinational circuits by employing transistor-level reconfiguration. We contribute new basic gates realized with silicon nanowires, such as 2/3-XOR and MUX gates. Exemplifying our approach with 4-bit, 8-bit and 16-bit conditional carry adders, we were able to reduce the number of transistors to almost one half. With our current case study we show that SiNW technology can reduce the required chip area by 16 despite larger size of the individual transistor, and improve circuit speed by 26%.

Resistive switching devices have a high potential for nonvolatile memories and circuit applications. This paper gives a review of the different switching modes in niobium oxide. Abrupt memory switching, threshold switching with or without memory switching and analog switching can be obtained by controlling the stoichiometry of the layer stack either with the use of reactive electrodes, by reactive sputtering with different argon to oxygen ratios or by ion implantation.

In this paper1a stability analysis sheds light into aspects of memristor circuit design, revealing a circuit theoretic technique for the stabilization of the NDR portion of the device DC characteristic. This type of studies supports the work of designers exploring memristor potential in electronics. Concepts from nonlinear dynamics theory allow us to gain a deep understanding of the dynamics of our locally-active memristor. The analysis provides hints on how to design an oscillator where limit-cycle behavior emerges from the locally-active threshold switching of the memristor, as theoretically proved here.

Reconfigurable fine-grain electronics target an increase in the number of integrated logic functions per chip by enhancing the functionality at the device level and by implementing a compact and technologically simple hardware platform. Here we study a promising realization approach by employing reconfigurable nanowire transistors (RFETs) as the multifunctional building-blocks to be integrated therein. RFETs merge the electrical characteristics of unipolar n- and p- type FETs into a single universal device. The switch comprises four terminals, where three of them act as the conventional FET electrodes and the fourth acts as an electric select signal to dynamically program the desired switch type. The transistor consists of two independent charge carrier injection valves as represented by two gated Schottky junctions integrated within an intrinsic silicon nanowire. Radial compressive strain applied to the channel is used as a scalable method to adjust n- and p-FET currents to each other, thereby enabling complementary logic circuits. Simple but relevant examples for the reconfiguration of complete gates will be given, demonstrating the potential of this technology.