Embedding Security into Ferroelectric FET Array via In-Situ Memory Operation

Non-volatile memories (NVMs) have the potential to reshape next-generation memory systems because of their promising properties of near-zero leakage power consumption, high density and non-volatility. However, NVMs also face critical security threats that exploit the non-volatile property. Compared to volatile memory, the capability of retaining data even after power down makes NVM more vulnerable. Existing solutions to address the security issues of NVMs are mainly based on Advanced Encryption Standard (AES), which incurs significant performance and power overhead. In this paper, we propose a lightweight memory encryption/decryption scheme by exploiting in-situ memory operations with negligible overhead. To validate the feasibility of the encryption/decryption scheme, device-level and array-level experiments are performed using ferroelectric field effect transistor (FeFET) as an example NVM without loss of generality. Besides, a comprehensive evaluation is performed on a 128x128 FeFET AND-type memory array in terms of area, latency, power and throughput. Compared with the AES-based scheme, our scheme shows around 22.6x/14.1x increase in encryption/decryption throughput with negligible power penalty. Furthermore, we evaluate the performance of our scheme over the AES-based scheme when deploying different neural network workloads. Our scheme yields significant latency reduction by 90% on average for encryption and decryption processes

Ultra Low Power Design for Digital CMOS Circuits Operating Near Threshold

Circuits operating in the subthreshold region are synonymous to low energy operation. However, the penalty in performance is colossal. In this paper, we investigate how designing in moderate inversion region recuperates some of that lost performance, while remaining very near to the minimum energy point. An power based minimum energy delay modeling that is continuous over the weak, moderate, and strong inversion regions is presented. The effect of supply voltage and device sizing on the minimum energy and performance is determined. The proposed model is utilized to design a temperature to time generator at 32nm technology node asthe application of the proposed model

In-Memory Computing by Using Nano-ionic Memristive Devices

By reaching to the CMOS scaling limitation based on the Moore’s law and due to the increasing disparity between the processing units and memory performance, the quest is continued to find a suitable alternative to replace the conventional technology. The recently discovered two terminal element, memristor, is believed to be one of the most promising candidates for future very large scale integrated systems. This thesis is comprised of two main parts, (Part I) modeling the memristor devices, and (Part II) memristive computing. The first part is presented in one chapter and the second part of the thesis contains five chapters. The basics and fundamentals regarding the memristor functionality and memristive computing are presented in the introduction chapter. A brief detail of these two main parts is as follows: Part I: Modeling- This part presents an accurate model based on the charge transport mechanisms for nanoionic memristor devices. The main current mechanism in metal/insulator/metal (MIM) structures are assessed, a physic-based model is proposed and a SPICE model is presented and tested for four different fabricated devices. An accuracy comparison is done for various models for Ag/TiO2/ITO fabricated device. Also, the functionality of the model is tested for various input signals. Part II: Memristive computing- Memristive computing is about utilizing memristor to perform computational tasks. This part of the thesis is divided into neuromorphic, analog and digital computing schemes with memristor devices. – Neuromorphic computing- Two chapters of this thesis are about biologicalinspired memristive neural networks using STDP-based learning mechanism. The memristive implementation of two well-known spiking neuron models, Hudgkin-Huxley and Morris-Lecar, are assessed and utilized in the proposed memristive network. The synaptic connections are also memristor devices in this design. Unsupervised pattern classification tasks are done to ensure the right functionality of the system. – Analog computing- Memristor has analog memory property as it can be programmed to different memristance values. A novel memristive analog adder is designed by Continuous Valued Number System (CVNS) scheme and its circuit is comprised of addition and modulo blocks. The proposed analog adder design is explained and its functionality is tested for various numbers. It is shown that the CVNS scheme is compatible with memristive design and the environment resolution can be adjusted by the memristance ratio of the memristor devices. – Digital computing- Two chapters are dedicated for digital computing. In the first one, a development over IMPLY-based logic with memristor is provided to implement a 4:2 compressor circuit. In the second chapter, A novel resistive over a novel mirrored memristive crossbar platform. Different logic gates are designed with the proposed memristive logic method and the simulations are provided with Cadence to prove the functionality of the logic. The logic implementation over a mirrored memristive crossbars is also assessed

Design of variability compensation architectures of digital circuits with adaptive body bias

The most critical concern in circuit is to achieve high level of performance with very tight power constraint. As the high performance circuits moved beyond 45nm technology one of the major issues is the parameter variation i.e. deviation in process, temperature and voltage (PVT) values from nominal specifications. A key process parameter subject to variation is the transistor threshold voltage (Vth) which impacts two important parameters: frequency and leakage power. Although the degradation can be compensated by the worstcase scenario based over-design approach, it induces remarkable power and performance overhead which is undesirable in tightly constrained designs. Dynamic voltage scaling (DVS) is a more power efficient approach, however its coarse granularity implies difficulty in handling fine grained variations. These factors have contributed to the growing interest in power aware robust circuit design. We propose a variability compensation architecture with adaptive body bias, for low power applications using 28nm FDSOI technology. The basic approach is based on a dynamic prediction and prevention of possible circuit timing errors. In our proposal we are using a Canary logic technique that enables the typical-case design. The body bias generation is based on a DLL type method which uses an external reference generator and voltage controlled delay line (VCDL) to generate the forward body bias (FBB) control signals. The adaptive technique is used for dynamic detection and correction of path failures in digital designs due to PVT variations. Instead of tuning the supply voltage, the key idea of the design approach is to tune the body bias voltage bymonitoring the error rate during operation. The FBB increases operating speed with an overhead in leakage power

Benchmarking the screen-grid field effect transistor (SGrFET) for digital applications

Continuous scaling of CMOS technology has now reached a state of evolution, therefore, novel device structures and new materials have been proposed for this purpose. The Screen- Grid field Effect Transistor is introduced as a as a novel device structure that takes advantage of several innovative aspects of the FinFET while introducing new geometrical feature to improve a FET device performance. The idea is to design a FET which is as small as possible without down-scaling issues, at the same time satisfying optimum device performance for both analogue and digital applications. The analogue operation of the SGrFET shows some promising results which make it interesting to continue the investigation on SGrFET for digital applications. The SGrFET addresses some of the concerns of scaled CMOS such as Drain Induce Barrier Lowering and sub-threshold slope, by offering the superior short channel control. In this work in order to evaluate SGrFET performance, the proposed device compared to the classical MOSFET and provides comprehensive benchmarking with finFETs. Both AC and DC simulations are presented using TaurusTM and MediciTM simulators which are commercially available via Synopsis. Initial investigation on the novel device with the single gate structure is carried out. The multi-geometrical characteristic of the proposed device is used to reduce parasitic capacitance and increase ION/IOFF ratio to improve device performance in terms of switching characteristic in different circuit structures. Using TaurusTM AC simulation, a small signal circuit is introduced for SGrFET and evaluated using both extracted small signal elements from TaurusTM and Y-parameter extraction. The SGrFET allows for the unique behavioural characteristics of an independent-gate device. Different configurations of double-gate device are introduced and benchmark against the finFET serving as a double gate device. Five different logic circuits, the complementary and N-inverter, the NOR, NAND and XOR, and controllable Current Mirror circuits are simulated with finFET and SGrFET and their performance compared. Some digital key merits are extracted for both finFET and SGrFET such as power dissipation, noise margin and switching speed to compare the devices under the investigation performance against each other. It is shown that using multi-geometrical feature in SGrFET together with its multi-gate operation can greatly decrease the number of device needed for the logic function without speed degradation and it can be used as a potential candidate in mix-circuit configuration as a multi-gate device. The initial fabrication steps of the novel device explained together with some in-house fabrication process using E-Beam lithography. The fabricated SGrFET is characterised via electrical measurements and used in a circuit configuration