Robustness Comparison of Emerging Devices for Portable Applications

Extensive development in portable devices imposes pressing need for designing VLSI circuits with ultralow power (ULP) consumption. Subthreshold operating region is found to be an attractive solution for achieving ultralow power. However, it limits the circuit speed due to use of parasitic leakage current as drive current. Maintaining power dissipation at ultralow level with enhanced speed will further broaden the application area of subthreshold circuits even towards the field programmable gate arrays and real-time portable domain. Operating the Si-MOSFET in subthreshold regions degrades the circuit performance in terms of speed and also increases the well-designed circuit parameter spreading due to process, voltage, and temperature variations. This may cause the subthreshold circuit failure at very low supply voltage. It is essential to examine the robustness of most emerging devices against PVT variations. Therefore, this paper investigates and compares the performance of most promising upcoming devices like CNFET and DG FinFET in subthreshold regions. Effect of PVT variation on performance of CNFET and DG FinFET has been explored and it is found that CNFET is more robust than DG-FinFET under subthreshold conditions against PVT variations

EMERGING COMPUTING BASED NOVEL SOLUTIONS FOR DESIGN OF LOW POWER CIRCUITS

The growing applications for IoT devices have caused an increase in the study of low power consuming circuit design to meet the requirement of devices to operate for various months without external power supply. Scaling down the conventional CMOS causes various complications to design due to CMOS properties, therefore various non-conventional CMOS design techniques are being proposed that overcome the limitations. This thesis focuses on some of those emerging and novel low power design technique namely Adiabatic logic and low power devices like Magnetic Tunnel Junction (MTJ) and Carbon Nanotube Field Effect transistor (CNFET). Circuits that are used for large computations (multipliers, encryption engines) that amount to maximum part of power consumption in a whole chip are designed using these novel low power techniques

Design of Adiabatic MTJ-CMOS Hybrid Circuits

Low-power designs are a necessity with the increasing demand of portable devices which are battery operated. In many of such devices the operational speed is not as important as battery life. Logic-in-memory structures using nano-devices and adiabatic designs are two methods to reduce the static and dynamic power consumption respectively. Magnetic tunnel junction (MTJ) is an emerging technology which has many advantages when used in logic-in-memory structures in conjunction with CMOS. In this paper, we introduce a novel adiabatic hybrid MTJ/CMOS structure which is used to design AND/NAND, XOR/XNOR and 1-bit full adder circuits. We simulate the designs using HSPICE with 32nm CMOS technology and compared it with a non-adiabatic hybrid MTJ/CMOS circuits. The proposed adiabatic MTJ/CMOS full adder design has more than 7 times lower power consumtion compared to the previous MTJ/CMOS full adder

Emerging physical unclonable functions with nanotechnology

Physical unclonable functions (PUFs) are increasingly used for authentication and identification applications as well as the cryptographic key generation. An important feature of a PUF is the reliance on minute random variations in the fabricated hardware to derive a trusted random key. Currently, most PUF designs focus on exploiting process variations intrinsic to the CMOS technology. In recent years, progress in emerging nanoelectronic devices has demonstrated an increase in variation as a consequence of scaling down to the nanoregion. To date, emerging PUFs with nanotechnology have not been fully established, but they are expected to emerge. Initial research in this area aims to provide security primitives for emerging integrated circuits with nanotechnology. In this paper, we review emerging nanotechnology-based PUFs

Approximate Compressors for Multiplication

At nanometric scales, approximate computing is an attractive prototype used for digital processing. Despite providing less accurate results, approximate computing is preferred over exact computing as it provides a fast & significant output along with low power consumption. Designing of an efficient multiplier has always been a challenge for VLSI designers as multipliers have a large area, long latency consumes considerable power. For this inconvenience compressor with low latency, low power consumption and reduced stages of the product are designed. This paper proposes two methods to design high order compressors (8:4 & 9:4) (i) Using adders (half & full) (ii) Using multiplexers in Cadence VIRTUOSO tool using 45nm technology. Extensive simulation results show that the proposed designs achieve significant accuracy improvement along with power, area, and delay reductions compared to previous compressor designs

Hardware security design from circuits to systems

The security of hardware implementations is of considerable importance, as even the most secure and carefully analyzed algorithms and protocols can be vulnerable in their hardware realization. For instance, numerous successful attacks have been presented against the Advanced Encryption Standard, which is approved for top secret information by the National Security Agency. There are numerous challenges for hardware security, ranging from critical power and resource constraints in sensor networks to scalability and automation for large Internet of Things (IoT) applications. The physically unclonable function (PUF) is a promising building block for hardware security, as it exposes a device-unique challenge-response behavior which depends on process variations in fabrication. It can be used in a variety of applications including random number generation, authentication, fingerprinting, and encryption. The primary concerns for PUF are reliability in presence of environmental variations, area and power overhead, and process-dependent randomness of the challenge-response behavior. Carbon nanotube field-effect transistors (CNFETs) have been shown to have excellent electrical and unique physical characteristics. They are a promising candidate to replace silicon transistors in future very large scale integration (VLSI) designs. We present the Carbon Nanotube PUF (CNPUF), which is the first PUF design that takes advantage of unique CNFET characteristics. CNPUF achieves higher reliability against environmental variations and increases the resistance against modeling attacks. Furthermore, CNPUF has a considerable power and energy reduction in comparison to previous ultra-low power PUF designs of 89.6% and 98%, respectively. Moreover, CNPUF allows a power-security tradeoff in an extended design, which can greatly increase the resilience against modeling attacks. Despite increasing focus on defenses against physical attacks, consistent security oriented design of embedded systems remains a challenge, as most formalizations and security models are concerned with isolated physical components or a high-level concept. Therefore, we build on existing work on hardware security and provide four contributions to system-oriented physical defense: (i) A system-level security model to overcome the chasm between secure components and requirements of high-level protocols; this enables synergy between component-oriented security formalizations and theoretically proven protocols. (ii) An analysis of current practices in PUF protocols using the proposed system-level security model; we identify significant issues and expose assumptions that require costly security techniques. (iii) A System-of-PUF (SoP) that utilizes the large PUF design-space to achieve security requirements with minimal resource utilization; SoP requires 64% less gate-equivalent units than recently published schemes. (iv) A multilevel authentication protocol based on SoP which is validated using our system-level security model and which overcomes current vulnerabilities. Furthermore, this protocol offers breach recognition and recovery. Unpredictability and reliability are core requirements of PUFs: unpredictability implies that an adversary cannot sufficiently predict future responses from previous observations. Reliability is important as it increases the reproducibility of PUF responses and hence allows validation of expected responses. However, advanced machine-learning algorithms have been shown to be a significant threat to the practical validity of PUFs, as they can accurately model PUF behavior. The most effective technique was shown to be the XOR-based combination of multiple PUFs, but as this approach drastically reduces reliability, it does not scale well against software-based machine-learning attacks. We analyze threats to PUF security and propose PolyPUF, a scalable and secure architecture to introduce polymorphic PUF behavior. This architecture significantly increases model-building resistivity while maintaining reliability. An extensive experimental evaluation and comparison demonstrate that the PolyPUF architecture can secure various PUF configurations and is the only evaluated approach to withstand highly complex neural network machine-learning attacks. Furthermore, we show that PolyPUF consumes less energy and has less implementation overhead in comparison to lightweight reference architectures. Emerging technologies such as the Internet of Things (IoT) heavily rely on hardware security for data and privacy protection. The outsourcing of integrated circuit (IC) fabrication introduces diverse threat vectors with different characteristics, such that the security of each device has unique focal points. Hardware Trojan horses (HTH) are a significant threat for IoT devices as they process security critical information with limited resources. HTH for information leakage are particularly difficult to detect as they have minimal footprint. Moreover, constantly increasing integration complexity requires automatic synthesis to maintain the pace of innovation. We introduce the first high-level synthesis (HLS) flow that produces a threat-targeted and security enhanced hardware design to prevent HTH injection by a malicious foundry. Through analysis of entropy loss and criticality decay, the presented algorithms implement highly resource-efficient targeted information dispersion. An obfuscation flow is introduced to camouflage the effects of dispersion and reduce the effectiveness of reverse engineering. A new metric for the combined security of the device is proposed, and dispersion and obfuscation are co-optimized to target user-supplied threat parameters under resource constraints. The flow is evaluated on existing HLS benchmarks and a new IoT-specific benchmark, and shows significant resource savings as well as adaptability. The IoT and cloud computing rely on strong confidence in security of confidential or highly privacy sensitive data. As (differential) power attacks can take advantage of side-channel leakage to expose device-internal secrets, side-channel leakage is a major concern with ongoing research focus. However, countermeasures typically require expert-level security knowledge for efficient application, which limits adaptation in the highly competitive and time-constrained IoT field. We address this need by presenting the first HLS flow with primary focus on side-channel leakage reduction. Minimal security annotation to the high-level C-code is sufficient to perform automatic analysis of security critical operations with corresponding insertion of countermeasures. Additionally, imbalanced branches are detected and corrected. For practicality, the flow can meet both resource and information leakage constraints. The presented flow is extensively evaluated on established HLS benchmarks and a general IoT benchmark. Under identical resource constraints, leakage is reduced between 32% and 72% compared to the baseline. Under leakage target, the constraints are achieved with 31% to 81% less resource overhead

Design of Hybrid Full Adder using 6T-XOR-Cell for High Speed Processor Designs Applications

Hybrid-logic implementation is highly suitable in the design of a full adder circuit to attain high-speed low-power consumption, which helps to design n any high speed ALUs that can be used in varies processors and applicable for high speed IoT- Application. XOR/XNOR-cell, Hybrid Full Adder (HFA) are the fundamental building block to perform any arithmetic operation. In this paper, different types of high-speed, low-power 6T-XOR/XNOR-cell designs are being proposed and simulated results are presented. The proposed HFA is simulated using a cadence virtuoso environment in a 45nm technology with supply voltage as 0.8V at 1GHz. The proposed HFA consumes a power of 1.555uw, and the delay is 36.692ns.  Layout designs are drawn for both 6T-XOR/XNOR-cell, and 1- bit HFA designs. XOR/XNOR-cells are designed based on the combination of normal CMOS-inverter and Pass Transistor Logic (PTL). Which is used in the design of high end device processors such as ALU that can be implemented for the IoT- design applications

Overcoming nanoscale variations through statistical error compensation

Increasingly severe parameter variations that are observed in advanced nanoscale technologies create great obstacles in designing high-performance, next-generation digital integrated circuits (ICs). Conventional design principles impose increased design margins in power supply, device sizing, and operating frequency, leading to overly conservative designs which prevent the realization of potential benefits from nanotechnology advances. In response, robust digital circuit design techniques have been developed to overcome processing non-idealities. Statistical error compensation (SEC) is a class of system-level, communication-inspired techniques for designing energy efficient and robust systems. In this thesis, stochastic sensor network on chip (SSNOC), a known SEC technique, is applied to a computational kernel implemented with carbon nanotube field-effect transistors (CNFETs). With the aid of a well developed CNFET delay distribution modeling method, circuit simulations show up to 90× improvement of the SSNOC-based design in the circuit yield over the conventional design. The results verify the robustness of an SEC-based design under CNFET-specific variations. The error resiliency of SEC allows CNFET circuits to operate with reduced design margins under relaxed processing requirements, while concurrently maintaining the desired application-level performance