Imperfection-Aware Design of CNFET Digital VLSI Circuits

Carbon nanotube field-effect transistor (CNFET) is one of the promising candidates as extensions to silicon CMOS devices. The CNFET, which is a 1-D structure with a near-ballistic transport capability, can potentially offer excellent device characteristics and order-of-magnitude better energy-delay product over standard CMOS devices. Significant challenges in CNT synthesis prevent CNFETs today from achieving such ideal benefits. CNT density variation and metallic CNTs are the dominant type of CNT variations/imperfections that cause performance variation, large static power consumption, and yield degradation. We present an imperfection-aware design technique for CNFET digital VLSI circuits by: 1) Analytical models that are developed to analyze and quantify the effects of CNT density variation on device characteristics, gate and system levels delays. The analytical models, which were validated by comparison to real experimental/simulation data, enables us to examine the space of CNFET combinational, sequential and memory cells circuits to minimize delay variations. Using these model, we drive CNFET processing and circuit design guidelines to manage/overcome CNT density variation. 2) Analytical models that are developed to analyze the effects of metallic CNTs on device characteristics, gate and system levels delay and power consumption. Using our presented analytical models, which are again validated by comparison with simulation data, it is shown that the static power dissipation is a more critical issue than the delay and the dynamic power of CNFET circuits in the presence of m-CNTs. 3) CNT density variation and metallic CNTs can result in functional failure of CNFET circuits. The complete and compact model for CNFET probability of failure that consider CNT density variation and m-CNTs is presented. This analytical model is applied to analyze the logical functional failures. The presented model is extended to predict opportunities and limitations of CNFET technology at todays Gigascale integration and beyond.\u2

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

Variability and reliability analysis of carbon nanotube technology in the presence of manufacturing imperfections

In 1925, Lilienfeld patented the basic principle of field effect transistor (FET). Thirty-four years later, Kahng and Atalla invented the MOSFET. Since that time, it has become the most widely used type of transistor in Integrated Circuits (ICs) and then the most important device in the electronics industry. Progress in the field for at least the last 40 years has followed an exponential behavior in accordance with Moore¿s Law. That is, in order to achieve higher densities and performance at lower power consumption, MOS devices have been scaled down. But this aggressive scaling down of the physical dimensions of MOSFETs has required the introduction of a wide variety of innovative factors to ensure that they could still be properly manufactured. Transistors have expe- rienced an amazing journey in the last 10 years starting with strained channel CMOS transistors at 90nm, carrying on the introduction of the high-k/metal-gate silicon CMOS transistors at 45nm until the use of the multiple-gate transistor architectures at 22nm and at recently achieved 14nm technology node. But, what technology will be able to produce sub-10nm transistors? Different novel materials and devices are being investigated. As an extension and enhancement to current MOSFETs some promising devices are n-type III-V and p-type Germanium FETs, Nanowire and Tunnel FETs, Graphene FETs and Carbon Nanotube FETs. Also, non-conventional FETs and other charge-based information carrier devices and alternative information processing devices are being studied. This thesis is focused on carbon nanotube technology as a possible option for sub-10nm transistors. In recent years, carbon nanotubes (CNTs) have been attracting considerable attention in the field of nanotechnology. They are considered to be a promising substitute for silicon channel because of their small size, unusual geometry (1D structure), and extraordinary electronic properties, including excellent carrier mobility and quasi-ballistic transport. In the same way, carbon nanotube field-effect transistors (CNFETs) could be potential substitutes for MOSFETs. Ideal CNFETs (meaning all CNTs in the transistor behave as semiconductors, have the same diameter and doping level, and are aligned and well-positioned) are predicted to be 5x faster than silicon CMOS, while consuming the same power. However, nowadays CNFETs are also affected by manufacturing variability, and several significant challenges must be overcome before these benefits can be achieved. Certain CNFET manufacturing imperfections, such as CNT diameter and doping variations, mispositioned and misaligned CNTs, high metal-CNT contact resistance, the presence of metallic CNTs (m-CNTs), and CNT density variations, can affect CNFET performance and reliability and must be addressed. The main objective of this thesis is to analyze the impact of the current CNFET manufacturing challenges on multi-channel CNFET performance from the point of view of variability and reliability and at different levels, device and circuit level. Assuming that CNFETs are not ideal or non-homogeneous because of today CNFET manufacturing imperfections, we propose a methodology of analysis that based on a CNFET ideal compact model is able to simulate heterogeneous or non-ideal CNFETs; that is, transistors with different number of tubes that have different diameters, are not uniformly spaced, have different source/drain doping levels, and, most importantly, are made up not only of semiconducting CNTs but also metallic ones. This method will allow us to analyze how CNT-specific variations affect CNFET device characteristics and parameters and CNFET digital circuit performance. Furthermore, we also derive a CNFET failure model and propose an alternative technique based on fault-tolerant architectures to deal with the presence of m-CNTs, one of the main causes of failure in CNFET circuits

Techniques and Prospects for Fault-tolerance in Post-CMOS ULSI

International audienceThis paper presents a survey of fault-masking techniques suitable for tolerating short-duration transient upsets in minimum-scale switching devices. Two types of fault masking are considered. The first type, coded dual-modular redundancy (cDMR), represents a family of parity-checking methods suitable for correcting a low rate of transient upsets. The second type, Restorative Feedback (RFB), is a triple-modular solution suitable for compensating a higher rate of transient upsets. We show that cDMR can be used efficiently for crossbar-style logic, but is not efficient in general for all logic styles. By contrast, RFB offers a fixed redundancy, and can be applied in general to any logic circuit. Finally, we propose novel circuits for ternary Muller C implementation based on carbon nanotube FET devices

Building Efficient and Reliable Emerging Technology Systems

The semiconductor industry has been reaping the benefits of Moore’s law powered by Dennard’s voltage scaling for the past fifty years. However, with the end of Dennard scaling, silicon chip manufacturers are facing a widespread plateau in performance improvements. While the architecture community has focused its effort on exploring parallelism, such as with multi-core, many-core and accelerator-based systems, chip manufacturers have been forced to explore beyond-Moore technologies to improve performance while maintaining power density. Examples of such technologies include monolithic 3D integration, carbon nanotube transistors, tunneling-based transistors, spintronics and quantum computing. However, the infancy of the manufacturing process of these new technologies impedes their usage in commercial products. The goal of this dissertation is to combine both architectural and device-level efforts to provide solutions across the computing stack that can overcome the reliability concerns of emerging technologies. This allows for beyond-Moore systems to compete with highly optimized silicon-based processors, thus, enabling faster commercialization of such systems. This dissertation proposes the following key steps: (i) Multifaceted understanding and modeling of variation and yield issues that occur in emerging technologies, such as carbon nanotube transistors (CNFETs). (ii) Design of systems using suitable logic families such as pass transistor logic that provide high performance. (iii) Design of a multi-granular fault-tolerant reconfigurable architecture that enhances yield and performance. (iv) Design of a multi-technology, multi-accelerator heterogeneous system (v) Development of real-time constrained efficient workload scheduling mechanism for heterogeneous systems. This dissertation first presents the use of pass transistor logic family as an alternate to the CMOS logic family for CNFETs to improve performance. It explores various architectural design choices for CNFETs using pass transistor logic (PTL) to create an energy-efficient RISC-V processor. Our results show that while a CNFET RISC-V processor using CMOS logic achieves a 2.9x energy-delay product (EDP) improvement over a silicon design, using PTL along the critical path components of the processor can boost EDP improvement by 5x as well as reduce area by 17% over 16 nm silicon CMOS. This document further builds on providing fault-tolerant and yield enhancing solutions for emerging 3D integration compatible technologies in the context of CNFETs. The proposed framework can efficiently support high-variation technologies by providing protection against manufacturing defects at multiple granularities: module and pipeline-stage levels. Based on the variation observed in a synthesized design, a reliable CNFET-based 3D multi-granular reconfigurable architecture, 3DTUBE, is presented to overcome the manufacturing difficulties. For 0.4-0.7 V, 3DTUBE provides up to 6.0x higher throughput and 3.1x lower EDP compared to a silicon-based multi-core design evaluated at 1 part per billion transistor failure rate, which is 10,000x lower in comparison to CNFET’s failure rate. This dissertation then ventures into building multi-accelerator heterogeneous systems and real-time schedulers that cater to the requirements of the applications while taking advantage of the underlying heterogeneous system. We introduce optimizations like task pruning, hierarchical hetero-ranking and rank update built upon two scheduler policies (MS-static and MS-dynamic), that result in a performance improvement of 3.5x (average) for real-world autonomous vehicle applications, when compared against state-of-the-art schedulers. Adopting insights from the above work, this thesis presents a multi-accelerator, multi-technology heterogeneous system powered by a multi-constrained scheduler that optimizes for varying task requirements to achieve up to 6.1x better energy over a baseline silicon-based system.PHDElectrical and Computer EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/169699/1/aporvaa_1.pd

Robust Circuit & Architecture Design in the Nanoscale Regime

Silicon based integrated circuit (IC) technology is approaching its physical limits. For sub 10nm technology nodes, the carbon nanotube (CNT) based field effect transistor has emerged as a promising device because of its excellent electronic properties. One of the major challenges faced by the CNT technology is the unwanted growth of metallic tubes. At present, there is no known CNT fabrication technology which allows the fabrication of 100% semiconducting CNTs. The presence of metallic tubes creates a short between the drain and source terminals of the transistor and has a detrimental impact on the delay, static power and yield of CNT based gates. This thesis will address the challenge of designing robust carbon nanotube based circuits in the presence of metallic tubes. For a small percentage of metallic tubes, circuit level solutions are proposed to increase the functional yield of CNT based gates in the presence of metallic tubes. Accurate analytical models with less than a 3% inaccuracy rate are developed to estimate the yield of CNT based circuit for a different percentage of metallic tubes and different drive strengths of logic gates. Moreover, a design methodology is developed for yield-aware carbon nanotube based circuits in the presence of metallic tubes using different CNFET transistor configurations. Architecture based on regular logic bricks with underlying hybrid CNFET configurations are developed which gives better trade-offs in terms of performance, power, and functional yield. In the case when the percentage of metallic tubes is large, the proposed circuit level techniques are not sufficient. Extra processing techniques must be applied to remove the metallic tubes. The tube removal techniques have trade-offs, as the removal process is not perfect and removes semiconducting tubes in addition to removing unwanted metallic tubes. As a result, stochastic removal of tubes from the drive and fanout gate(s) results in large variation in the performance of CNFET based gates and in the worst case open circuit gates. A Monte Carlo simulation engine is developed to estimate the impact of the removal of tubes on the performance and power of CNFET based logic gates. For a quick estimation of functional yield of logic gates, accurate analytical models are developed to estimate the functional yield of logic gates when a fraction of the tubes are removed. An efficient tube level redundancy (TLR) is proposed, resulting in a high functional yield of carbon nanotube based circuits with minimal overheads in terms of area and power when large fraction of tubes are removed. Furthermore, for applications where parallelism can be utilized we propose to increase the functional yield of the CNFET based circuits by increasing the logic depth of gates

A Holistic Solution for Reliability of 3D Parallel Systems

As device scaling slows down, emerging technologies such as 3D integration and carbon nanotube field-effect transistors are among the most promising solutions to increase device density and performance. These emerging technologies offer shorter interconnects, higher performance, and lower power. However, higher levels of operating temperatures and current densities project significantly higher failure rates. Moreover, due to the infancy of the manufacturing process, high variation, and defect densities, chip designers are not encouraged to consider these emerging technologies as a stand-alone replacement for Silicon-based transistors. The goal of this dissertation is to introduce new architectural and circuit techniques that can work around high-fault rates in the emerging 3D technologies, improving performance and reliability comparable to Silicon. We propose a new holistic approach to the reliability problem that addresses the necessary aspects of an effective solution such as detection, diagnosis, repair, and prevention synergically for a practical solution. By leveraging 3D fabric layouts, it proposes the underlying architecture to efficiently repair the system in the presence of faults. This thesis presents a fault detection scheme by re-executing instructions on idle identical units that distinguishes between transient and permanent faults while localizing it to the granularity of a pipeline stage. Furthermore, with the use of a dynamic and adaptive reconfiguration policy based on activity factors and temperature variation, we propose a framework that delivers a significant improvement in lifetime management to prevent faults due to aging. Finally, a design framework that can be used for large-scale chip production while mitigating yield and variation failures to bring up Carbon Nano Tube-based technology is presented. The proposed framework is capable of efficiently supporting high-variation technologies by providing protection against manufacturing defects at different granularities: module and pipeline-stage levels.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/168118/1/javadb_1.pd

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

An Efficient Gate Library for Ambipolar CNTFET Logic

Recently, several emerging technologies have been reported as potential candidates for controllable ambipolar devices. Controllable ambipolarity is a desirable property that enables the on-line configurability of n-type and p-type device polarity. In this paper, we introduce a new design methodology for logic gates based on controllable ambipolar devices, with an emphasis on carbon nanotubes as the candidate technology. Our technique results in ambipolar gates with a higher expressive power than conventional complementary metal-oxidesemiconductor (CMOS) libraries. We propose a library of static ambipolar carbon nanotube field effect transistor (CNTFET) gates based on generalized NOR-NAND-AOI-OAI primitives, which efficiently implements XOR-based functions. Technology mapping of several multi-level logic benchmarks that extensively use the XOR function, including multipliers, adders, and linear circuits, with ambipolar CNTFET logic gates indicates that on average, it is possible to reduce the number of logic levels by 42%, the delay by 26%, and the power consumption by 32%, resulting in a energy-delay-product (EDP) reduction of 59% over the same circuits mapped with unipolar CNTFET logic gates. Based on the projections in [1], where it is stated that defectfree CNTFETs will provide a 5× performance improvement over metal-oxide-semiconductor field effect transistors, the ambipolar library provides a performance improvement of 7×, a 57% reduction in power consumption, and a 20× improvement in EDP over the CMOS library