Oxygen-insertion Technology for CMOS Performance Enhancement

Until 2003, the semiconductor industry followed Dennard scaling rules to improve complementary metal-oxide-semiconductor (CMOS) transistor performance. However, performance gains with further reductions in transistor gate length are limited by physical effects that do not scale commensurately with device dimensions: short-channel effects (SCE) due to gate-leakage-limited gate-oxide thickness scaling, channel mobility degradation due to enhanced vertical electric fields, increased parasitic resistances due to reductions in source/drain (S/D) contact area, and increased variability in transistor performance due to random dopant fluctuation (RDF) effects and gate work function variations (WFV). These emerging scaling issues, together with increased process complexity and cost, pose severe challenges to maintaining the exponential scaling of transistor dimensions. This dissertation discusses the benefits of oxygen-insertion (OI) technology, a CMOS performance booster, for overcoming these challenges. The benefit of OI technology to mitigate the increase in sheet resistance ($R_{sh}$) with decreasing junction depth ($X_J$) for ultra-shallow-junctions (USJs) relevant for deep-sub-micron planar CMOS transistors is assessed through the fabrication of $R_{sh}$ test structures, electrical characterization, and technology computer-aided design (TCAD) simulations. Experimental and secondary ion mass spectroscopy (SIMS) analyses indicate that OI technology can facilitate low-resistivity USJ formation by reducing $R_{sh}$ and $X_J$ due to retarded transient-enhanced-diffusion (TED) effects and enhanced dopant retention during post-implantation thermal annealing. It is also shown that a low-temperature-oxide (LTO) capping can increase $R_{sh}$ unfavorably due to lower dopant activation levels, which can be alleviated by OI technology. This dissertation extends the evaluation of OI technology to advanced FinFET technology, targeting 7/8-nm low power technology node. A bulk-Si FinFET design comprising a super-steep retrograde (SSR) fin channel doping profile achievable with OI technology is studied by three-dimensional (3-D) TCAD simulations. As compared with the conventional bulk-Si (control) FinFET design with a heavily-doped fin channel doping profile, SSR FinFETs can achieve higher $I_{on}/I_{off}$ ratios and reduce the sensitivity of device performance to variations due to the lightly doped fin channel. As compared with the SOI FinFET design, SSR FinFETs can achieve similarly low $V_{DD,min}$ for 6T-SRAM cell yield estimation. Both SSR and SOI design can provide for as much as 100 mV reduction in $V_{DD,min}$ compared with the control FinFET design. Overall, the SSR FinFET design that can be achieved with OI technology is demonstrated to be a cheaper alternative to the SOI FinFET technology for extending CMOS scaling beyond the 10-nm node. Finally, this dissertation investigates the benefits of OI technology for reducing the Schottky barrier height ($\Phi_{Bp}$) of a Pt/Ti/p-type Si metal-semiconductor (M/S) contact, which can be expected to help reduce the specific contact resistivity for a p-type silicon contact. Electrical measurements of back-to-back Schottky diodes, SIMS, and X-ray photoelectron spectroscopy (XPS) show that the reduction in $\Phi_{Bp}$ is associated with enhanced Ti 2p and Si 2p core energy level shifts. OI technology is shown to favor low-$\Phi_{Bp}$ Pt monosilicide formation during forming gas anneal (FGA) by suppressing the grain boundary diffusion of Pt atoms into the crystalline Si substrate

Design of SRAM Cell using Modified Lector and Dual Threshold Method Based on FINFET

FinFET (Fin Field Effect Transistor) is a new technology that satisfies the demand for a superior storage system by improving transistor circuit design (SS). CMOS devices experience a wide range of issues due to the gate's diminishing ability to control the channel. Increased total production costs are a few of these disadvantages. But this store needs to dissipate less power, have a quick access time, and a low leakage current. The increased power dissipation and leakage current of traditional CMOS-based SRAM (Static RAM) architectures cause a sharp decline in performance. The nanoscale gadget called FinFET is being introduced for use in SRAM fabrication due to its 3D gate architecture. The adoption of FinFET has helped boost overall performance in terms of efficiency, power, and footprint. And because it is immune to SCEs, FinFET has become the transistor of choice. In this study, we have examined a number of FinFET-based SRAM cells and compared them with CMOS technology. We have also suggested a novel 14T SRAM design that uses the Dual Threshold Method and Modified Lector Approach with FinFET, and it is implemented for the 1bit, 4bit, and 8bit

A Construction Kit for Efficient Low Power Neural Network Accelerator Designs

Implementing embedded neural network processing at the edge requires efficient hardware acceleration that couples high computational performance with low power consumption. Driven by the rapid evolution of network architectures and their algorithmic features, accelerator designs are constantly updated and improved. To evaluate and compare hardware design choices, designers can refer to a myriad of accelerator implementations in the literature. Surveys provide an overview of these works but are often limited to system-level and benchmark-specific performance metrics, making it difficult to quantitatively compare the individual effect of each utilized optimization technique. This complicates the evaluation of optimizations for new accelerator designs, slowing-down the research progress. This work provides a survey of neural network accelerator optimization approaches that have been used in recent works and reports their individual effects on edge processing performance. It presents the list of optimizations and their quantitative effects as a construction kit, allowing to assess the design choices for each building block separately. Reported optimizations range from up to 10'000x memory savings to 33x energy reductions, providing chip designers an overview of design choices for implementing efficient low power neural network accelerators

Novel IC designs with 32 nm Independent-Gate FinFET

Electrical EngineeringThe semiconductor industry is confronted with serious challenges as the push continues toward scaling transistors into the 22-nm technology node and beyond. The most important among these challenges is the diminishing gate control over the channel, which manifests itself in the form of the increased short-channel effects (SCE) and leakage currents. One approach to countering these effects is introducing new materials for improved performance, either into the gate stack, the channel, or the source/drain extension regions. However, even with the introduction of these new materials, leakage will continue to be a serious problem. Hence, alter device architecture are being explored which processes inherently better robustness to SCE. Among this alternatives, multiple-gate FETs, also known as FinFET or gate wrap-around FETs, are emerging as promising candidates. In a FinFET, the gate wraps around a thin slice of silicon, also known as a ???fin???, and current flows along the top and side surface of the fin. This wrap-around nature of the gate enhances the gate control over the channel, thus reducing the SCE and leakage currents. Furthermore, fabrication of FinFET is compatible with that of conventional CMOS, thus making possible very rapid deployment to manufacturing. From a circuit-design perspective, FinFET provides IC designer with more options to innovate. For instance, FinFET device can directly substitute the CMOS in the existing applications by using the shorted-gate FinFET in which two FinFET gates are tied together. Additionally, the low-power mode of FinFET device in which the back-gate bias is tied to a reverse-bias voltage is often employed in the low-power design in that it can reduce subthreshold leakage. Last but not least, the independent-gate FinFET emerges as an interesting device so that IC designers have a variety of choices to flexibly use the two gates of FinFET for difference tasks. In this thesis, independent-gate FinFET are our concern with two designs being included. The first work presents a novel methodology for IC speed-up in 32nm FinFET. By taking advantage of independently controlling two gates of IG-FinFET, a boosting structures is developed to improve the signal propagation on interconnect significantly. In the second work, a digital voltage sensor design is illustrated. Based on the operation of a p-type FinFET in low-power mode and independent-gate mode, a new technique for designing a controllable delay element (CDE) with high linearity is presented. Then, we develop a 9-bit digital voltage sensor with a voltage range of 0.7 ??? 1.1 V and 50 mV resolution. The proposed voltage sensor can operate with ultra-low power, a wide voltage range, and fairly high frequency.ope

ENABLING IOT AUTHENTICATION, PRIVACY AND SECURITY VIA BLOCKCHAIN

Although low-power and Internet-connected gadgets and sensors are increasingly integrated into our lives, the optimal design of these systems remains an issue. In particular, authentication, privacy, security, and performance are critical success factors. Furthermore, with emerging research areas such as autonomous cars, advanced manufacturing, smart cities, and building, usage of the Internet of Things (IoT) devices is expected to skyrocket. A single compromised node can be turned into a malicious one that brings down whole systems or causes disasters in safety-critical applications. This dissertation addresses the critical problems of (i) device management, (ii) data management, and (iii) service management in IoT systems. In particular, we propose an integrated platform solution for IoT device authentication, data privacy, and service security via blockchain-based smart contracts. We ensure IoT device authentication by blockchain-based IC traceability system, from its fabrication to its end-of-life, allowing both the supplier and a potential customer to verify an IC’s provenance. Results show that our proposed consortium blockchain framework implementation in Hyperledger Fabric for IC traceability achieves a throughput of 35 transactions per second (tps). To corroborate the blockchain information, we authenticate the IC securely and uniquely with an embedded Physically Unclonable Function (PUF). For reliable Weak PUF-based authentication, our proposed accelerated aging technique reduces the cumulative burn-in cost by ∼ 56%. We also propose a blockchain-based solution to integrate the privacy of data generated from the IoT devices by giving users control of their privacy. The smart contract controlled trust-base ensures that the users have private access to their IoT devices and data. We then propose a remote configuration of IC features via smart contracts, where an IC can be programmed repeatedly and securely. This programmability will enable users to upgrade IC features or rent upgraded IC features for a fixed period after users have purchased the IC. We tailor the hardware to meet the blockchain performance. Our on-die hardware module design enforces the hardware configuration’s secure execution and uses only 2,844 slices in the Xilinx Zedboard Zynq Evaluation board. The blockchain framework facilitates decentralized IoT, where interacting devices are empowered to execute digital contracts autonomously

Cache memory design in the FinFET era

The major problem in the future technology scaling is the variations in process parameters that are interpreted as imperfections in the development process. Moreover, devices are more sensitive to the environmental changes of temperature and supply volt- age as well as to ageing. All these influences are manifested in the integrated circuits as increased power consumption, reduced maximal operating frequency and increased number of failures. These effects have been partially overcome with the introduction of the FinFET technology which have solved the problem of variability caused by Random Dopant Fluctuations. However, in the next ten years channel length is projected to shrink to 10nm where the variability source generated by Line Edge Roughness will dominate, and its effects on the threshold voltage variations will become critical. The embedded memories with their cells as the basic building unit are the most prone to these effects due to their the smallest dimensions. Because of that, memories should be designed with particular care in order to make possible further technology scaling. This thesis explores upcoming 10nm FinFETs and the existing issues in the cache memory design with this technology. More- over, it tries to present some original and novel techniques on the different level of design abstraction for mitigating the effects of process and environmental variability. At first original method for simulating variability of Tri-Gate Fin- FETs is presented using conventional HSPICE simulation environment and BSIM-CMG model cards. When that is accomplished, thorough characterisation of traditional SRAM cell circuits (6T and 8T) is performed. Possibility of using Independent Gate FinFETs for increasing cell stability has been explored, also. Gain Cells appeared in the recent past as an attractive alternative for in the cache memory design. This thesis partially explores this idea by presenting and performing detailed circuit analysis of the dynamic 3T gain cell for 10nm FinFETs. At the top of this work, thesis shows one micro-architecture optimisation of high-speed cache when it is implemented by 3T gain cells. We show how the cache coherency states can be used in order to reduce refresh energy of the memory as well as reduce memory ageing.El principal problema de l'escalat la tecnologia són les variacions en els paràmetres de disseny (imperfeccions) durant procés de fabricació. D'altra banda, els dispositius també són més sensibles als canvis ambientals de temperatura, la tensió d'alimentació, així com l'envelliment. Totes aquestes influències es manifesten en els circuits integrats com l'augment de consum d'energia, la reducció de la freqüència d'operació màxima i l'augment del nombre de xips descartats. Aquests efectes s'han superat parcialment amb la introducció de la tecnologia FinFET que ha resolt el problema de la variabilitat causada per les fluctuacions de dopants aleatòries. No obstant això, en els propers deu anys, l'ample del canal es preveu que es reduirà a 10nm, on la font de la variabilitat generada per les rugositats de les línies de material dominarà, i els seu efecte en les variacions de voltatge llindar augmentarà. Les memòries encastades amb les seves cel·les com la unitat bàsica de construcció són les més propenses a sofrir aquests efectes a causa de les seves dimensions més petites. A causa d'això, cal dissenyar les memòries amb una especial cura per tal de fer possible l'escalat de la tecnologia. Aquesta tesi explora la tecnologia de FinFETs de 10nm i els problemes existents en el disseny de memòries amb aquesta tecnologia. A més a més, presentem noves tècniques originals sobre diferents nivells d'abstracció del disseny per a la mitigació dels efectes les variacions tan de procés com ambientals. En primer lloc, presentem un mètode original per a la simulació de la variabilitat de Tri-Gate FinFETs usant entorn de simulació HSPICE convencional i models de tecnologia BSIMCMG. Després, es realitza la caracterització completa dels circuits de cel·les SRAM tradicionals (6T i 8T) conjuntament amb l'ús de Gate-independent FinFETs per augmentar l'estabilitat de la cèl·lula

Architectural techniques to extend multi-core performance scaling

Multi-cores have successfully delivered performance improvements over the past decade; however, they now face problems on two fronts: power and off-chip memory bandwidth. Dennard\u27s scaling is effectively coming to an end which has lead to a gradual increase in chip power dissipation. In addition, sustaining off-chip memory bandwidth has become harder due to the limited space for pins on the die and greater current needed to drive the increasing load . My thesis focuses on techniques to address the power and off-chip memory bandwidth challenges in order to avoid the premature end of the multi-core era. ^ In the first part of my thesis, I focus on techniques to address the power problem. One option to cope with the power limit, as suggested by some recent papers, is to ensure that an increasing number of cores are kept powered down (i.e., dark silicon) due to lack of power; but this option imposes a low upper bound on performance. The alternative option of customizing the cores to improve power efficiency may incur increased effort for hardware design, verification and test, and degraded programmability. I propose a gentler evolutionary path for multi-cores, called successive frequency unscaling ( SFU), to cope with the slowing of Dennard\u27s scaling. SFU keeps powered significantly more cores (compared to the option of keeping them \u27dark\u27) running at clock frequencies on the extended Pareto frontier that are successively lowered every generation to stay within the power budget. ^ In the second part of my thesis, I focus on techniques to avert the limited off-chip memory bandwidth problem. Die-stacking of DRAM on a processor die promises to continue scaling the pin bandwidth to off-chip memory. While the die-stacked DRAM is expected to be used as a cache, storing any part of the tag in the DRAM itself erodes the bandwidth advantage of die-stacking. As such, the on-die space overhead of the large DRAM cache\u27s tag is a concern. A well-known compromise is to employ a small on-die tag cache (T$) for the tag metadata while the full tag stays in the DRAM. However, tag caching fundamentally requires exploiting page-level metadata locality to ensure efficient use of the 3-D DRAM bandwidth. Plain sub-blocking exploits this locality but incurs holes in the cache (i.e., diminished DRAM cache capacity), whereas decoupled organizations avoid holes but destroy this locality. I propose Bandwidth-Efficient Tag Access (BETA) DRAM cache (β$ ) which avoids holes while exploiting the locality through various metadata organizational techniques. Using simulations, I conclusively show that the primary concern in DRAM caches is bandwidth and not latency, and that due to β$\u27s tag bandwidth efficiency, β$ with a T$performs 15$

The Design, Fabrication and Characterization of Independent-Gate FinFETs

The Independent-Gate FinFET is introduced as a novel device structure that combines several innovative aspects of the FinFET and planar double-gate FETs. The IG-FinFET addresses the concerns of scaled CMOS at extremely short channel lengths, by offering the superior short channel control of the double-gate architecture. The IG-FinFET allows for the unique behavioral characteristics of an independent-gate, four-terminal FET. This capability has been demonstrated in planar double-gate architectures, but is intrinsically prohibited by nominal FinFET integration schemes. Finally, the IG-FinFET allows for conventional CMOS manufacturing techniques to be used by leveraging many of the FinFET integration concepts. By introducing relatively few deviations from a standard FinFET fabrication process, the IG-FinFET integration offers the capability of combining three-terminal FinFET devices with four-terminal IG-FinFET devices in one powerful technology for SoC or Analog/RF application, to name only a few. The IG-FinFET device is examined by device modeling, circuit simulation, testsite design, fabrication and electrical characterization. The results of two-dimensional device simulations are presented, and the effects of process variations are discussed in order to understand the desire for a fully self-aligned double-gate architecture. Circuit design is investigated to demonstrate the capabilities of such a double-gate device. Physical designs are also examined, and the layout penalties of implementing such a device are discussed in order to understand the requirement of double-gate and independent-gate integration. A test vehicle is designed and presented for the structural integration and fabrication process development necessary for the demonstration and validation of this novel device architecture. The processing and results of several fabrication experiments are presented, with physical and electrical analysis. The integration changes and process modifications suggested by this analysis are discussed and analyzed. Fabricated devices are then electrically and physically characterized. The final set of fabricated devices show excellent agreement with simulated devices, and experimental verification of double-gate device theory. The results of this work provide for a new and novel device architecture with wide ranging technology application, as well as a new fabrication platform with which to study double-gate device theory and further technology integration

Nano-scale TG-FinFET: Simulation and Analysis

Transistor has been designed and fabricated in the same way since its invention more than four decades ago enabling exponential shrinking in the channel length. However, hitting fundamental limits imposed the need for introducing disruptive technology to take over. FinFET - 3-D transistor - has been emerged as the first successor to MOSFET to continue the technology scaling roadmap. In this thesis, scaling of nano-meter FinFET has been investigated on both the device and circuit levels. The studies, primarily, consider FinFET in its tri-gate (TG) structure. On the device level, first, the main TCAD models used in simulating electron transport are benchmarked against the most accurate results on the semi-classical level using Monte Carlo techniques. Different models and modifications are investigated in a trial to extend one of the conventional models to the nano-scale simulations. Second, a numerical study for scaling TG-FinFET according to the most recent International Technology Roadmap of Semiconductors is carried out by means of quantum corrected 3-D Monte Carlo simulations in the ballistic and quasi-ballistic regimes, to assess its ultimate performance and scaling behavior for the next generations. Ballisticity ratio (BR) is extracted and discussed over different channel lengths. The electron velocity along the channel is analyzed showing the physical significance of the off-equilibrium transport with scaling the channel length. On the circuit level, first, the impact of FinFET scaling on basic circuit blocks is investigated based on the PTM models. 256-bit (6T) SRAM is evaluated for channel lengths of 20nm down to 7nm showing the scaling trends of basic performance metrics. In addition, the impact of VT variations on the delay, power, and stability is reported considering die-to-die variations. Second, we move to another peer-technology which is 28nm FD-SOI as a comparative study, keeping the SRAM cell as the test block, more advanced study is carried out considering the cell‘s stability and the evolution from dynamic to static metrics

Near-Threshold Computing: Past, Present, and Future.

Transistor threshold voltages have stagnated in recent years, deviating from constant-voltage scaling theory and directly limiting supply voltage scaling. To overcome the resulting energy and power dissipation barriers, energy efficiency can be improved through aggressive voltage scaling, and there has been increased interest in operating at near-threshold computing (NTC) supply voltages. In this region sizable energy gains are achieved with moderate performance loss, some of which can be regained through parallelism. This thesis first provides a methodical definition of how near to threshold is "near threshold" and continues with an in-depth examination of NTC across past, present, and future CMOS technologies. By systematically defining near-threshold, the trends and tradeoffs are analyzed, lending insight in how best to design and optimize near-threshold systems. NTC works best for technologies that feature good circuit delay scalability, therefore technologies without strong short-channel effects. Early planar technologies (prior to 90nm or so) featured good circuit scalability (8x energy gains), but lacked area in which to add cores for parallelization. Recent planar nodes (32nm – 20nm) feature more area for cores but suffer from poor delay scalability, and so are not well-suited for NTC (4x energy gains). The switch to FinFET CMOS technology allows for a return to strong voltage scalability (8x gain), reversing trends seen in planar technologies, while dark silicon has created an opportunity to add cores for parallelization. Improved FinFET voltage scalability even allows for latency reduction of a single task, as long as the task is sufficiently parallelizable (< 10% serial code). Finally, we will look at a technique for fast voltage boosting, called Shortstop, in which a core's operating voltage is raised in 10s of cycles. Shortstop can be used to quickly respond to single-threaded performance demands of a near-threshold system by leveraging the innate parasitic inductance of a dedicated dirty supply rail, further improving energy efficiency. The technique is demonstrated in a wirebond implementation and is able to boost a core up to 1.8x faster than a header-based approach, while reducing supply droop by 2-7x. An improved flip-chip architecture is also proposed.PhDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113600/1/npfet_1.pd