High-Performance Deep SubMicron CMOS Technologies with Polycrystalline-SiGe Gates

The use of polycrystalline SiGe as the gate material for deep submicron CMOS has been investigated. A complete compatibility to standard CMOS processing is demonstrated when polycrystalline Si is substituted with SiGe (for Ge fractions below 0.5) to form the gate electrode of the transistors. Performance improvements are achieved for PMOS transistors by careful optimization of both transistor channel profile and p-type gate workfunction, the latter by changing Ge mole fraction in the gate. For the 0.18 ¿m CMOS generation we record up to 20% increase in the current drive, a 10% increase in the channel transconductance and subthreshold swing improvement from 82 mV/dec to 75 mV/dec resulting in excellent ¿on¿/¿off¿ currents ratio. At the same time, NMOS transistor performance is not affected by gate material substitutio

Multi-objective Pareto front and particle swarm optimization algorithms for power dissipation reduction in microprocessors

The progress of microelectronics making possible higher integration densities, and a considerable development of on-board systems are currently undergoing, this growth comes up against a limiting factor of power dissipation. Higher power dissipation will cause an immediate spread of generated heat which causes thermal problems. Consequently, the system's total consumed energy will increase as the system temperature increase. High temperatures in microprocessors and large thermal energy of computer systems produce huge problems of system confidence, performance, and cooling expenses. Power consumed by processors are mainly due to the increase in number of cores and the clock frequency, which is dissipated in the form of heat and causes thermal challenges for chip designers. As the microprocessor’s performance has increased remarkably in Nano-meter technology, power dissipation is becoming non-negligible. To solve this problem, this article addresses power dissipation reduction issues for high performance processors using multi-objective Pareto front (PF), and particle swarm optimization (PSO) algorithms to achieve power dissipation as a prior computation that reduces the real delay of a target microprocessor unit. Simulation is verified the conceptual fundamentals and optimization of joint body and supply voltages (Vth-VDD) which showing satisfactory findings

Design, Modeling and Analysis of Non-classical Field Effect Transistors

Transistor scaling following per Moore\u27s Law slows down its pace when entering into nanometer regime where short channel effects (SCEs), including threshold voltage fluctuation, increased leakage current and mobility degradation, become pronounced in the traditional planar silicon MOSFET. In addition, as the demand of diversified functionalities rises, conventional silicon technologies cannot satisfy all non-digital applications requirements because of restrictions that stem from the fundamental material properties. Therefore, novel device materials and structures are desirable to fuel further evolution of semiconductor technologies. In this dissertation, I have proposed innovative device structures and addressed design considerations of those non-classical field effect transistors for digital, analog/RF and power applications with projected benefits. Considering device process difficulties and the dramatic fabrication cost, application-oriented device design and optimization are performed through device physics analysis and TCAD modeling methodology to develop design guidelines utilizing transistor\u27s improved characteristics toward application-specific circuit performance enhancement. Results support proposed device design methodologies that will allow development of novel transistors capable of overcoming limitation of planar nanoscale MOSFETs. In this work, both silicon and III-V compound devices are designed, optimized and characterized for digital and non-digital applications through calibrated 2-D and 3-D TCAD simulation. For digital functionalities, silicon and InGaAs MOSFETs have been investigated. Optimized 3-D silicon-on-insulator (SOI) and body-on-insulator (BOI) FinFETs are simulated to demonstrate their impact on the performance of volatile memory SRAM module with consideration of self-heating effects. Comprehensive simulation results suggest that the current drivability degradation due to increased device temperature is modest for both devices and corresponding digital circuits. However, SOI FinFET is recommended for the design of low voltage operation digital modules because of its faster AC response and better SCEs management than the BOI structure. The FinFET concept is also applied to the non-volatile memory cell at 22 nm technology node for low voltage operation with suppressed SCEs. In addition to the silicon technology, our TCAD estimation based on upper projections show that the InGaAs FinFET, with superior mobility and improved interface conditions, achieve tremendous drive current boost and aggressively suppressed SCEs and thereby a strong contender for low-power high-performance applications over the silicon counterpart. For non-digital functionalities, multi-fin FETs and GaN HEMT have been studied. Mixed-mode simulations along with developed optimization guidelines establish the realistic application potential of underlap design of silicon multi-Fin FETs for analog/RF operation. The device with underlap design shows compromised current drivability but improve analog intrinsic gain and high frequency performance. To investigate the potential of the novel N-polar GaN material, for the first time, I have provided calibrated TCAD modeling of E-mode N-polar GaN single-channel HEMT. In this work, I have also proposed a novel E-mode dual-channel hybrid MIS-HEMT showing greatly enhanced current carrying capability. The impact of GaN layer scaling has been investigated through extensive TCAD simulations and demonstrated techniques for device optimization

Characterization of 28 nm FDSOI MOS and application to the design of a low-power 2.4 GHz LNA

IoT is expected to connect billions of devices all over world in the next years, and in a near future, it is expected to use LR-WPAN in a wide variety of applications. Not all the devices will require of high performance but will require of low power hungry systems since most of them will be powered with a battery. Conventional CMOS technologies cannot cover these needs even scaling it to very small regimes, which appear other problems. Hence, new technologies are emerging to cover the needs of this devices. One promising technology is the UTBB FDSOI, which achieves good performance with very good energy efficiency. This project characterizes this technology to obtain a set of parameters of interest for analog/RF design. Finally, with the help of a low-power design methodology (gm/Id approach), a design of an ULP ULV LNA is performed to check the suitability of this technology for IoT

Reliability in the face of variability in nanometer embedded memories

In this thesis, we have investigated the impact of parametric variations on the behaviour of one performance-critical processor structure - embedded memories. As variations manifest as a spread in power and performance, as a first step, we propose a novel modeling methodology that helps evaluate the impact of circuit-level optimizations on architecture-level design choices. Choices made at the design-stage ensure conflicting requirements from higher-levels are decoupled. We then complement such design-time optimizations with a runtime mechanism that takes advantage of adaptive body-biasing to lower power whilst improving performance in the presence of variability. Our proposal uses a novel fully-digital variation tracking hardware using embedded DRAM (eDRAM) cells to monitor run-time changes in cache latency and leakage. A special fine-grain body-bias generator uses the measurements to generate an optimal body-bias that is needed to meet the required yield targets. A novel variation-tolerant and soft-error hardened eDRAM cell is also proposed as an alternate candidate for replacing existing SRAM-based designs in latency critical memory structures. In the ultra low-power domain where reliable operation is limited by the minimum voltage of operation (Vddmin), we analyse the impact of failures on cache functional margin and functional yield. Towards this end, we have developed a fully automated tool (INFORMER) capable of estimating memory-wide metrics such as power, performance and yield accurately and rapidly. Using the developed tool, we then evaluate the #effectiveness of a new class of hybrid techniques in improving cache yield through failure prevention and correction. Having a holistic perspective of memory-wide metrics helps us arrive at design-choices optimized simultaneously for multiple metrics needed for maintaining lifetime requirements