A novel deep submicron bulk planar sizing strategy for low energy subthreshold standard cell libraries

Engineering andPhysical Science ResearchCouncil (EPSRC) and Arm Ltd for providing funding in the form of grants and studentshipsThis work investigates bulk planar deep submicron semiconductor physics in an attempt to improve standard cell libraries aimed at operation in the subthreshold regime and in Ultra Wide Dynamic Voltage Scaling schemes. The current state of research in the field is examined, with particular emphasis on how subthreshold physical effects degrade robustness, variability and performance. How prevalent these physical effects are in a commercial 65nm library is then investigated by extensive modeling of a BSIM4.5 compact model. Three distinct sizing strategies emerge, cells of each strategy are laid out and post-layout parasitically extracted models simulated to determine the advantages/disadvantages of each. Full custom ring oscillators are designed and manufactured. Measured results reveal a close correlation with the simulated results, with frequency improvements of up to 2.75X/2.43X obs erved for RVT/LVT devices respectively. The experiment provides the first silicon evidence of the improvement capability of the Inverse Narrow Width Effect over a wide supply voltage range, as well as a mechanism of additional temperature stability in the subthreshold regime. A novel sizing strategy is proposed and pursued to determine whether it is able to produce a superior complex circuit design using a commercial digital synthesis flow. Two 128 bit AES cores are synthesized from the novel sizing strategy and compared against a third AES core synthesized from a state-of-the-art subthreshold standard cell library used by ARM. Results show improvements in energy-per-cycle of up to 27.3% and frequency improvements of up to 10.25X. The novel subthreshold sizing strategy proves superior over a temperature range of 0 °C to 85 °C with a nominal (20 °C) improvement in energy-per-cycle of 24% and frequency improvement of 8.65X. A comparison to prior art is then performed. Valid cases are presented where the proposed sizing strategy would be a candidate to produce superior subthreshold circuits

Subthreshold and gate leakage current analysis and reduction in VLSI circuits

CMOS technology has scaled aggressively over the past few decades in an effort to enhance functionality, speed and packing density per chip. As the feature sizes are scaling down to sub-100nm regime, leakage power is increasing significantly and is becoming the dominant component of the total power dissipation. Major contributors to the total leakage current in deep submicron regime are subthreshold and gate tunneling leakage currents. The leakage reduction techniques developed so far were mostly devoted to reducing subthreshold leakage. However, at sub-65nm feature sizes, gate leakage current grows faster and is expected to surpass subthreshold leakage current. In this work, an extensive analysis of the circuit level characteristics of subthreshold and gate leakage currents is performed at 45nm and 32nm feature sizes. The analysis provides several key observations on the interdependency of gate and subthreshold leakage currents. Based on these observations, a new leakage reduction technique is proposed that optimizes both the leakage currents. This technique identifies minimum leakage vectors for a given circuit based on the number of transistors in OFF state and their position in the stack. The effectiveness of the proposed technique is compared to most of the mainstream leakage reduction techniques by implementing them on ISCAS89 benchmark circuits. The proposed leakage reduction technique proved to be more effective in reducing gate leakage current than subthreshold leakage current. However, when combined with dual-threshold and variable-threshold CMOS techniques, substantial subthreshold leakage current reduction was also achieved. A total savings of 53% for subthreshold leakage current and 26% for gate leakage current are reported

Near-Zero-Power Temperature Sensing via Tunneling Currents Through Complementary Metal-Oxide-Semiconductor Transistors.

Temperature sensors are routinely found in devices used to monitor the environment, the human body, industrial equipment, and beyond. In many such applications, the energy available from batteries or the power available from energy harvesters is extremely limited due to limited available volume, and thus the power consumption of sensing should be minimized in order to maximize operational lifetime. Here we present a new method to transduce and digitize temperature at very low power levels. Specifically, two pA current references are generated via small tunneling-current metal-oxide-semiconductor field effect transistors (MOSFETs) that are independent and proportional to temperature, respectively, which are then used to charge digitally-controllable banks of metal-insulator-metal (MIM) capacitors that, via a discrete-time feedback loop that equalizes charging time, digitize temperature directly. The proposed temperature sensor was integrated into a silicon microchip and occupied 0.15 mm2 of area. Four tested microchips were measured to consume only 113 pW with a resolution of 0.21 °C and an inaccuracy of ±1.65 °C, which represents a 628× reduction in power compared to prior-art without a significant reduction in performance

Versatile stochastic dot product circuits based on nonvolatile memories for high performance neurocomputing and neurooptimization.

The key operation in stochastic neural networks, which have become the state-of-the-art approach for solving problems in machine learning, information theory, and statistics, is a stochastic dot-product. While there have been many demonstrations of dot-product circuits and, separately, of stochastic neurons, the efficient hardware implementation combining both functionalities is still missing. Here we report compact, fast, energy-efficient, and scalable stochastic dot-product circuits based on either passively integrated metal-oxide memristors or embedded floating-gate memories. The circuit's high performance is due to mixed-signal implementation, while the efficient stochastic operation is achieved by utilizing circuit's noise, intrinsic and/or extrinsic to the memory cell array. The dynamic scaling of weights, enabled by analog memory devices, allows for efficient realization of different annealing approaches to improve functionality. The proposed approach is experimentally verified for two representative applications, namely by implementing neural network for solving a four-node graph-partitioning problem, and a Boltzmann machine with 10-input and 8-hidden neurons

High-performance subthreshold standard cell design and cell placement optimization

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Development, Demonstration, and Device Physics of FET-Accessed One-Transistor GaAs Dynamic Memory Technologies

The introduction of digital GaAs into modem high-speed computing systems has led to an increasing demand for high-density memory in these GaAs technologies. To date, most of the memory development efforts in GaAs have been directed toward four- and six-transistor static RAM\u27s, which consume substantial chip area and dissipate much static power resulting in limited single-chip GaAs storage capacities. As it has successfully done in silicon, a one-transistor dynamic RAM approach could alleviate these problems making higher density GaAs memories possible. This dissertation discusses theoretical and experimental work that presents the possibility for a high-speed, low-power, one-transistor dynamic RAM technology in GaAs. The two elements of the DRAM cell, namely the charge storage capacitor and the access field-effect transistor have been studied in detail. Isolated diode junction charge storage capacitors have demonstrated 30 minutes of storage time at room temperature with charge densities comparable to those obtained in planar silicon DRAM capacitors. GaAs JFET and MESFET technologies have been studied, and with careful device design and choice of proper operating voltages experimental results show that both can function as acceptable access transistors. One-transistor MESFET- and JFET-accessed DRAM cells have been fabricated and operated at room temperature and above with a standby power dissipation that is only a small fraction of the power dissipated by the best commercial GaAs static RAM cells. A 2 x 2 bit demonstration array was built and successfully operated at room temperature to demonstrate the addressable read/write capability of this new technology

An Ultra-Low-Power Track-and-Hold Amplifier

The future of electronics is the Internet of Things (IoT) paradigm, where always-on devices and sensors monitor and transform everyday life. A plethora of applications (such as navigating drivers past road hazards or monitoring bridge and building stresses) employ this technology. These unattended ground-sensor applications require decade(s)-long operational life-times without battery changes. Such electronics demand stringent performance specifications with only nano-Watt power levels.This thesis presents an ultra-low-power track-and-hold amplifier for such systems. It serves as the front-end of a SAR-ADC or the building block for equalizers or filters. This amplifier\u27s design attains exceptional hold times by mitigating switch subthreshold leakage and bulk leakage. Its novel transmission-gate topology achieves wide-swing performance. Though only consuming 100 pico-Watts, it achieves a precision of 7.6 effective number of bits (ENOB). The track-and-hold amplifier was designed in 130-nm CMOS