Ultra-Low Power Circuit Design for Cubic-Millimeter Wireless Sensor Platform.

Modern daily life is surrounded by smaller and smaller computing devices. As Bell’s Law predicts, the research community is now looking at tiny computing platforms and mm3-scale sensor systems are drawing an increasing amount of attention since they can create a whole new computing environment. Designing mm3-scale sensor nodes raises various circuit and system level challenges and we have addressed and proposed novel solutions for many of these challenges to create the first complete 1.0mm3 sensor system including a commercial microprocessor. We demonstrate a 1.0mm3 form factor sensor whose modular die-stacked structure allows maximum volume utilization. Low power I2C communication enables inter-layer serial communication without losing compatibility to standard I2C communication protocol. A dual microprocessor enables concurrent computation for the sensor node control and measurement data processing. A multi-modal power management unit allowed energy harvesting from various harvesting sources. An optical communication scheme is provided for initial programming, synchronization and re-programming after recovery from battery discharge. Standby power reduction techniques are investigated and a super cut-off power gating scheme with an ultra-low power charge pump reduces the standby power of logic circuits by 2-19× and memory by 30%. Different approaches for designing low-power memory for mm3-scale sensor nodes are also presented in this work. A dual threshold voltage gain cell eDRAM design achieves the lowest eDRAM retention power and a 7T SRAM design based on hetero-junction tunneling transistors reduces the standby power of SRAM by 9-19× with only 15% area overhead. We have paid special attention to the timer for the mm3-scale sensor systems and propose a multi-stage gate-leakage-based timer to limit the standard deviation of the error in hourly measurement to 196ms and a temperature compensation scheme reduces temperature dependency to 31ppm/°C. These techniques for designing ultra-low power circuits for a mm3-scale sensor enable implementation of a 1.0mm3 sensor node, which can be used as a skeleton for future micro-sensor systems in variety of applications. These microsystems imply the continuation of the Bell’s Law, which also predicts the massive deployment of mm3-scale computing systems and emergence of even smaller and more powerful computing systems in the near future.Ph.D.Electrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/91438/1/sori_1.pd

A hierarchical optimization engine for nanoelectronic systems using emerging device and interconnect technologies

A fast and efficient hierarchical optimization engine was developed to benchmark and optimize various emerging device and interconnect technologies and system-level innovations at the early design stage. As the semiconductor industry approaches sub-20nm technology nodes, both devices and interconnects are facing severe physical challenges. Many novel device and interconnect concepts and system integration techniques are proposed in the past decade to reinforce or even replace the conventional Si CMOS technology and Cu interconnects. To efficiently benchmark and optimize these emerging technologies, a validated system-level design methodology is developed based on the compact models from all hierarchies, starting from the bottom material-level, to the device- and interconnect-level, and to the top system-level models. Multiple design parameters across all hierarchies are co-optimized simultaneously to maximize the overall chip throughput instead of just the intrinsic delay or energy dissipation of the device or interconnect itself. This optimization is performed under various constraints such as the power dissipation, maximum temperature, die size area, power delivery noise, and yield. For the device benchmarking, novel graphen PN junction devices and InAs nanowire FETs are investigated for both high-performance and low-power applications. For the interconnect benchmarking, a novel local interconnect structure and hybrid Al-Cu interconnect architecture are proposed, and emerging multi-layer graphene interconnects are also investigated, and compared with the conventional Cu interconnects. For the system-level analyses, the benefits of the systems implemented with 3D integration and heterogeneous integration are analyzed. In addition, the impact of the power delivery noise and process variation for both devices and interconnects are quantified on the overall chip throughput.Ph.D

Power Management for Deep Submicron Microprocessors

As VLSI technology scales, the enhanced performance of smaller transistors comes at the expense of increased power consumption. In addition to the dynamic power consumed by the circuits there is a tremendous increase in the leakage power consumption which is further exacerbated by the increasing operating temperatures. The total power consumption of modern processors is distributed between the processor core, memory and interconnects. In this research two novel power management techniques are presented targeting the functional units and the global interconnects. First, since most leakage control schemes for processor functional units are based on circuit level techniques, such schemes inherently lack information about the operational profile of higher-level components of the system. This is a barrier to the pivotal task of predicting standby time. Without this prediction, it is extremely difficult to assess the value of any leakage control scheme. Consequently, a methodology that can predict the standby time is highly beneficial in bridging the gap between the information available at the application level and the circuit implementations. In this work, a novel Dynamic Sleep Signal Generator (DSSG) is presented. It utilizes the usage traces extracted from cycle accurate simulations of benchmark programs to predict the long standby periods associated with the various functional units. The DSSG bases its decisions on the current and previous standby state of the functional units to accurately predict the length of the next standby period. The DSSG presents an alternative to Static Sleep Signal Generation (SSSG) based on static counters that trigger the generation of the sleep signal when the functional units idle for a prespecified number of cycles. The test results of the DSSG are obtained by the use of a modified RISC superscalar processor, implemented by SimpleScalar, the most widely accepted open source vehicle for architectural analysis. In addition, the results are further verified by a Simultaneous Multithreading simulator implemented by SMTSIM. Leakage saving results shows an increase of up to 146% in leakage savings using the DSSG versus the SSSG, with an accuracy of 60-80% for predicting long standby periods. Second, chip designers in their effort to achieve timing closure, have focused on achieving the lowest possible interconnect delay through buffer insertion and routing techniques. This approach, though, taxes the power budget of modern ICs, especially those intended for wireless applications. Also, in order to achieve more functionality, die sizes are constantly increasing. This trend is leading to an increase in the average global interconnect length which, in turn, requires more buffers to achieve timing closure. Unconstrained buffering is bound to adversely affect the overall chip performance, if the power consumption is added as a major performance metric. In fact, the number of global interconnect buffers is expected to reach hundreds of thousands to achieve an appropriate timing closure. To mitigate the impact of the power consumed by the interconnect buffers, a power-efficient multi-pin routing technique is proposed in this research. The problem is based on a graph representation of the routing possibilities, including buffer insertion and identifying the least power path between the interconnect source and set of sinks. The novel multi-pin routing technique is tested by applying it to the ISPD and IBM benchmarks to verify the accuracy, complexity, and solution quality. Results obtained indicate that an average power savings as high as 32% for the 130-nm technology is achieved with no impact on the maximum chip frequency

Digital-Based Analog Processing in Nanoscale CMOS ICs for IoT Applications

L'abstract è presente nell'allegato / the abstract is in the attachmen

Multi-criteria optimization for energy-efficient multi-core systems-on-chip

The steady down-scaling of transistor dimensions has made possible the evolutionary progress leading to today’s high-performance multi-GHz microprocessors and core based System-on-Chip (SoC) that offer superior performance, dramatically reduced cost per function, and much-reduced physical size compared to their predecessors. On the negative side, this rapid scaling however also translates to high power densities, higher operating temperatures and reduced reliability making it imperative to address design issues that have cropped up in its wake. In particular, the aggressive physical miniaturization have increased CMOS fault sensitivity to the extent that many reliability constraints pose threat to the device normal operation and accelerate the onset of wearout-based failures. Among various wearout-based failure mechanisms, Negative biased temperature instability (NBTI) has been recognized as the most critical source of device aging. The urge of reliable, low-power circuits is driving the EDA community to develop new design techniques, circuit solutions, algorithms, and software, that can address these critical issues. Unfortunately, this challenge is complicated by the fact that power and reliability are known to be intrinsically conflicting metrics: traditional solutions to improve reliability such as redundancy, increase of voltage levels, and up-sizing of critical devices do contrast with traditional low-power solutions, which rely on compact architectures, scaled supply voltages, and small devices. This dissertation focuses on methodologies to bridge this gap and establishes an important link between low-power solutions and aging effects. More specifically, we proposed new architectural solutions based on power management strategies to enable the design of low-power, aging aware cache memories. Cache memories are one of the most critical components for warranting reliable and timely operation. However, they are also more susceptible to aging effects. Due to symmetric structure of a memory cell, aging occurs regardless of the fact that a cell (or word) is accessed or not. Moreover, aging is a worst-case matric and line with worst-case access pattern determines the aging of the entire cache. In order to stop the aging of a memory cell, it must be put into a proper idle state when a cell (or word) is not accessed which require proper management of the idleness of each atomic unit of power management. We have proposed several reliability management techniques based on the idea of cache partitioning to alleviate NBTI-induced aging and obtain joint energy and lifetime benefits. We introduce graceful degradation mechanism which allows different cache blocks into which a cache is partitioned to age at different rates. This implies that various sub-blocks become unreliable at different times, and the cache keeps functioning with reduced efficiency. We extended the capabilities of this architecture by integrating the concept of reconfigurable caches to maintain the performance of the cache throughout its lifetime. By this strategy, whenever a block becomes unreliable, the remaining cache is reconfigured to work as a smaller size cache with only a marginal degradation of performance. Many mission-critical applications require guaranteed lifetime of their operations and therefore the hardware implementing their functionality. Such constraints are usually enforced by means of various reliability enhancing solutions mostly based on redundancy which are not energy-friendly. In our work, we have proposed a novel cache architecture in which a smart use of cache partitions for redundancy allows us to obtain cache that meet a desired lifetime target with minimal energy consumption

Low Power Circuits for Miniature Sensor Systems.

With the development of VLSI technologies, the sensor systems of all kinds of applications have entered our everyday's life. For specific applications such as medical implants, the form factor of such systems is the crucial concern. In order to minimize of size of the power sources with a given lifetime, the ability to operate the system with low power consumption is the key. An effective way of lowering the active power dissipation is through aggressive voltage scaling. For minimal energy operation, the optimum supply voltage is typical lower than the subthreshold voltage. On the other hand, a sensor system spends most of the time idling while only actively obtaining data in a short period of time. As a result, strong power gating is needed for reducing the leakage power. We discuss the design challenges for several building blocks for the sensor system that have not been gotten much emphasis in term of power consumption. To monitor the period for idle time and to wake up the system periodically, two types of ultra low power timers are proposed. The first one utilizes the gate leakage of a MOS transistor to achieve low temperature dependency and large time constant. The second one implements a program-and-hold technique to compensate for the temperature coefficient of a one-shot oscillator with 150pW of average power. We propose a low power temperature sensor that is suitable for passive RFID transponder. To retrieve the data out of the sensor chip, two passive proximity communication schemes are presented. Capacitive coupling can be used for chips on a stack where the key challenge is misalignment. A alignment detection and microplate reconfiguration method is proposed to solve the problem. We also propose a passive inductive coupling scheme using pulse signaling. Compared to the traditional backscattering technique, the limitations on the quality factor of the inductor and the signal sensitivity of the receiver can be relaxed.Ph.D.Electrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/61782/1/yushiang_1.pd

Digital-based analog processing in nanoscale CMOS ICs for IoT applications

The Internet-of-Things (IoT) concept has been opening up a variety of applications, such as urban and environmental monitoring, smart health, surveillance, and home automation. Most of these IoT applications require more and more power/area efficient Complemen tary Metal–Oxide–Semiconductor (CMOS) systems and faster prototypes (lower time-to market), demanding special modifications in the current IoT design system bottleneck: the analog/RF interfaces. Specially after the 2000s, it is evident that there have been significant improvements in CMOS digital circuits when compared to analog building blocks. Digital circuits have been taking advantage of CMOS technology scaling in terms of speed, power consump tion, and cost, while the techniques running behind the analog signal processing are still lagging. To decrease this historical gap, there has been an increasing trend in finding alternative IC design strategies to implement typical analog functions exploiting Digital in-Concept Design Methodologies (DCDM). This idea of re-thinking analog functions in digital terms has shown that Analog ICs blocks can also avail of the feature-size shrinking and energy efficiency of new technologies. This thesis deals with the development of DCDM, demonstrating its compatibility for Ultra-Low-Voltage (ULV) and Power (ULP) IoT applications. This work proves this state ment through the proposing of new digital-based analog blocks, such as an Operational Transconductance Amplifiers (OTAs) and an ac-coupled Bio-signal Amplifier (BioAmp). As an initial contribution, for the first time, a silicon demonstration of an embryonic Digital-Based OTA (DB-OTA) published in 2013 is exhibited. The fabricated DB-OTA test chip occupies a compact area of 1,426 µm2 , operating at supply voltages (VDD) down to 300 mV, consuming only 590 pW while driving a capacitive load of 80pF. With a Total Harmonic Distortion (THD) lower than 5% for a 100mV input signal swing, its measured small-signal figure of merit (FOMS) and large-signal figure of merit (FOML) are 2,101 V −1 and 1,070, respectively. To the best of this thesis author’s knowledge, this measured power is the lowest reported to date in OTA literature, and its figures of merit are the best in sub-500mV OTAs reported to date. As the second step, mainly due to the robustness limitation of previous DB-OTA, a novel calibration-free digital-based topology is proposed, named here as Digital OTA (DIG OTA). A 180-nm DIGOTA test chip is also developed exhibiting an area below the 1000 µm2 wall, 2.4nW power under 150pF load, and a minimum VDD of 0.25 V. The proposed DIGOTA is more digital-like compared with DB-OTA since no pseudo-resistor is needed. As the last contribution, the previously proposed DIGOTA is then used as a building block to demonstrate the operation principle of power-efficient ULV and ultra-low area (ULA) fully-differential, digital-based Operational Transconductance Amplifier (OTA), suitable for microscale biosensing applications (BioDIGOTA) such as extreme low area Body Dust. Measured results in 180nm CMOS confirm that the proposed BioDIGOTA can work with a supply voltage down to 400 mV, consuming only 95 nW. The BioDIGOTA layout occupies only 0.022 mm2 of total silicon area, lowering the area by 3.22X times compared to the current state of the art while keeping reasonable system performance, such as 7.6 Noise Efficiency Factor (NEF) with 1.25 µVRMS input-referred noise over a 10 Hz bandwidth, 1.8% of THD, 62 dB of the common-mode rejection ratio (CMRR) and 55 dB of power supply rejection ratio (PSRR). After reviewing the current DCDM trend and all proposed silicon demonstrations, the thesis concludes that, despite the current analog design strategies involved during the analog block development

Computational Sprinting: Exceeding Sustainable Power in Thermally Constrained Systems

Although process technology trends predict that transistor sizes will continue to shrink for a few more generations, voltage scaling has stalled and thus future chips are projected to be increasingly more power hungry than previous generations. Particularly in mobile devices which are severely cooling constrained, it is estimated that the peak operation of a future chip could generate heat ten times faster than than the device can sustainably vent. However, many mobile applications do not demand sustained performance; rather they comprise short bursts of computation in response to sporadic user activity. To improve responsiveness for such applications, this dissertation proposes computational sprinting, in which a system greatly exceeds sustainable power margins (by up to 10Ã?) to provide up to a few seconds of high-performance computation when a user interacts with the device. Computational sprinting exploits the material property of thermal capacitance to temporarily store the excess heat generated when sprinting. After sprinting, the chip returns to sustainable power levels and dissipates the stored heat when the system is idle. This dissertation: (i) broadly analyzes thermal, electrical, hardware, and software considerations to analyze the feasibility of engineering a system which can provide the responsiveness of a plat- form with 10Ã? higher sustainable power within today\u27s cooling constraints, (ii) leverages existing sources of thermal capacitance to demonstrate sprinting on a real system today, and (iii) identifies the energy-performance characteristics of sprinting operation to determine runtime sprint pacing policies