Low Power SoC Design

The design of Low Power Systems-on-Chips (SoC) in very deep submicron technologies becomes a very complex task that has to bridge very high level system description with low-level considerations due to technology defaults and variations and increasing system and circuit complexity. This paper describes the major low-level issues, such as dynamic and static power consumption, temperature, technology variations, interconnect, DFM, reliability and yield, and their impact on high-level design, such as the design of multi-Vdd, fault-tolerant, redundant or adaptive chip architectures. Some very low power System-on-Chip (SoC) will be presented in three domains: wireless sensor networks, vision sensors and mobile TV

Efficient Neuromorphic Computing Enabled by Spin-Transfer Torque: Devices, Circuits and Systems

Present day computers expend orders of magnitude more computational resources to perform various cognitive and perception related tasks that humans routinely perform everyday. This has recently resulted in a seismic shift in the field of computation where research efforts are being directed to develop a neurocomputer that attempts to mimic the human brain by nanoelectronic components and thereby harness its efficiency in recognition problems. Bridging the gap between neuroscience and nanoelectronics, this thesis demonstrates the encoding of biological neural and synaptic functionalities in the underlying physics of electron spin. Description of various spin-transfer torque mechanisms that can be potentially utilized for realizing neuro-mimetic device structures is provided. A cross-layer perspective extending from the device to the circuit and system level is presented to envision the design of an All-Spin neuromorphic processor enabled with on-chip learning functionalities. Device-circuit-algorithm co-simulation framework calibrated to experimental results suggest that such All-Spin neuromorphic systems can potentially achieve almost two orders of magnitude energy improvement in comparison to state-of-the-art CMOS implementations

Low power digital baseband core for wireless Micro-Neural-Interface using CMOS sub/near-threshold circuit

This thesis presents the work on designing and implementing a low power digital baseband core with custom-tailored protocol for wirelessly powered Micro-Neural-Interface (MNI) System-on-Chip (SoC) to be implanted within the skull to record cortical neural activities. The core, on the tag end of distributed sensors, is designed to control the operation of individual MNI and communicate and control MNI devices implanted across the brain using received downlink commands from external base station and store/dump targeted neural data uplink in an energy efficient manner. The application specific protocol defines three modes (Time Stamp Mode, Streaming Mode and Snippet Mode) to extract neural signals with on-chip signal conditioning and discrimination. In Time Stamp Mode, Streaming Mode and Snippet Mode, the core executes basic on-chip spike discrimination and compression, real-time monitoring and segment capturing of neural signals so single spike timing as well as inter-spike timing can be retrieved with high temporal and spatial resolution. To implement the core control logic using sub/near-threshold logic, a novel digital design methodology is proposed which considers INWE (Inverse-Narrow-Width-Effect), RSCE (Reverse-Short-Channel-Effect) and variation comprehensively to size the transistor width and length accordingly to achieve close-to-optimum digital circuits. Ultra-low-power cell library containing 67 cells including physical cells and decoupling capacitor cells using the optimum fingers is designed, laid-out, characterized, and abstracted. A robust on-chip sense-amp-less SRAM memory (8X32 size) for storing neural data is implemented using 8T topology and LVT fingers. The design is validated with silicon tapeout and measurement shows the digital baseband core works at 400mV and 1.28 MHz system clock with an average power consumption of 2.2 μW, resulting in highest reported communication power efficiency of 290Kbps/μW to date

Low Power Decoding Circuits for Ultra Portable Devices

A wide spread of existing and emerging battery driven wireless devices do not necessarily demand high data rates. Rather, ultra low power, portability and low cost are the most desired characteristics. Examples of such applications are wireless sensor networks (WSN), body area networks (BAN), and a variety of medical implants and health-care aids. Being small, cheap and low power for the individual transceiver nodes, let those to be used in abundance in remote places, where access for maintenance or recharging the battery is limited. In such scenarios, the lifetime of the battery, in most cases, determines the lifetime of the individual nodes. Therefore, energy consumption has to be so low that the nodes remain operational for an extended period of time, even up to a few years. It is known that using error correcting codes (ECC) in a wireless link can potentially help to reduce the transmit power considerably. However, the power consumption of the coding-decoding hardware itself is critical in an ultra low power transceiver node. Power and silicon area overhead of coding-decoding circuitry needs to be kept at a minimum in the total energy and cost budget of the transceiver node. In this thesis, low power approaches in decoding circuits in the framework of the mentioned applications and use cases are investigated. The presented work is based on the 65nm CMOS technology and is structured in four parts as follows: In the first part, goals and objectives, background theory and fundamentals of the presented work is introduced. Also, the ECC block in coordination with its surrounding environment, a low power receiver chain, is presented. Designing and implementing an ultra low power and low cost wireless transceiver node introduces challenges that requires special considerations at various levels of abstraction. Similarly, a competitive solution often occurs after a conclusive design space exploration. The proposed decoder circuits in the following parts are designed to be embedded in the low power receiver chain, that is introduced in the first part. Second part, explores analog decoding method and its capabilities to be embedded in a compact and low power transceiver node. Analog decod- ing method has been theoretically introduced over a decade ago that followed with early proof of concept circuits that promised it to be a feasible low power solution. Still, with the increased popularity of low power sensor networks, it has not been clear how an analog decoding approach performs in terms of power, silicon area, data rate and integrity of calculations in recent technologies and for low data rates. Ultra low power budget, small size requirement and more relaxed demands on data rates suggests a decoding circuit with limited complexity. Therefore, the four-state (7,5) codes are considered for hardware implementation. Simulations to chose the critical design factors are presented. Consequently, to evaluate critical specifications of the decoding circuit, three versions of analog decoding circuit with different transistor dimensions fabricated. The measurements results reveal different trade-off possibilities as well as the potentials and limitations of the analog decoding approach for the target applications. Measurements seem to be crucial, since the available computer-aided design (CAD) tools provide limited assistance and precision, given the amount of calculations and parameters that has to be included in the simulations. The largest analog decoding core (AD1) takes 0.104mm2 on silicon and the other two (AD2 and AD3) take 0.035mm2 and 0.015mm2, respectively. Consequently, coding gain in trade-off with silicon area and throughput is presented. The analog decoders operate with 0.8V supply. The achieved coding gain is 2.3 dB at bit error rates (BER)=0.001 and 10 pico-Joules per bit (pJ/b) energy efficiency is reached at 2 Mbps. Third part of this thesis, proposes an alternative low power digital decoding approach for the same codes. The desired compact and low power goal has been pursued by designing an equivalent digital decoding circuit that is fabricated in 65nm CMOS technology and operates in low voltage (near-threshold) region. The architecture of the design is optimized in system and circuit levels to propose a competitive digital alternative. Similarly, critical specifications of the decoder in terms of power, area, data rate (speed) and integrity are reported according to the measurements. The digital implementation with 0.11mm2 area, consumes minimum energy at 0.32V supply which gives 9 pJ/b energy efficiency at 125 kb/s and 2.9 dB coding gain at BER=0.001. The forth and last part, compares the proposed design alternatives based on the fabricated chips and the results attained from the measurements to conclude the most suitable solution for the considered target applications. Advantages and disadvantages of both approaches are discussed. Possible extensions of this work is introduced as future work

Integrated Circuit Design for Miniaturized, Trackable, Ultrasound Based Biomedical Implants

This thesis focuses on the design of an ultrasonography compatible implantable sensor platform, as a novel approach that implements a miniaturized, battery-less, real-time trackable parallel biosensing system. In addition to the frontend circuit, a sub-nW fully integrated pH sensor is designed in a way that can be easily integrated with the proposed sonography-compatible sensor platform. Combining the two integrated circuits together, the whole system will be able to map in vivo physiological information acquired from a distributed set of sensors on top of the ultrasound movie, leading to the idea envisioned as “augmented ultrasonography”. Implemented in a 0.18 μm technology, an ultrasound power and data frontend circuit is designed to enable medical sensing implants to operate in an ultrasonography compatible way. When placed within the field of view of an imaging transducer, the frontend circuit harvests the power through a piece of piezo crystal from a minimally modified brightness-mode (B-mode) ultrasound imaging process that is commonly adopted in modern medical practices. The implant can also establish bi-directional data communication channels with the imaging transducer, allowing data to be transmitted in a way synchronized to the frame rate of the B-mode film. The design of the circuit is made possible by a combination of ultra-low-power circuit techniques and novel frontend circuit topologies, as imaging ultrasound waves in the form of short pulses with extremely low duty cycle poses challenges that has not previously seen in other implantable sensor systems. The proposed prototype achieves a total area of 0.6mm² for the integrated circuit (IC), as well as 71mm theoretical maximum implantable depth (up to 40 mm is verified experimentally). These two together give opportunities for this design to become the next generation solution for deep-tissue bio-sensing implants. Realized using the same 0.18 μm technology, the fully integrated pH sensor is designed to deliver accurate pH readouts, at a reasonable speed of 1 sample per second, while consuming only 0.72 nW of power. Using an ion-sensitive field effect transistor (ISFET) and reference field effect transistor pair (REFET), the IC requires minimum additional post fabrication to deliver 10-bit resolution pH readouts at an end-to-end sensitivity of 65.8 LSB/pH. When working as a standalone device, this work advances the state-of-the-art of ISFET based pH sensor design. With an addition of 0.46 mm² of area, it is possible to integrate it with the ultrasound sonography compatible implant platform. This potential integration will further advance the vision of the augmented ultrasonography: real-time display of physiological information in a B-mode film, with the help from a distributed bio-sensor system for deep-tissue physiology monitoring

Nano-Watt Modular Integrated Circuits for Wireless Neural Interface.

In this work, a nano-watt modular neural interface circuit is proposed for ECoG neuroprosthetics. The main purposes of this work are threefold: (1) optimizing the power-performance of the neural interface circuits based on ECoG signal characteristics, (2) equipping a stimulation capability, and (3) providing a modular system solution to expand functionality. To achieve these aims, the proposed system introduces the following contributions/innovations: (1) power-noise optimization based on the ECoG signal driven analysis, (2) extreme low-power analog front-ends, (3) Manchester clock-edge modulation clock data recovery, (4) power-efficient data compression, (5) integrated stimulator with fully programmable waveform, (6) wireless signal transmission through skin, and (7) modular expandable design. Towards these challenges and contributions, three different ECoG neural interface systems, ENI-1, ENI-16, and ENI-32, have been designed, fabricated, and tested. The first ENI system(ENI-1) is a one-channel analog front-end and fabricated in a 0.25µm CMOS process with chopper stabilized pseudo open-loop preamplifier and area-efficient SAR ADC. The measured channel power, noise and area are 1.68µW at 2.5V power-supply, 1.69µVrms (NEF=2.43), and 0.0694mm^2, respectively. The fabricated IC is packaged with customized miniaturized package. In-vivo human EEG is successfully measured with the fabricated ENI-1-IC. To demonstrate a system expandability and wireless link, ENI-16 IC is fabricated in 0.25µm CMOS process and has sixteen channels with a push-pull preamplifier, asynchronous SAR ADC, and intra-skin communication(ISCOM) which is a new way of transmitting the signal through skin. The measured channel power, noise and area are 780nW, 4.26µVrms (NEF=5.2), and 2.88mm^2, respectively. With the fabricated ENI-16-IC, in-vivo epidural ECoG from monkey is successfully measured. As a closed-loop system, ENI-32 focuses on optimizing the power performance based on a bio-signal property and integrating stimulator. ENI-32 is fabricated in 0.18µm CMOS process and has thirty-two recording channels and four stimulation channels with a cyclic preamplifier, data compression, asymmetric wireless transceiver (Tx/Rx). The measured channel power, noise and area are 140nW (680nW including ISCOM), 3.26µVrms (NEF=1.6), and 5.76mm^2, respectively. The ENI-32 achieves an order of magnitude power reduction while maintaining the system performance. The proposed nano-watt ENI-32 can be the first practical wireless closed-loop solution with a practically miniaturized implantable device.PhDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/98064/1/schang_1.pd

Digital and Analog Computing Paradigms in Printed Electronics

Da das Ende von Moore\u27s Gesetz schon absehbar ist, müssen neue Wege gefunden werden um den innovationsgetriebenen IT-Markt mit neuartiger Elektronik zu sättigen. Durch den Einsatz von kostengünstiger Hardware mit flexiblem Formfaktor, welche auf neuartigen Materialien und Technologien beruhen, können neue Anwendungsbereiche erschlossen werden, welche über konventionelle siliziumbasierte Elektronik hinausgehen. Im Fokus sind hier insbesondere elektronische Systeme, welche es ermöglichen Konsumgüter für den täglichen Bedarf zu überwachen - z.B. im Zusammenhang einer Qualitätskontrolle - indem sie in das Produkt integriert werden als Teil einer intelligenten Verpackung und dadurch nur begrenzte Produktlebenszeit erfordern. Weitere vorhersehbare Anwendungsbereiche sind tragbare Elektronik oder Produkte für das "Internet der Dinge". Hier entstehen Systemanforderungen wie flexible, dehnbare Hardware unter Einsatz von ungiftigen Materialien. Aus diesem Grund werden additive Technologien herangezogen, wie zum Beispiel gedruckte Elektronik, welche als komplementär zu siliziumbasierten Technologien betrachtet wird, da sie durch den simplen Herstellungsprozess sehr geringe Produktionskosten ermöglicht, und darüber hinaus auf ungiftigen und funktionalen Materialien basiert, welche auf flexible Plastik- oder Papiersubstrate aufgetragen werden können. Unter den verschiedenen Druckprozessen ist insbesondere der Tintenstrahldruck für zukünftige gedruckte Elektronikanwendungen interessant, da er eine Herstellung vor Ort und nach Bedarf ermöglicht auf Grund seines maskenlosen Druckprozesses. Da sich jedoch die Technologie der Tintenstrahl-druckbaren Elektronik in der Frühphasenentwicklung befindet, ist es fraglich ob Schaltungen für zukünftige Anwendungsfelder überhaupt entworfen werden können, beziehungsweise ob sie überhaupt herstellbar sind. Da die laterale Auflösung von Druckprozessen sich um mehrere Größenordnungen über siliziumbasierten Herstellungstechnologien befindet und des Weiteren entweder nur p- oder n-dotierte Transistoren verfügbar sind, können existierende Schaltungsentwürfe nicht direkt in die gedruckte Elektronik überführt werden. Dies führt zu der wissenschaftlichen Fragestellung, welche Rechenparadigmen überhaupt sinnvoll anwendbar sind im Bereich der gedruckten Elektronik. Die Beantwortung dieser Frage wird Schaltungsdesignern in der Zukunft helfen, erfolgreich gedruckte Schaltungen für den sich rasch entwickelnden Konsumgütermarkt zu entwerfen und zu produzieren. Aus diesem Anlass exploriert diese Arbeit verschiedene Rechenparadigmen und Schaltungsentwürfe, welche als essenziell für zukünftige, gedruckte Systeme betrachtet werden. Die erfolgte Analyse beruht auf der recht jungen "Electrolyte-gated Transistor" (EGT) Technologie, welche auf einem kostengünstigen Tintenstrahldruckverfahren basiert und sehr geringe Betriebsspannungen ermöglicht. Da bisher nur einfache Logik-Gatter in der EGT-Technologie realisiert wurden, wird in dieser Arbeit der Entwurfsraum weiter exploriert, durch die Entwicklung von gedruckten Speicherbausteinen, Lookup Tabellen, künstliche Neuronen und Entscheidungsbäume. Besonders bei dem künstlichen Neuron und den Entscheidungsbäumen wird Bezug auf Hardware-Implementierungen von Algorithmen des maschinellen Lernens gemacht und die Skalierung der Schaltungen auf die Anwendungsebene aufgezeigt. Die Rechenparadigmen, welche in dieser Arbeit evaluiert wurden, reichen von digitalen, analogen, neuromorphen Berechnungen bis zu stochastischen Verfahren. Zusätzlich wurden individuell anpassbare Schaltungsentwürfe untersucht, welche durch das Tintenstrahldruckverfahren ermöglicht werden und zu substanziellen Verbesserungen bezüglich des Flächenbedarfs, Leistungsverbrauch und Schaltungslatenzen führen, indem variable Entwurfsparameter in die Schaltung fest verdrahtet werden. Da die explorierten Schaltungen die Komplexität von bisher hergestellter, gedruckter Hardware weit übertreffen, ist es prinzipiell nicht automatisch garantiert, dass sie herstellbar sind, was insbesondere die nicht-digitalen Schaltungen betrifft. Aus diesem Grund wurden in dieser Arbeit EGT-basierte Hardware-Prototypen hergestellt und bezüglich Flächenbedarf, Leistungsverbrauch und Latenz charakterisiert. Die Messergebnisse können verwendet werden, um eine Extrapolation auf komplexere anwendungsbezogenere Schaltungsentwürfe durchzuführen. In diesem Zusammenhang wurden Validierungen von den entwickelten Hardware-Implementierungen von Algorithmen des maschinellen Lernens durchgeführt, um einen Wirksamkeitsnachweis zu erhalten. Die Ergebnisse dieser Thesis führen zu mehreren Schlussfolgerungen. Zum ersten kann gefolgert werden, dass die sequentielle Verarbeitung von Algorithmen in gedruckter EGT-basierter Hardware prinzipiell möglich ist, da, wie in dieser Arbeit dargestellt wird, neben kombinatorischen Schaltungen auch Speicherbausteine implementiert werden können. Letzteres wurde experimentell validiert. Des Weiteren können analoge und neuromorphe Rechenparadigmen sinnvoll eingesetzt werden, um gedruckte Hardware für maschinelles Lernen zu realisieren, um gegenüber konventionellen Methoden die Komplexität von Schaltungsentwürfen erheblich zu minimieren, welches schlussendlich zu einer höheren Produktionsausbeute im Herstellungsprozess führt. Ebenso können neuronale Netzwerkarchitekturen, welche auf Stochastic Computing basieren, zur Reduzierung des Hardwareumfangs gegenüber konventionellen Implementierungen verwendet werden. Letztlich kann geschlussfolgert werden, dass durch den Tintenstrahldruckprozess Schaltungsentwürfe bezüglich Kundenwünschen während der Herstellung individuell angepasst werden können, um die Anwendbarkeit von gedruckter Hardware generell zu erhöhen, da auch hier geringerer Hardwareaufwand im Vergleich zu konventionellen Schaltungsentwürfen erreicht wird. Es wird antizipiert, dass die in dieser Thesis vorgestellten Forschungsergebnisse relevant sind für Informatiker, Elektrotechniker und Materialwissenschaftler, welche aktiv im Bereich der druckbaren Elektronik arbeiten. Die untersuchten Rechenparadigmen und ihr Einfluss auf Verhalten und wichtige Charakteristiken gedruckter Hardware geben Einblicke darüber, wie gedruckte Schaltungen in der Zukunft effizient umgesetzt werden können, um neuartige auf Druckverfahren-basierte Produkte im Elektronikbereich zu ermöglichen