A scalable multi-core architecture with heterogeneous memory structures for Dynamic Neuromorphic Asynchronous Processors (DYNAPs)

Neuromorphic computing systems comprise networks of neurons that use asynchronous events for both computation and communication. This type of representation offers several advantages in terms of bandwidth and power consumption in neuromorphic electronic systems. However, managing the traffic of asynchronous events in large scale systems is a daunting task, both in terms of circuit complexity and memory requirements. Here we present a novel routing methodology that employs both hierarchical and mesh routing strategies and combines heterogeneous memory structures for minimizing both memory requirements and latency, while maximizing programming flexibility to support a wide range of event-based neural network architectures, through parameter configuration. We validated the proposed scheme in a prototype multi-core neuromorphic processor chip that employs hybrid analog/digital circuits for emulating synapse and neuron dynamics together with asynchronous digital circuits for managing the address-event traffic. We present a theoretical analysis of the proposed connectivity scheme, describe the methods and circuits used to implement such scheme, and characterize the prototype chip. Finally, we demonstrate the use of the neuromorphic processor with a convolutional neural network for the real-time classification of visual symbols being flashed to a dynamic vision sensor (DVS) at high speed.Comment: 17 pages, 14 figure

Energy-Efficient Digital Circuit Design using Threshold Logic Gates

abstract: Improving energy efficiency has always been the prime objective of the custom and automated digital circuit design techniques. As a result, a multitude of methods to reduce power without sacrificing performance have been proposed. However, as the field of design automation has matured over the last few decades, there have been no new automated design techniques, that can provide considerable improvements in circuit power, leakage and area. Although emerging nano-devices are expected to replace the existing MOSFET devices, they are far from being as mature as semiconductor devices and their full potential and promises are many years away from being practical. The research described in this dissertation consists of four main parts. First is a new circuit architecture of a differential threshold logic flipflop called PNAND. The PNAND gate is an edge-triggered multi-input sequential cell whose next state function is a threshold function of its inputs. Second a new approach, called hybridization, that replaces flipflops and parts of their logic cones with PNAND cells is described. The resulting \hybrid circuit, which consists of conventional logic cells and PNANDs, is shown to have significantly less power consumption, smaller area, less standby power and less power variation. Third, a new architecture of a field programmable array, called field programmable threshold logic array (FPTLA), in which the standard lookup table (LUT) is replaced by a PNAND is described. The FPTLA is shown to have as much as 50% lower energy-delay product compared to conventional FPGA using well known FPGA modeling tool called VPR. Fourth, a novel clock skewing technique that makes use of the completion detection feature of the differential mode flipflops is described. This clock skewing method improves the area and power of the ASIC circuits by increasing slack on timing paths. An additional advantage of this method is the elimination of hold time violation on given short paths. Several circuit design methodologies such as retiming and asynchronous circuit design can use the proposed threshold logic gate effectively. Therefore, the use of threshold logic flipflops in conventional design methodologies opens new avenues of research towards more energy-efficient circuits.Dissertation/ThesisDoctoral Dissertation Computer Science 201

Variability-aware low-power techniques for nanoscale mixed-signal circuits.

New circuit design techniques that accommodate lower supply voltages necessary for portable systems need to be integrated into the semiconductor intellectual property (IP) core. Systems that once worked at 3.3 V or 2.5 V now need to work at 1.8 V or lower, without causing any performance degradation. Also, the fluctuation of device characteristics caused by process variation in nanometer technologies is seen as design yield loss. The numerous parasitic effects induced by layouts, especially for high-performance and high-speed circuits, pose a problem for IC design. Lack of exact layout information during circuit sizing leads to long design iterations involving time-consuming runs of complex tools. There is a strong need for low-power, high-performance, parasitic-aware and process-variation-tolerant circuit design. This dissertation proposes methodologies and techniques to achieve variability, power, performance, and parasitic-aware circuit designs. Three approaches are proposed: the single iteration automatic approach, the hybrid Monte Carlo and design of experiments (DOE) approach, and the corner-based approach. Widely used mixed-signal circuits such as analog-to-digital converter (ADC), voltage controlled oscillator (VCO), voltage level converter and active pixel sensor (APS) have been designed at nanoscale complementary metal oxide semiconductor (CMOS) and subjected to the proposed methodologies. The effectiveness of the proposed methodologies has been demonstrated through exhaustive simulations. Apart from these methodologies, the application of dual-oxide and dual-threshold techniques at circuit level in order to minimize power and leakage is also explored

Design Space Re-Engineering for Power Minimization in Modern Embedded Systems

Power minimization is a critical challenge for modern embedded system design. Recently, due to the rapid increase of system's complexity and the power density, there is a growing need for power control techniques at various design levels. Meanwhile, due to technology scaling, leakage power has become a significant part of power dissipation in the CMOS circuits and new techniques are needed to reduce leakage power. As a result, many new power minimization techniques have been proposed such as voltage island, gate sizing, multiple supply and threshold voltage, power gating and input vector control, etc. These design options further enlarge the design space and make it prohibitively expensive to explore for the most energy efficient design solution. Consequently, heuristic algorithms and randomized algorithms are frequently used to explore the design space, seeking sub-optimal solutions to meet the time-to-market requirements. These algorithms are based on the idea of truncating the design space and restricting the search in a subset of the original design space. While this approach can effectively reduce the runtime of searching, it may also exclude high-quality design solutions and cause design quality degradation. When the solution to one problem is used as the base for another problem, such solution quality degradation will accumulate. In modern electronics system design, when several such algorithms are used in series to solve problems in different design levels, the final solution can be far off the optimal one. In my Ph.D. work, I develop a {\em re-engineering} methodology to facilitate exploring the design space of power efficient embedded systems design. The direct goal is to enhance the performance of existing low power techniques. The methodology is based on the idea that design quality can be improved via iterative ``re-shaping'' the design space based on the ``bad'' structure in the obtained design solutions; the searching run-time can be reduced by the guidance from previous exploration. This approach can be described in three phases: (1) apply the existing techniques to obtain a sub-optimal solution; (2) analyze the solution and expand the design space accordingly; and (3) re-apply the technique to re-explore the enlarged design space. We apply this methodology at different levels of embedded system design to minimize power: (i) switching power reduction in sequential logic synthesis; (ii) gate-level static leakage current reduction; (iii) dual threshold voltage CMOS circuits design; and (iv) system-level energy-efficient detection scheme for wireless sensor networks. An extensive amount of experiments have been conducted and the results have shown that this methodology can effectively enhance the power efficiency of the existing embedded system design flows with very little overhead

IMPACT OF DYNAMIC VOLTAGE SCALING (DVS) ON CIRCUIT OPTIMIZATION

Circuit designers perform optimization procedures targeting speed and power during the design of a circuit. Gate sizing can be applied to optimize for speed, while Dual-VT and Dynamic Voltage Scaling (DVS) can be applied to optimize for leakage and dynamic power, respectively. Both gate sizing and Dual-VT are design-time techniques, which are applied to the circuit at a fixed voltage. On the other hand, DVS is a run-time technique and implies that the circuit will be operating at a different voltage than that used during the optimization phase at design-time. After some analysis, the risk of non-critical paths becoming critical paths at run-time is detected under these circumstances. The following questions arise: 1) should we take DVS into account during the optimization phase? 2) Does DVS impose any restrictions while performing design-time circuit optimizations?. This thesis is a case study of applying DVS to a circuit that has been optimized for speed and power, and aims at answering the previous two questions. We used a 45-nm CMOS design kit and flow. Synthesis, placement and routing, and timing analysis were applied to the benchmark circuit ISCAS?85 c432. Logical Effort and Dual-VT algorithms were implemented and applied to the circuit to optimize for speed and leakage power, respectively. Optimizations were run for the circuit operating at different voltages. Finally, the impact of DVS on circuit optimization was studied based on HSPICE simulations sweeping the supply voltage for each optimization. The results showed that DVS had no impact on gate sizing optimizations, but it did on Dual-VT optimizations. It is shown that we should not optimize at an arbitrary voltage. Moreover, simulations showed that Dual-VT optimizations should be performed at the lowest voltage that DVS is intended to operate, otherwise non-critical paths will become critical paths at run-time

Design Techniques for Energy-Quality Scalable Digital Systems

Energy efficiency is one of the key design goals in modern computing. Increasingly complex tasks are being executed in mobile devices and Internet of Things end-nodes, which are expected to operate for long time intervals, in the orders of months or years, with the limited energy budgets provided by small form-factor batteries. Fortunately, many of such tasks are error resilient, meaning that they can toler- ate some relaxation in the accuracy, precision or reliability of internal operations, without a significant impact on the overall output quality. The error resilience of an application may derive from a number of factors. The processing of analog sensor inputs measuring quantities from the physical world may not always require maximum precision, as the amount of information that can be extracted is limited by the presence of external noise. Outputs destined for human consumption may also contain small or occasional errors, thanks to the limited capabilities of our vision and hearing systems. Finally, some computational patterns commonly found in domains such as statistics, machine learning and operational research, naturally tend to reduce or eliminate errors. Energy-Quality (EQ) scalable digital systems systematically trade off the quality of computations with energy efficiency, by relaxing the precision, the accuracy, or the reliability of internal software and hardware components in exchange for energy reductions. This design paradigm is believed to offer one of the most promising solutions to the impelling need for low-energy computing. Despite these high expectations, the current state-of-the-art in EQ scalable design suffers from important shortcomings. First, the great majority of techniques proposed in literature focus only on processing hardware and software components. Nonetheless, for many real devices, processing contributes only to a small portion of the total energy consumption, which is dominated by other components (e.g. I/O, memory or data transfers). Second, in order to fulfill its promises and become diffused in commercial devices, EQ scalable design needs to achieve industrial level maturity. This involves moving from purely academic research based on high-level models and theoretical assumptions to engineered flows compatible with existing industry standards. Third, the time-varying nature of error tolerance, both among different applications and within a single task, should become more central in the proposed design methods. This involves designing “dynamic” systems in which the precision or reliability of operations (and consequently their energy consumption) can be dynamically tuned at runtime, rather than “static” solutions, in which the output quality is fixed at design-time. This thesis introduces several new EQ scalable design techniques for digital systems that take the previous observations into account. Besides processing, the proposed methods apply the principles of EQ scalable design also to interconnects and peripherals, which are often relevant contributors to the total energy in sensor nodes and mobile systems respectively. Regardless of the target component, the presented techniques pay special attention to the accurate evaluation of benefits and overheads deriving from EQ scalability, using industrial-level models, and on the integration with existing standard tools and protocols. Moreover, all the works presented in this thesis allow the dynamic reconfiguration of output quality and energy consumption. More specifically, the contribution of this thesis is divided in three parts. In a first body of work, the design of EQ scalable modules for processing hardware data paths is considered. Three design flows are presented, targeting different technologies and exploiting different ways to achieve EQ scalability, i.e. timing-induced errors and precision reduction. These works are inspired by previous approaches from the literature, namely Reduced-Precision Redundancy and Dynamic Accuracy Scaling, which are re-thought to make them compatible with standard Electronic Design Automation (EDA) tools and flows, providing solutions to overcome their main limitations. The second part of the thesis investigates the application of EQ scalable design to serial interconnects, which are the de facto standard for data exchanges between processing hardware and sensors. In this context, two novel bus encodings are proposed, called Approximate Differential Encoding and Serial-T0, that exploit the statistical characteristics of data produced by sensors to reduce the energy consumption on the bus at the cost of controlled data approximations. The two techniques achieve different results for data of different origins, but share the common features of allowing runtime reconfiguration of the allowed error and being compatible with standard serial bus protocols. Finally, the last part of the manuscript is devoted to the application of EQ scalable design principles to displays, which are often among the most energy- hungry components in mobile systems. The two proposals in this context leverage the emissive nature of Organic Light-Emitting Diode (OLED) displays to save energy by altering the displayed image, thus inducing an output quality reduction that depends on the amount of such alteration. The first technique implements an image-adaptive form of brightness scaling, whose outputs are optimized in terms of balance between power consumption and similarity with the input. The second approach achieves concurrent power reduction and image enhancement, by means of an adaptive polynomial transformation. Both solutions focus on minimizing the overheads associated with a real-time implementation of the transformations in software or hardware, so that these do not offset the savings in the display. For each of these three topics, results show that the aforementioned goal of building EQ scalable systems compatible with existing best practices and mature for being integrated in commercial devices can be effectively achieved. Moreover, they also show that very simple and similar principles can be applied to design EQ scalable versions of different system components (processing, peripherals and I/O), and to equip these components with knobs for the runtime reconfiguration of the energy versus quality tradeoff

DESIGN AND SYNTHESIS OF HIGH DENSITY INTEGRATED CIRCUITS

Gordon E. Moore, a co-founder of Fairchild Semiconductor, and later of Intel, predicted that after 1980 the complexity of an Integrated Circuit would be expected to double every two years. The prevision made by Moore held for decades, for this reason it is also called \u201cMoore\u2019s law\u201d. The trend in ICs is driven by a reduction of area and power consumption. Today scaled CMOS technologies are the main solution for digital processing. However, the interconnection scaling is not optimal. At every new technology node, the number of metal layers and their thickness increases, exploiting the vertical direction. The reduction of the minimum distance between interconnections and the growth in vertical dimension increase the parasitic capacitance and consequently the dynamic power consumption. Moreover, due to the non-optimal scaling of the interconnections, signal routing is becoming more and more challenging at every technology node advancement. Very scaled technologies make possible to reach a great transistor density. However, the design must comply to strict rules for metal interconnections. The aim of this thesis is to find possible solutions to the disadvantages of scaled CMOS technologies. This goal is obtained in two different ways: using ad-hoc design techniques on today CMOS technologies and finding new approaches to logic synthesis of nanocrossbars, that are an emerging post-CMOS technology. The two approaches used corresponds to the two parts of this thesis. The first part presents the design of an Associative Memory focusing the attention on develop design and logic synthesis techniques to reduce power consumption. The field of applicability of AMs is real-time pattern-recognition tasks. The possible uses range from scientific calculations to image processing for intelligent autonomous devices to image reconstruction for electro-medical apparatuses. In particular AMs are used in High Energy Physics (HEP) experiments to detect particle tracks. HEP experiments generate a huge amount of data, but it is necessary to select and save only the most interesting tracks. Being the data compared in parallel, AMs are synchronous ICs that have a very peaked power consumption, and therefore it is necessary to minimize the power consumption. This AM is designed within the projects IMPART and HTT in 28 nm CMOS technology, using a fully-CMOS approach. The logic is based on the propagation of a \u201ckill signal\u201d that, if one of the bits in a word is not matching, inhibits the switching of the following cells. Thanks to this feature, the designed AM array consumes less than 0.7 fJ/bit. A prototype has been fabricated and it has proven to be functional. The final chip will be installed in the data acquisition chain of ATLAS experiment on HL-LHC at CERN. In the future nanocrossbars are expected to reduce device dimensions and interconnection complexity with respect to CMOS. Logic functions are obtained with switching lattices of four-terminal switches. The research activity on nanocrossbars is done within the project NANOxCOMP. To improve synthesis are used some algorithmic approaches based on Boolean function decomposition and regularities, in particular P-circuits, EXOR-Projected Sums of Products (EP-SOP), Dimension-reducible (D-red) functions and autosymmetric functions. The decomposed functions are implemented into lattices using internal and external decomposition methods. Experimental results show that this approaches reduce the complexity of the single synthesis problem and leads, in average, to a reduction of lattice area and synthesis time. Lattices are made of self-assembled structures and they have a non-negligible defectivity ratio. To cope with this limitation, some techniques to reduce sensitivity to defects have been studied

Micro-architecture level low power design for microprocessors

Ph.DDOCTOR OF PHILOSOPH

Design for Reliability and Low Power in Emerging Technologies

Die fortlaufende Verkleinerung von Transistor-Strukturgrößen ist einer der wichtigsten Antreiber für das Wachstum in der Halbleitertechnologiebranche. Seit Jahrzehnten erhöhen sich sowohl Integrationsdichte als auch Komplexität von Schaltkreisen und zeigen damit einen fortlaufenden Trend, der sich über alle modernen Fertigungsgrößen erstreckt. Bislang ging das Verkleinern von Transistoren mit einer Verringerung der Versorgungsspannung einher, was zu einer Reduktion der Leistungsaufnahme führte und damit eine gleichbleibenden Leistungsdichte sicherstellte. Doch mit dem Beginn von Strukturgrößen im Nanometerbreich verlangsamte sich die fortlaufende Skalierung. Viele Schwierigkeiten, sowie das Erreichen von physikalischen Grenzen in der Fertigung und Nicht-Idealitäten beim Skalieren der Versorgungsspannung, führten zu einer Zunahme der Leistungsdichte und, damit einhergehend, zu erschwerten Problemen bei der Sicherstellung der Zuverlässigkeit. Dazu zählen, unter anderem, Alterungseffekte in Transistoren sowie übermäßige Hitzeentwicklung, nicht zuletzt durch stärkeres Auftreten von Selbsterhitzungseffekten innerhalb der Transistoren. Damit solche Probleme die Zuverlässigkeit eines Schaltkreises nicht gefährden, werden die internen Signallaufzeiten üblicherweise sehr pessimistisch kalkuliert. Durch den so entstandenen zeitlichen Sicherheitsabstand wird die korrekte Funktionalität des Schaltkreises sichergestellt, allerdings auf Kosten der Performance. Alternativ kann die Zuverlässigkeit des Schaltkreises auch durch andere Techniken erhöht werden, wie zum Beispiel durch Null-Temperatur-Koeffizienten oder Approximate Computing. Wenngleich diese Techniken einen Großteil des üblichen zeitlichen Sicherheitsabstandes einsparen können, bergen sie dennoch weitere Konsequenzen und Kompromisse. Bleibende Herausforderungen bei der Skalierung von CMOS Technologien führen außerdem zu einem verstärkten Fokus auf vielversprechende Zukunftstechnologien. Ein Beispiel dafür ist der Negative Capacitance Field-Effect Transistor (NCFET), der eine beachtenswerte Leistungssteigerung gegenüber herkömmlichen FinFET Transistoren aufweist und diese in Zukunft ersetzen könnte. Des Weiteren setzen Entwickler von Schaltkreisen vermehrt auf komplexe, parallele Strukturen statt auf höhere Taktfrequenzen. Diese komplexen Modelle benötigen moderne Power-Management Techniken in allen Aspekten des Designs. Mit dem Auftreten von neuartigen Transistortechnologien (wie zum Beispiel NCFET) müssen diese Power-Management Techniken neu bewertet werden, da sich Abhängigkeiten und Verhältnismäßigkeiten ändern. Diese Arbeit präsentiert neue Herangehensweisen, sowohl zur Analyse als auch zur Modellierung der Zuverlässigkeit von Schaltkreisen, um zuvor genannte Herausforderungen auf mehreren Designebenen anzugehen. Diese Herangehensweisen unterteilen sich in konventionelle Techniken ((a), (b), (c) und (d)) und unkonventionelle Techniken ((e) und (f)), wie folgt: $\textbf{(a)}$ Analyse von Leistungszunahmen in Zusammenhang mit der Maximierung von Leistungseffizienz beim Betrieb nahe der Transistor Schwellspannung, insbesondere am optimalen Leistungspunkt. Das genaue Ermitteln eines solchen optimalen Leistungspunkts ist eine besondere Herausforderung bei Multicore Designs, da dieser sich mit den jeweiligen Optimierungszielsetzungen und der Arbeitsbelastung verschiebt. $\textbf{(b)}$ Aufzeigen versteckter Interdependenzen zwischen Alterungseffekten bei Transistoren und Schwankungen in der Versorgungsspannung durch „IR-drops“. Eine neuartige Technik wird vorgestellt, die sowohl Über- als auch Unterschätzungen bei der Ermittlung des zeitlichen Sicherheitsabstands vermeidet und folglich den kleinsten, dennoch ausreichenden Sicherheitsabstand ermittelt. $\textbf{(c)}$ Eindämmung von Alterungseffekten bei Transistoren durch „Graceful Approximation“, eine Technik zur Erhöhung der Taktfrequenz bei Bedarf. Der durch Alterungseffekte bedingte zeitlich Sicherheitsabstand wird durch Approximate Computing Techniken ersetzt. Des Weiteren wird Quantisierung verwendet um ausreichend Genauigkeit bei den Berechnungen zu gewährleisten. $\textbf{(d)}$ Eindämmung von temperaturabhängigen Verschlechterungen der Signallaufzeit durch den Betrieb nahe des Null-Temperatur Koeffizienten (N-ZTC). Der Betrieb bei N-ZTC minimiert temperaturbedingte Abweichungen der Performance und der Leistungsaufnahme. Qualitative und quantitative Vergleiche gegenüber dem traditionellen zeitlichen Sicherheitsabstand werden präsentiert. $\textbf{(e)}$ Modellierung von Power-Management Techniken für NCFET-basierte Prozessoren. Die NCFET Technologie hat einzigartige Eigenschaften, durch die herkömmliche Verfahren zur Spannungs- und Frequenzskalierungen zur Laufzeit (DVS/DVFS) suboptimale Ergebnisse erzielen. Dies erfordert NCFET-spezifische Power-Management Techniken, die in dieser Arbeit vorgestellt werden. $\textbf{(f)}$ Vorstellung eines neuartigen heterogenen Multicore Designs in NCFET Technologie. Das Design beinhaltet identische Kerne; Heterogenität entsteht durch die Anwendung der individuellen, optimalen Konfiguration der Kerne. Amdahls Gesetz wird erweitert, um neue system- und anwendungsspezifische Parameter abzudecken und die Vorzüge des neuen Designs aufzuzeigen. Die Auswertungen der vorgestellten Techniken werden mithilfe von Implementierungen und Simulationen auf Schaltkreisebene (gate-level) durchgeführt. Des Weiteren werden Simulatoren auf Systemebene (system-level) verwendet, um Multicore Designs zu implementieren und zu simulieren. Zur Validierung und Bewertung der Effektivität gegenüber dem Stand der Technik werden analytische, gate-level und system-level Simulationen herangezogen, die sowohl synthetische als auch reale Anwendungen betrachten