A Construction Kit for Efficient Low Power Neural Network Accelerator Designs

Implementing embedded neural network processing at the edge requires efficient hardware acceleration that couples high computational performance with low power consumption. Driven by the rapid evolution of network architectures and their algorithmic features, accelerator designs are constantly updated and improved. To evaluate and compare hardware design choices, designers can refer to a myriad of accelerator implementations in the literature. Surveys provide an overview of these works but are often limited to system-level and benchmark-specific performance metrics, making it difficult to quantitatively compare the individual effect of each utilized optimization technique. This complicates the evaluation of optimizations for new accelerator designs, slowing-down the research progress. This work provides a survey of neural network accelerator optimization approaches that have been used in recent works and reports their individual effects on edge processing performance. It presents the list of optimizations and their quantitative effects as a construction kit, allowing to assess the design choices for each building block separately. Reported optimizations range from up to 10'000x memory savings to 33x energy reductions, providing chip designers an overview of design choices for implementing efficient low power neural network accelerators

High-Performance Energy-Efficient and Reliable Design of Spin-Transfer Torque Magnetic Memory

In this dissertation new computing paradigms, architectures and design philosophy are proposed and evaluated for adopting the STT-MRAM technology as highly reliable, energy efficient and fast memory. For this purpose, a novel cross-layer framework from the cell-level all the way up to the system- and application-level has been developed. In these framework, the reliability issues are modeled accurately with appropriate fault models at different abstraction levels in order to analyze the overall failure rates of the entire memory and its Mean Time To Failure (MTTF) along with considering the temperature and process variation effects. Design-time, compile-time and run-time solutions have been provided to address the challenges associated with STT-MRAM. The effectiveness of the proposed solutions is demonstrated in extensive experiments that show significant improvements in comparison to state-of-the-art solutions, i.e. lower-power, higher-performance and more reliable STT-MRAM design

Reliable Low-Power High Performance Spintronic Memories

Moores Gesetz folgend, ist es der Chipindustrie in den letzten fünf Jahrzehnten gelungen, ein explosionsartiges Wachstum zu erreichen. Dies hatte ebenso einen exponentiellen Anstieg der Nachfrage von Speicherkomponenten zur Folge, was wiederum zu speicherlastigen Chips in den heutigen Computersystemen führt. Allerdings stellen traditionelle on-Chip Speichertech- nologien wie Static Random Access Memories (SRAMs), Dynamic Random Access Memories (DRAMs) und Flip-Flops eine Herausforderung in Bezug auf Skalierbarkeit, Verlustleistung und Zuverlässigkeit dar. Eben jene Herausforderungen und die überwältigende Nachfrage nach höherer Performanz und Integrationsdichte des on-Chip Speichers motivieren Forscher, nach neuen nichtflüchtigen Speichertechnologien zu suchen. Aufkommende spintronische Spe- ichertechnologien wie Spin Orbit Torque (SOT) und Spin Transfer Torque (STT) erhielten in den letzten Jahren eine hohe Aufmerksamkeit, da sie eine Reihe an Vorteilen bieten. Dazu gehören Nichtflüchtigkeit, Skalierbarkeit, hohe Beständigkeit, CMOS Kompatibilität und Unan- fälligkeit gegenüber Soft-Errors. In der Spintronik repräsentiert der Spin eines Elektrons dessen Information. Das Datum wird durch die Höhe des Widerstandes gespeichert, welche sich durch das Anlegen eines polarisierten Stroms an das Speichermedium verändern lässt. Das Prob- lem der statischen Leistung gehen die Speichergeräte sowohl durch deren verlustleistungsfreie Eigenschaft, als auch durch ihr Standard- Aus/Sofort-Ein Verhalten an. Nichtsdestotrotz sind noch andere Probleme, wie die hohe Zugriffslatenz und die Energieaufnahme zu lösen, bevor sie eine verbreitete Anwendung finden können. Um diesen Problemen gerecht zu werden, sind neue Computerparadigmen, -architekturen und -entwurfsphilosophien notwendig. Die hohe Zugriffslatenz der Spintroniktechnologie ist auf eine vergleichsweise lange Schalt- dauer zurückzuführen, welche die von konventionellem SRAM übersteigt. Des Weiteren ist auf Grund des stochastischen Schaltvorgangs der Speicherzelle und des Einflusses der Prozessvari- ation ein nicht zu vernachlässigender Zeitraum dafür erforderlich. In diesem Zeitraum wird ein konstanter Schreibstrom durch die Bitzelle geleitet, um den Schaltvorgang zu gewährleisten. Dieser Vorgang verursacht eine hohe Energieaufnahme. Für die Leseoperation wird gleicher- maßen ein beachtliches Zeitfenster benötigt, ebenfalls bedingt durch den Einfluss der Prozess- variation. Dem gegenüber stehen diverse Zuverlässigkeitsprobleme. Dazu gehören unter An- derem die Leseintereferenz und andere Degenerationspobleme, wie das des Time Dependent Di- electric Breakdowns (TDDB). Diese Zuverlässigkeitsprobleme sind wiederum auf die benötigten längeren Schaltzeiten zurückzuführen, welche in der Folge auch einen über längere Zeit an- liegenden Lese- bzw. Schreibstrom implizieren. Es ist daher notwendig, sowohl die Energie, als auch die Latenz zur Steigerung der Zuverlässigkeit zu reduzieren, um daraus einen potenziellen Kandidaten für ein on-Chip Speichersystem zu machen. In dieser Dissertation werden wir Entwurfsstrategien vorstellen, welche das Ziel verfolgen, die Herausforderungen des Cache-, Register- und Flip-Flop-Entwurfs anzugehen. Dies erre- ichen wir unter Zuhilfenahme eines Cross-Layer Ansatzes. Für Caches entwickelten wir ver- schiedene Ansätze auf Schaltkreisebene, welche sowohl auf der Speicherarchitekturebene, als auch auf der Systemebene in Bezug auf Energieaufnahme, Performanzsteigerung und Zuver- lässigkeitverbesserung evaluiert werden. Wir entwickeln eine Selbstabschalttechnik, sowohl für die Lese-, als auch die Schreiboperation von Caches. Diese ist in der Lage, den Abschluss der entsprechenden Operation dynamisch zu ermitteln. Nachdem der Abschluss erkannt wurde, wird die Lese- bzw. Schreiboperation sofort gestoppt, um Energie zu sparen. Zusätzlich limitiert die Selbstabschalttechnik die Dauer des Stromflusses durch die Speicherzelle, was wiederum das Auftreten von TDDB und Leseinterferenz bei Schreib- bzw. Leseoperationen re- duziert. Zur Verbesserung der Schreiblatenz heben wir den Schreibstrom an der Bitzelle an, um den magnetischen Schaltprozess zu beschleunigen. Um registerbankspezifische Anforderungen zu berücksichtigen, haben wir zusätzlich eine Multiport-Speicherarchitektur entworfen, welche eine einzigartige Eigenschaft der SOT-Zelle ausnutzt, um simultan Lese- und Schreiboperatio- nen auszuführen. Es ist daher möglich Lese/Schreib- Konfilkte auf Bitzellen-Ebene zu lösen, was sich wiederum in einer sehr viel einfacheren Multiport- Registerbankarchitektur nieder- schlägt. Zusätzlich zu den Speicheransätzen haben wir ebenfalls zwei Flip-Flop-Architekturen vorgestellt. Die erste ist eine nichtflüchtige non-Shadow Flip-Flop-Architektur, welche die Speicherzelle als aktive Komponente nutzt. Dies ermöglicht das sofortige An- und Ausschalten der Versorgungss- pannung und ist daher besonders gut für aggressives Powergating geeignet. Alles in Allem zeigt der vorgestellte Flip-Flop-Entwurf eine ähnliche Timing-Charakteristik wie die konventioneller CMOS Flip-Flops auf. Jedoch erlaubt er zur selben Zeit eine signifikante Reduktion der statis- chen Leistungsaufnahme im Vergleich zu nichtflüchtigen Shadow- Flip-Flops. Die zweite ist eine fehlertolerante Flip-Flop-Architektur, welche sich unanfällig gegenüber diversen Defekten und Fehlern verhält. Die Leistungsfähigkeit aller vorgestellten Techniken wird durch ausführliche Simulationen auf Schaltkreisebene verdeutlicht, welche weiter durch detaillierte Evaluationen auf Systemebene untermauert werden. Im Allgemeinen konnten wir verschiedene Techniken en- twickeln, die erhebliche Verbesserungen in Bezug auf Performanz, Energie und Zuverlässigkeit von spintronischen on-Chip Speichern, wie Caches, Register und Flip-Flops erreichen

Embedding Logic and Non-volatile Devices in CMOS Digital Circuits for Improving Energy Efficiency

abstract: Static CMOS logic has remained the dominant design style of digital systems for more than four decades due to its robustness and near zero standby current. Static CMOS logic circuits consist of a network of combinational logic cells and clocked sequential elements, such as latches and flip-flops that are used for sequencing computations over time. The majority of the digital design techniques to reduce power, area, and leakage over the past four decades have focused almost entirely on optimizing the combinational logic. This work explores alternate architectures for the flip-flops for improving the overall circuit performance, power and area. It consists of three main sections. First, is the design of a multi-input configurable flip-flop structure with embedded logic. A conventional D-type flip-flop may be viewed as realizing an identity function, in which the output is simply the value of the input sampled at the clock edge. In contrast, the proposed multi-input flip-flop, named PNAND, can be configured to realize one of a family of Boolean functions called threshold functions. In essence, the PNAND is a circuit implementation of the well-known binary perceptron. Unlike other reconfigurable circuits, a PNAND can be configured by simply changing the assignment of signals to its inputs. Using a standard cell library of such gates, a technology mapping algorithm can be applied to transform a given netlist into one with an optimal mixture of conventional logic gates and threshold gates. This approach was used to fabricate a 32-bit Wallace Tree multiplier and a 32-bit booth multiplier in 65nm LP technology. Simulation and chip measurements show more than 30% improvement in dynamic power and more than 20% reduction in core area. The functional yield of the PNAND reduces with geometry and voltage scaling. The second part of this research investigates the use of two mechanisms to improve the robustness of the PNAND circuit architecture. One is the use of forward and reverse body biases to change the device threshold and the other is the use of RRAM devices for low voltage operation. The third part of this research focused on the design of flip-flops with non-volatile storage. Spin-transfer torque magnetic tunnel junctions (STT-MTJ) are integrated with both conventional D-flipflop and the PNAND circuits to implement non-volatile logic (NVL). These non-volatile storage enhanced flip-flops are able to save the state of system locally when a power interruption occurs. However, manufacturing variations in the STT-MTJs and in the CMOS transistors significantly reduce the yield, leading to an overly pessimistic design and consequently, higher energy consumption. A detailed analysis of the design trade-offs in the driver circuitry for performing backup and restore, and a novel method to design the energy optimal driver for a given yield is presented. Efficient designs of two nonvolatile flip-flop (NVFF) circuits are presented, in which the backup time is determined on a per-chip basis, resulting in minimizing the energy wastage and satisfying the yield constraint. To achieve a yield of 98%, the conventional approach would have to expend nearly 5X more energy than the minimum required, whereas the proposed tunable approach expends only 26% more energy than the minimum. A non-volatile threshold gate architecture NV-TLFF are designed with the same backup and restore circuitry in 65nm technology. The embedded logic in NV-TLFF compensates performance overhead of NVL. This leads to the possibility of zero-overhead non-volatile datapath circuits. An 8-bit multiply-and- accumulate (MAC) unit is designed to demonstrate the performance benefits of the proposed architecture. Based on the results of HSPICE simulations, the MAC circuit with the proposed NV-TLFF cells is shown to consume at least 20% less power and area as compared to the circuit designed with conventional DFFs, without sacrificing any performance.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

Low Power Memory/Memristor Devices and Systems

This reprint focusses on achieving low-power computation using memristive devices. The topic was designed as a convenient reference point: it contains a mix of techniques starting from the fundamental manufacturing of memristive devices all the way to applications such as physically unclonable functions, and also covers perspectives on, e.g., in-memory computing, which is inextricably linked with emerging memory devices such as memristors. Finally, the reprint contains a few articles representing how other communities (from typical CMOS design to photonics) are fighting on their own fronts in the quest towards low-power computation, as a comparison with the memristor literature. We hope that readers will enjoy discovering the articles within

Bit-Flip Aware Data Structures for Phase Change Memory

Big, non-volatile, byte-addressable, low-cost, and fast non-volatile memories like Phase Change Memory are appearing in the marketplace. They have the capability to unify both memory and storage and allow us to rethink the present memory hierarchy. An important draw-back to Phase Change Memory is limited write-endurance. In addition, Phase Change Memory shares with other Non-Volatile Random Access Memories an asym- metry in the energy costs of writes and reads. Best use of Non-Volatile Random Access Memories limits the number of times a Non-Volatile Random Access Memory cell changes contents, called a bit-flip. While the future of main memory is still unknown, we should already start to create data structures for them in order to shape the future era. This thesis investigates the creation of bit-flip aware data structures.The thesis first considers general ways in which a data structure can save bit- flips by smart overwrites and by using the exclusive-or of pointers. It then shows how a simple content dependent encoding can reduce bit-flips for web corpora. It then shows how to build hash based dictionary structures for Linear Hashing and Spiral Storage. Finally, the thesis presents Gray counters, close to bit-flip optimal counters that even enable age- based wear leveling with counters managed by the Non-Volatile Random Access Memories themselves instead of by the Operating Systems

Heterogeneous Reconfigurable Fabrics for In-circuit Training and Evaluation of Neuromorphic Architectures

A heterogeneous device technology reconfigurable logic fabric is proposed which leverages the cooperating advantages of distinct magnetic random access memory (MRAM)-based look-up tables (LUTs) to realize sequential logic circuits, along with conventional SRAM-based LUTs to realize combinational logic paths. The resulting Hybrid Spin/Charge FPGA (HSC-FPGA) using magnetic tunnel junction (MTJ) devices within this topology demonstrates commensurate reductions in area and power consumption over fabrics having LUTs constructed with either individual technology alone. Herein, a hierarchical top-down design approach is used to develop the HSCFPGA starting from the configurable logic block (CLB) and slice structures down to LUT circuits and the corresponding device fabrication paradigms. This facilitates a novel architectural approach to reduce leakage energy, minimize communication occurrence and energy cost by eliminating unnecessary data transfer, and support auto-tuning for resilience. Furthermore, HSC-FPGA enables new advantages of technology co-design which trades off alternative mappings between emerging devices and transistors at runtime by allowing dynamic remapping to adaptively leverage the intrinsic computing features of each device technology. HSC-FPGA offers a platform for fine-grained Logic-In-Memory architectures and runtime adaptive hardware. An orthogonal dimension of fabric heterogeneity is also non-determinism enabled by either low-voltage CMOS or probabilistic emerging devices. It can be realized using probabilistic devices within a reconfigurable network to blend deterministic and probabilistic computational models. Herein, consider the probabilistic spin logic p-bit device as a fabric element comprising a crossbar-structured weighted array. The Programmability of the resistive network interconnecting p-bit devices can be achieved by modifying the resistive states of the array\u27s weighted connections. Thus, the programmable weighted array forms a CLB-scale macro co-processing element with bitstream programmability. This allows field programmability for a wide range of classification problems and recognition tasks to allow fluid mappings of probabilistic and deterministic computing approaches. In particular, a Deep Belief Network (DBN) is implemented in the field using recurrent layers of co-processing elements to form an n x m1 x m2 x ::: x mi weighted array as a configurable hardware circuit with an n-input layer followed by i ≥ 1 hidden layers. As neuromorphic architectures using post-CMOS devices increase in capability and network size, the utility and benefits of reconfigurable fabrics of neuromorphic modules can be anticipated to continue to accelerate

Cross-Layer Pathfinding for Off-Chip Interconnects

Off-chip interconnects for integrated circuits (ICs) today induce a diverse design space, spanning many different applications that require transmission of data at various bandwidths, latencies and link lengths. Off-chip interconnect design solutions are also variously sensitive to system performance, power and cost metrics, while also having a strong impact on these metrics. The costs associated with off-chip interconnects include die area, package (PKG) and printed circuit board (PCB) area, technology and bill of materials (BOM). Choices made regarding off-chip interconnects are fundamental to product definition, architecture, design implementation and technology enablement. Given their cross-layer impact, it is imperative that a cross-layer approach be employed to architect and analyze off-chip interconnects up front, so that a top-down design flow can comprehend the cross-layer impacts and correctly assess the system performance, power and cost tradeoffs for off-chip interconnects. Chip architects are not exposed to all the tradeoffs at the physical and circuit implementation or technology layers, and often lack the tools to accurately assess off-chip interconnects. Furthermore, the collaterals needed for a detailed analysis are often lacking when the chip is architected; these include circuit design and layout, PKG and PCB layout, and physical floorplan and implementation. To address the need for a framework that enables architects to assess the system-level impact of off-chip interconnects, this thesis presents power-area-timing (PAT) models for off-chip interconnects, optimization and planning tools with the appropriate abstraction using these PAT models, and die/PKG/PCB co-design methods that help expose the off-chip interconnect cross-layer metrics to the die/PKG/PCB design flows. Together, these models, tools and methods enable cross-layer optimization that allows for a top-down definition and exploration of the design space and helps converge on the correct off-chip interconnect implementation and technology choice. The tools presented cover off-chip memory interfaces for mobile and server products, silicon photonic interfaces, 2.5D silicon interposers and 3D through-silicon vias (TSVs). The goal of the cross-layer framework is to assess the key metrics of the interconnect (such as timing, latency, active/idle/sleep power, and area/cost) at an appropriate level of abstraction by being able to do this across layers of the design flow. In additional to signal interconnect, this thesis also explores the need for such cross-layer pathfinding for power distribution networks (PDN), where the system-on-chip (SoC) floorplan and pinmap must be optimized before the collateral layouts for PDN analysis are ready. Altogether, the developed cross-layer pathfinding methodology for off-chip interconnects enables more rapid and thorough exploration of a vast design space of off-chip parallel and serial links, inter-die and inter-chiplet links and silicon photonics. Such exploration will pave the way for off-chip interconnect technology enablement that is optimized for system needs. The basis of the framework can be extended to cover other interconnect technology as well, since it fundamentally relates to system-level metrics that are common to all off-chip interconnects