Programmable Superconducting Optoelectronic Single-Photon Synapses with Integrated Multi-State Memory

The co-location of memory and processing is a core principle of neuromorphic computing. A local memory device for synaptic weight storage has long been recognized as an enabling element for large-scale, high-performance neuromorphic hardware. In this work, we demonstrate programmable superconducting synapses with integrated memories for use in superconducting optoelectronic neural systems. Superconducting nanowire single-photon detectors and Josephson junctions are combined into programmable synaptic circuits that exhibit single-photon sensitivity, memory cells with more than 400 internal states, leaky integration of input spike events, and 0.4 fJ programming energies (including cooling power). These results are attractive for implementing a variety of supervised and unsupervised learning algorithms and lay the foundation for a new hardware platform optimized for large-scale spiking network accelerators.Comment: 16 pages, 11 figure

Extremely Large Area (88 mm X 88 mm) Superconducting Integrated Circuit (ELASIC)

Superconducting integrated circuit (SIC) is a promising "beyond-CMOS" device technology enables speed-of-light, nearly lossless communications to advance cryogenic (4 K or lower) computing. However, the lack of large-area superconducting IC has hindered the development of scalable practical systems. Herein, we describe a novel approach to interconnect 16 high-resolution deep UV (DUV EX4, 248 nm lithography) full reticle circuits to fabricate an extremely large (88mm X 88 mm) area superconducting integrated circuit (ELASIC). The fabrication process starts by interconnecting four high-resolution DUV EX4 (22 mm X 22 mm) full reticles using a single large-field (44 mm X 44 mm) I-line (365 nm lithography) reticle, followed by I-line reticle stitching at the boundaries of 44 mm X 44 mm fields to fabricate the complete ELASIC field (88 mm X 88 mm). The ELASIC demonstrated a 2X-12X reduction in circuit features and maintained high-stitched line superconducting critical currents. We examined quantum flux parametron (QFP) circuits to demonstrate the viability of common active components used for data buffering and transmission. Considering that no stitching requirement for high-resolution EX4 DUV reticles is employed, the present fabrication process has the potential to advance the scaling of superconducting quantum devices

Defect-based testing of LTS digital circuits

A Defect-Based Test (DBT) methodology for Superconductor Electronics (SCE) is presented in this thesis, so that commercial production and efficient testing of systems can be implemented in this technology in the future. In the first chapter, the features and prospects for SCE have been presented. The motivation for this research and the outline of the thesis were also described in Chapter 1. It has been shown that high-end applications such as Software-Defined Radio (SDR) and petaflop computers which are extremely difficult to implement in top-of-the-art semiconductor technologies can be realised using SCE. But, a systematic structural test methodology had yet to be developed for SCE and has been addressed in this thesis. A detailed introduction to Rapid Single-Flux Quantum (RSFQ) circuits was presented in Chapter 2. A Josephson Junction (JJ) was described with associated theory behind its operation. The JJ model used in the simulator used in this research work was also presented. RSFQ logic with logic protocols as well as the design and implementation of an example D-type flip-flop (DFF) was also introduced. Finally, advantages and disadvantages of RSFQ circuits have been discussed with focus on the latest developments in the field. Various techniques for testing RSFQ circuits were discussed in Chapter 3. A Process Defect Monitor (PDM) approach was presented for fabrication process analysis. The presented defect-monitor structures were used to gather measurement data, to find the probability of the occurrence of defects in the process which forms the first step for Inductive Fault Analysis (IFA). Results from measurements on these structures were used to create a database for defects. This information can be used as input for performing IFA. "Defect-sprinkling" over a fault-free circuit can be carried out according to the measured defect densities over various layers. After layout extraction and extensive fault simulation, the resulting information will indicate realistic faults. In addition, possible Design-for-Testability (DfT) schemes for monitoring Single-Flux Quantum (SFQ) pulses within an RSFQ circuit has also been discussed in Chapter 3. The requirement for a DfT scheme is inevitable for RSFQ circuits because of their very high frequency of operation and very low operating temperature. It was demonstrated how SFQ pulses can be monitored at an internal node of an SCE circuit, introducing observability using Test-Point Insertion (TPI). Various techniques were discussed for the introduction of DfT and to avoid the delay introduced by the DfT structure if it is required. The available features in the proposed design for customising the detector make it attractive for a detailed DBT of RSFQ circuits. The control of internal nodes has also been illustrated using TPI. The test structures that were designed and implemented to determine the occurrence of defects in the processes can also be used to locate the position for the insertion of the above mentioned DfT structures

Cryogenic Neuromorphic Hardware

The revolution in artificial intelligence (AI) brings up an enormous storage and data processing requirement. Large power consumption and hardware overhead have become the main challenges for building next-generation AI hardware. To mitigate this, Neuromorphic computing has drawn immense attention due to its excellent capability for data processing with very low power consumption. While relentless research has been underway for years to minimize the power consumption in neuromorphic hardware, we are still a long way off from reaching the energy efficiency of the human brain. Furthermore, design complexity and process variation hinder the large-scale implementation of current neuromorphic platforms. Recently, the concept of implementing neuromorphic computing systems in cryogenic temperature has garnered intense interest thanks to their excellent speed and power metric. Several cryogenic devices can be engineered to work as neuromorphic primitives with ultra-low demand for power. Here we comprehensively review the cryogenic neuromorphic hardware. We classify the existing cryogenic neuromorphic hardware into several hierarchical categories and sketch a comparative analysis based on key performance metrics. Our analysis concisely describes the operation of the associated circuit topology and outlines the advantages and challenges encountered by the state-of-the-art technology platforms. Finally, we provide insights to circumvent these challenges for the future progression of research

Design and Performance of Scalable High-Performance Programmable Routers - Doctoral Dissertation, August 2002

The flexibility to adapt to new services and protocols without changes in the underlying hardware is and will increasingly be a key requirement for advanced networks. Introducing a processing component into the data path of routers and implementing packet processing in software provides this ability. In such a programmable router, a powerful processing infrastructure is necessary to achieve to level of performance that is comparable to custom silicon-based routers and to demonstrate the feasibility of this approach. This work aims at the general design of such programmable routers and, specifically, at the design and performance analysis of the processing subsystem. The necessity of programmable routers is motivated, and a router design is proposed. Based on the design, a general performance model is developed and quantitatively evaluated using a new network processor benchmark. Operational challenges, like scheduling of packets to processing engines, are addressed, and novel algorithms are presented. The results of this work give qualitative and quantitative insights into this new domain that combines issues from networking, computer architecture, and system design

A physical design and layout versus schematic framework for superconducting electronics

Thesis (MEng)--Stellenbosch University, 2021.ENGLISH ABSTRACT: This dissertation presents a PCell synthesis and layout vs schematic extraction framework, named SPiRA. This framework allows the user to create a PCell-based layout, creating parameters to adjust polygon positions, sizes and presence. All polygons are connected to a specific layer in the fabrication process by means of a suggested Rule Deck Database containing process information. During the creation of a PCell, an undirected graph or node graph, showing all the interconnections present in the layout, is generated. Furthermore a SPICE-like netlist (a list containing information about the elements contained in the circuit and how element ports are connected) is generated by parsing this node network allowing the user to see if the extracted elements match up with the initial design. SPiRA is a Python framework, allowing for dynamicity in the creation of the layout, giving the user feedback along the way. Design rule checking (DRC) is implemented by means of different parameter types, allowing the user to get feedback during the creation of the layout about broken design rules. Further, full post-layout DRC is implemented by means of the KLayout DRC engine. As a futher extension of the framework, SPiRA-tools is introduced. This collection of tools allows the user to modify a layout, to prepare it for simulation by means of the InductEx simulation engine. SPiRA-tools also brings to life a schematic generator, that reads in a netlist file to produce a Standard Vector Graphics schematic, allowing the user to visually compare initial design, with the newly generated output allowing for true Layout vs Schematic comparison.AFRIKAANSE OPSOMMING: Die dissertasie bied ’n geparametriseerde sell (PCell) sintese raamwerk met LVS (Layout vs Schematic) funksionaliteit ingebou, genaamd SPiRA. Hierdie raamwerk gee die gebruiker die funksionaliteit om ’n PCell te maak, wat verstelbaarheid aan die posisie, grote en teenwoordigheid van enige veelhoek in die stroombaan gee. Vervaardigingsprosesreëls en prosesdata word in ’n Reëldatabase (RDD) gestoor, om hergebruik te word deur stroombaanontwerpers gedurende die uitleg van ’n geparameteriseerde sel. ’n Ongerigte node grafiek/netwerk word gegenereer wanneer ’n gaparametriseerde sel geïnstansieer word. Hierdie grafiek dui al die interkonneksies van die gegewe stroombaan aan. Hierdie netwerk word dan verder reduseer om ’n geskikte netlist (soortgelyk aan SPICE) te produseer wat werk met die simulasiesagteware, InductEx. Hierdie netlist kan met die oorspronklike ontwerp vergelyk word om te bepaal of al die konneksies en grote van die stroombaanelemente ooreenstem. Aangesien SPiRA op die skriptaal, Python, gebaseer is, kan dinamiese terugvoer vir die gebruiker gegee word tydens seluitleg. Ontwerpreëlkontrole is in plek gestel deur middel van gespesialiseerde SPiRA parameters, wat die gebruiker inkennis stel wanneer ’n ontwerpreël gebreek word. Verder het SPiRA die funksionaliteit om volle selontwerpe te kan analiseer met behulp van KLayout se losstaande ontwerpreëlkontrole sagteware. SPiRA-tools is ’n ekstensie van SPiRA wat streef om ’n Standard Vector Graphic lêer te produseer, wat die visuele voorstelling van ’n gegewe netlist is. Hierdie visuele voorstelling van die stroombaan kan dan direk met die oorspronklike ontwerp vergelyk word, vir ware Layout vs Schematic vergelykbaarheid.Master

Experimental Study of Novel Materials and Module for Cryogenic (4K) Superconducting Multi-Chip Modules

The objectives of this proposal are to understand the science and technology of interfaces in the packaging of superconducting electronic (SCE) multichip modules (MCMs) at 4 K. The thermal management issue of the current SCE-MCMs was examined and the package assembly was optimized. A novel thermally conducting and electrically insulating nano-engineered polymer was developed for the thermal management of SCE-MCMs for 4 K cryogenic packaging. Finally, the nano-engineered polymer was integrated as underfill in a SCE-MCM and the thermal and electrical performance of SCE-MCM was demonstrated at 4 K. Niobium based superconducting electronics (SCE) are the fastest known digital logic which operate at 100GHz and greater. Nevertheless, the performance of the SCE device depends on the temperature of the SCE integrated circuits being maintained between 4.2 - 4.25 K. Additionally, as semiconductors are slowly approaching their performance limitations the SCE devices are viewed as a viable alternative for high end computing and commercial wireless applications. However, the successful implementation of SCE\u27s requires the demonstration of these devices in multichip module (MCM) architecture. Thus the stringent thermal constraint and the complex MCM architecture require an innovative method for thermal management which is addressed by the current research

Data-Driven Nonlinear Control Designs for Constrained Systems

Systems with nonlinear dynamics are theoretically constrained to the realm of nonlinear analysis and design, while explicit constraints are expressed as equalities or inequalities of state, input, and output vectors of differential equations. Few control designs exist for systems with such explicit constraints, and no generalized solution has been provided. This dissertation presents general techniques to design stabilizing controls for a specific class of nonlinear systems with constraints on input and output, and verifies that such designs are straightforward to implement in selected applications. Additionally, a closed-form technique for an open-loop problem with unsolvable dynamic equations is developed. Typical optimal control methods cannot be readily applied to nonlinear systems without heavy modification. However, by embedding a novel control framework based on barrier functions and feedback linearization, well-established optimal control techniques become applicable when constraints are imposed by the design in real-time. Applications in power systems and aircraft control often have safety, performance, and hardware restrictions that are combinations of input and output constraints, while cryogenic memory applications have design restrictions and unknown analytic solutions. Most applications fall into a broad class of systems known as passivity-short, in which certain properties are utilized to form a structural framework for system interconnection with existing general stabilizing control techniques. Previous theoretical contributions are extended to include constraints, which can be readily applied to the development of scalable system networks in practical systems, even in the presence of unknown dynamics. In cases such as these, model identification techniques are used to obtain estimated system models which are guaranteed to be at least passivity-short. With numerous analytic tools accessible, a data-driven nonlinear control design framework is developed using model identification resulting in passivity-short systems which handles input and output saturations. Simulations are presented that prove to effectively control and stabilize example practical systems

Energy efficient wireless sensor network protocols for monitoring and prognostics of large scale systems

In this work, energy-efficient protocols for wireless sensor networks (WSN) with applications to prognostics are investigated. Both analytical methods and verification are shown for the proposed methods via either hardware experiments or simulation. This work is presented in five papers. Energy-efficiency methods for WSN include distributed algorithms for i) optimal routing, ii) adaptive scheduling, iii) adaptive transmission power and data-rate control --Abstract, page iv