The future of computing beyond Moore's Law.

Moore's Law is a techno-economic model that has enabled the information technology industry to double the performance and functionality of digital electronics roughly every 2 years within a fixed cost, power and area. Advances in silicon lithography have enabled this exponential miniaturization of electronics, but, as transistors reach atomic scale and fabrication costs continue to rise, the classical technological driver that has underpinned Moore's Law for 50 years is failing and is anticipated to flatten by 2025. This article provides an updated view of what a post-exascale system will look like and the challenges ahead, based on our most recent understanding of technology roadmaps. It also discusses the tapering of historical improvements, and how it affects options available to continue scaling of successors to the first exascale machine. Lastly, this article covers the many different opportunities and strategies available to continue computing performance improvements in the absence of historical technology drivers. This article is part of a discussion meeting issue 'Numerical algorithms for high-performance computational science'

Processor Microarchitecture for Implementation of Ephemeral State Processing within Network Routers

The evolving concept of Ephemeral State Processing (ESP) is overviewed. ESP allows development of new scalable end-to-end network user services. An evolving macro-level language is being developed to support ESP at the network node level. Three approaches for implementing ESP services at network routers can be considered. One approach is to use the existing processing capability within commercially available network routers. Another approach is to add a small scale existing ASIC based general-purpose processor to an existing network router. This thesis research concentrates on a third approach of developing a special-purpose programmable Ephemeral State Processor (ESPR) Instruction Set Architecture (ISA) and implementing microarchitecture for deployment within each ESP-capable node to implement ESP service within that node. A unique architectural characteristic of the ESPR is its scalable and temporal Ephemeral State Store (ESS) associative memory, required by the ESP service for storage/retrieval of bounded (short) lifetime ephemeral (tag, value) pairs of application data. The ESPR will be implemented to Programmable Logic Device (PLD) technology within a network node. This offers advantages of reconfigurability, in-field upgrade capability and supports the evolving growth of ESP services. Correct functional and performance operation of the presented ESPR microarchitecture is validated via Hardware Description Language (HDL) post-implementation (virtual prototype) simulation testing. Suggestions of future research related to improving the performance of the ESPR rnicroarchitecture and experimental deployment of ESP are discussed

Virtualized Reconfigurable Resources and Their Secured Provision in an Untrusted Cloud Environment

The cloud computing business grows year after year. To keep up with increasing demand and to offer more services, data center providers are always searching for novel architectures. One of them are FPGAs, reconfigurable hardware with high compute power and energy efficiency. But some clients cannot make use of the remote processing capabilities. Not every involved party is trustworthy and the complex management software has potential security flaws. Hence, clients’ sensitive data or algorithms cannot be sufficiently protected. In this thesis state-of-the-art hardware, cloud and security concepts are analyzed and com- bined. On one side are reconfigurable virtual FPGAs. They are a flexible resource and fulfill the cloud characteristics at the price of security. But on the other side is a strong requirement for said security. To provide it, an immutable controller is embedded enabling a direct, confidential and secure transfer of clients’ configurations. This establishes a trustworthy compute space inside an untrusted cloud environment. Clients can securely transfer their sensitive data and algorithms without involving vulnerable software or a data center provider. This concept is implemented as a prototype. Based on it, necessary changes to current FPGAs are analyzed. To fully enable reconfigurable yet secure hardware in the cloud, a new hybrid architecture is required.Das Geschäft mit dem Cloud Computing wächst Jahr für Jahr. Um mit der steigenden Nachfrage mitzuhalten und neue Angebote zu bieten, sind Betreiber von Rechenzentren immer auf der Suche nach neuen Architekturen. Eine davon sind FPGAs, rekonfigurierbare Hardware mit hoher Rechenleistung und Energieeffizienz. Aber manche Kunden können die ausgelagerten Rechenkapazitäten nicht nutzen. Nicht alle Beteiligten sind vertrauenswürdig und die komplexe Verwaltungssoftware ist anfällig für Sicherheitslücken. Daher können die sensiblen Daten dieser Kunden nicht ausreichend geschützt werden. In dieser Arbeit werden modernste Hardware, Cloud und Sicherheitskonzept analysiert und kombiniert. Auf der einen Seite sind virtuelle FPGAs. Sie sind eine flexible Ressource und haben Cloud Charakteristiken zum Preis der Sicherheit. Aber auf der anderen Seite steht ein hohes Sicherheitsbedürfnis. Um dieses zu bieten ist ein unveränderlicher Controller eingebettet und ermöglicht eine direkte, vertrauliche und sichere Übertragung der Konfigurationen der Kunden. Das etabliert eine vertrauenswürdige Rechenumgebung in einer nicht vertrauenswürdigen Cloud Umgebung. Kunden können sicher ihre sensiblen Daten und Algorithmen übertragen ohne verwundbare Software zu nutzen oder den Betreiber des Rechenzentrums einzubeziehen. Dieses Konzept ist als Prototyp implementiert. Darauf basierend werden nötige Änderungen von modernen FPGAs analysiert. Um in vollem Umfang eine rekonfigurierbare aber dennoch sichere Hardware in der Cloud zu ermöglichen, wird eine neue hybride Architektur benötigt

Analog Signal Buffering and Reconstruction

Wireless sensor networks (WSNs) are capable of a myriad of tasks, from monitoring critical infrastructure such as bridges to monitoring a person\u27s vital signs in biomedical applications. However, their deployment is impractical for many applications due to their limited power budget. Sleep states are one method used to conserve power in resource-constrained systems, but they necessitate a wake-up circuit for detecting unpredictable events. In conventional wake-up-based systems, all information preceding a wake-up event will be forfeited. To avoid this data loss, it is necessary to include a buffer that can record prelude information without sacrificing the power savings garnered by the active use of sleep states.;Unfortunately, traditional memory buffer systems utilize digital electronics which are costly in terms of power. Instead of operating in the target signal\u27s native analog environment, a digital buffer must first expend a great deal of energy to convert the signal into a digital signal. This issue is further compounded by the use of traditional Nyquist sampling which does not adapt to the characteristics of a dynamically changing signal. These characteristics reveal why a digital buffer is not an appropriate choice for a WSN or other resource-constrained system.;This thesis documents the development of an analog pre-processing block that buffers an incoming signal using a new method of sampling. This method requires sampling only local maxima and minima (both amplitude and time), effectively approximating the instantaneous Nyquist rate throughout a time-varying signal. The use of this sampling method along with ultra-low-power analog electronics enables the entire system to operate in the muW power levels. In addition to these power saving techniques, a reconfigurable architecture will be explored as infrastructure for this system. This reconfigurable architecture will also be leveraged to explore wake-up circuits that can be used in parallel with the buffer system

Distributed and Scalable Video Analysis Architecture for Human Activity Recognition Using Cloud Services

This thesis proposes an open-source, maintainable system for detecting human activity in large video datasets using scalable hardware architectures. The system is validated by detecting writing and typing activities that were collected as part of the Advancing Out of School Learning in Mathematics and Engineering (AOLME) project. The implementation of the system using Amazon Web Services (AWS) is shown to be both horizontally and vertically scalable. The software associated with the system was designed to be robust so as to facilitate reproducibility and extensibility for future research

Managing Event-Driven Applications in Heterogeneous Fog Infrastructures

The steady increase in digitalization propelled by the Internet of Things (IoT) has led to a deluge of generated data at unprecedented pace. Thereby, the promise to realize data-driven decision-making is a major innovation driver in a myriad of industries. Based on the widely used event processing paradigm, event-driven applications allow to analyze data in the form of event streams in order to extract relevant information in a timely manner. Most recently, graphical flow-based approaches in no-code event processing systems have been introduced to significantly lower technological entry barriers. This empowers non-technical citizen technologists to create event-driven applications comprised of multiple interconnected event-driven processing services. Still, today’s event-driven applications are focused on centralized cloud deployments that come with inevitable drawbacks, especially in the context of IoT scenarios that require fast results, are limited by the available bandwidth, or are bound by the regulations in terms of privacy and security. Despite recent advances in the area of fog computing which mitigate these shortcomings by extending the cloud and moving certain processing closer to the event source, these approaches are hardly established in existing systems. Inherent fog computing characteristics, especially the heterogeneity of resources alongside novel application management demands, particularly the aspects of geo-distribution and dynamic adaptation, pose challenges that are currently insufficiently addressed and hinder the transition to a next generation of no-code event processing systems. The contributions of this thesis enable citizen technologists to manage event-driven applications in heterogeneous fog infrastructures along the application life cycle. Therefore, an approach for a holistic application management is proposed which abstracts citizen technologists from underlying technicalities. This allows to evolve present event processing systems and advances the democratization of event-driven application management in fog computing. Individual contributions of this thesis are summarized as follows: 1. A model, manifested in a geo-distributed system architecture, to semantically describe characteristics specific to node resources, event-driven applications and their management to blend application-centric and infrastructure-centric realms. 2. Concepts for geo-distributed deployment and operation of event-driven applications alongside strategies for flexible event stream management. 3. A methodology to support the evolution of event-driven applications including methods to dynamically reconfigure, migrate and offload individual event-driven processing services at run-time. The contributions are introduced, applied and evaluated along two scenarios from the manufacturing and logistics domain