Design of an Adaptable Run-Time Reconfigurable Software-Defined Radio Processing Architecture

Processing power is a key technical challenge holding back the development of a high-performance software defined radio (SDR). Traditionally, SDR has utilized digital signal processors (DSPs), but increasingly complex algorithms, higher data rates, and multi-tasking needs have exceed the processing capabilities of modern DSPs. Reconfigurable computers, such as field-programmable gate arrays (FPGAs), are popular alternatives because of their performance gains over software for streaming data applications like SDR. However, FPGAs have not yet realized the ideal SDR because architectures have not fully utilized their partial reconfiguration (PR) capabilities to bring needed flexibility. A reconfigurable processor architecture is proposed that utilizes PR in reconfigurable computers to achieve a more sophisticated SDR. The proposed processor contains run-time swappable blocks whose parameters and interconnects are programmable. The architecture is analyzed for performance and flexibility and compared with available alternate technologies. For a sample QPSK algorithm, hardware performance gains of at least 44x are seen over modern desktop processors and DSPs while most of their flexibility and extensibility is maintained

Optimierung der Rechenleistung pro Fläche von Prozessorarchitekturen durch Rekonfiguration von Funktionseinheiten

Viele eingebettete Systeme, wie Smartphones, PDAs, MP3-Player und zahlreiche weitere, werden zur Miniaturisierung, Kostenreduktion und Steigerung der Robustheit zunehmend als System-on-a-Chip, also auf nur einem Stück Silizium, gefertigt. In solchen Systemen arbeiten sowohl Prozessoren und Speicher, wie auch mannigfaltige andere Peripherieeinheiten, welche spezialisierte Aufgaben des jeweiligen Einsatzgebietes des Systems übernehmen. Einige dieser Einheiten sind jedoch nicht durchgängig im Einsatz, wie beispielsweise ein GSM-Modulator bei Smartphones oder ein Hardware MPEG-Dekoder im PDA. Aufgrund der benötigten Flexibilität und des einfacheren Entwurfsprozesses wird es zunehmend populärer, Systems-on-a-Chip mit Field Programmable Gate Arrays (FPGAs), frei programmierbaren Logikbausteinen, zu realisieren. Aktuelle Bausteine erlauben dynamische partielle Rekonfiguration. Sie können also Teile ihrer Logik ersetzen, während andere weiter in Betrieb bleiben. Die Ressourcen nicht aktiver Einheiten des Systems können somit dynamisch für andere Zwecke benutzt werden. Diese Arbeit schlägt eine Prozessorarchitektur vor, deren Rechenleistung sich durch zeitlich variable Hinzunahme und Abgabe von zur Verfügung stehenden Ressourcen der programmierbaren Logik anpasst. Zusätzliche Ressourcen werden, um dies zu erreichen, durch zusätzliche Funktionseinheiten für den Prozessor belegt. Deren Einbindung in die Berechnungen wird durch parallel ausführbare, den Prinzipien des Explicitly Parallel Instruction Computings genügende Instruktionen erreicht. Werden die belegten Ressourcen des Prozessors an anderer Stelle wieder benötigt, werden schrittweise Funktionseinheiten abgetreten, bis ein Minimum an Rechenleistung des Prozessors erreicht ist. Durch diesen Ansatz werden die zeitweise ungenutzten Ressourcen des Prozessors sinnvoll verwendet. Zudem bietet die vorgeschlagene Architektur die Fähigkeit, sich selbst an die auszuführenden Berechnungen anzupassen und sie somit schneller auszuführen. Ziel dieser Arbeit ist es, eine solche Klasse neuer Prozessoren zu definieren, ihren möglichen Nutzen zu quantifizieren und ihre technische Umsetzbarkeit nachzuweisen. Die mögliche Beschleunigung durch eine solche Architektur wird durch simulative Zuordnung von Befehlen potentieller Traces von Programmen auf Funktionseinheiten ermittelt. Die technische Machbarkeit des Ansatzes wird durch prototypische Implementierungen der kritischen Elemente der Architektur, vor allem im Bereich der partiellen Rekonfiguration von FPGAs, gezeigt

Just-in-time Hardware generation for abstracted reconfigurable computing

This thesis addresses the use of reconfigurable hardware in computing platforms, in order to harness the performance benefits of dedicated hardware whilst maintaining the flexibility associated with software. Although the reconfigurable computing concept is not new, the low level nature of the supporting tools normally used, together with the consequent limited level of abstraction and resultant lack of backwards compatibility, has prevented the widespread adoption of this technology. In addition, bandwidth and architectural limitations, have seriously constrained the potential improvements in performance. A review of existing approaches and tools flows is conducted to highlight the current problems being faced in this field. The objective of the work presented in this thesis is to introduce a radically new approach to reconfigurable computing tool flows. The runtime based tool flow introduces complete abstraction between the application developer and the underlying hardware. This new technique eliminates the ease of use and backwards compatibility issues that have plagued the reconfigurable computing concept, and could pave the way for viable mainstream reconfigurable computing platforms. An easy to use, cycle accurate behavioural modelling system is also presented, which was used extensively during the early exploration of new concepts and architectures. Some performance improvements produced by the new reconfigurable computing tool flow, when applied to both a MIPS based embedded platform, and the Cray XDl, are also presented. These results are then analyzed and the hardware and software factors affecting the performance increases that were obtained are discussed, together with potential techniques that could be used to further increase the performance of the system. Lastly a heterogenous computing concept is proposed, in which, a computer system, containing multiple types of computational resource is envisaged, each having their own strengths and weaknesses (e.g. DSPs, CPUs, FPGAs). A revolutionary new method of fully exploiting the potential of such a system, whilst maintaining scalability, backwards compatibility, and ease of use is also presented

Coprocesadores dinámicamente reconfigurables en sistemas embebidos basados en FPGAs: Tesis doctoral

Tesis doctoral inédita leída en la Universidad Autónoma de Madrid. Escuela Politécnica Superior, Departamento de Ingeniería Informática. Fecha de lectura: 12-05-2006

A Reconfigurable Processor for Heterogeneous Multi-Core Architectures

A reconfigurable processor is a general-purpose processor coupled with an FPGA-like reconfigurable fabric. By deploying application-specific accelerators, performance for a wide range of applications can be improved with such a system. In this work concepts are designed for the use of reconfigurable processors in multi-tasking scenarios and as part of multi-core systems

Technological innovation, industry platforms or financialization? A comparative institutional perspective on Nokia, Apple, and Samsung

The puzzle of how Nokia lost the smartphone wars has intrigued recent scholarship. Despite Nokia’s dominant position in the mobile phone industry and its technological capabilities and reputation for strategic agility, it was completely wiped out from the market, only a few years after the launch of Apple’s iPhone. The article provides a comparative, historical and institutional account on the smartphone industry by focusing on three key players: Nokia, Apple, and Samsung. This perspective enriches earlier accounts that were overly focused on explaining Nokia’s decline by looking at internal organisational design and conflicts. We propose a two-pronged explanation focused on the reconfiguration of industry platforms and financialisation. The article suggests that single company histories could be enriched by integrating a comparative perspective that examines additional cases. We discuss opportunities for further research to understand how success or failure in technological innovation is embedded in a wider societal and institutional context

PROPOSED MIDDLEWARE SOLUTION FOR RESOURCE-CONSTRAINED DISTRIBUTED EMBEDDED NETWORKS

The explosion in processing power of embedded systems has enabled distributed embedded networks to perform more complicated tasks. Middleware are sets of encapsulations of common and network/operating system-specific functionality into generic, reusable frameworks to manage such distributed networks. This thesis will survey and categorize popular middleware implementations into three adapted layers: host-infrastructure, distribution, and common services. This thesis will then apply a quantitative approach to grading and proposing a single middleware solution from all layers for two target platforms: CubeSats and autonomous unmanned aerial vehicles (UAVs). CubeSats are 10x10x10cm nanosatellites that are popular university-level space missions, and impose power and volume constraints. Autonomous UAVs are similarly-popular hobbyist-level vehicles that exhibit similar power and volume constraints. The MAVLink middleware from the host-infrastructure layer is proposed as the middleware to manage the distributed embedded networks powering these platforms in future projects. Finally, this thesis presents a performance analysis on MAVLink managing the ARM Cortex-M 32-bit processors that power the target platforms

A hardware-software codesign framework for cellular computing

Until recently, the ever-increasing demand of computing power has been met on one hand by increasing the operating frequency of processors and on the other hand by designing architectures capable of exploiting parallelism at the instruction level through hardware mechanisms such as super-scalar execution. However, both these approaches seem to have reached a plateau, mainly due to issues related to design complexity and cost-effectiveness. To face the stabilization of performance of single-threaded processors, the current trend in processor design seems to favor a switch to coarser-grain parallelization, typically at the thread level. In other words, high computational power is achieved not only by a single, very fast and very complex processor, but through the parallel operation of several processors, each executing a different thread. Extrapolating this trend to take into account the vast amount of on-chip hardware resources that will be available in the next few decades (either through further shrinkage of silicon fabrication processes or by the introduction of molecular-scale devices), together with the predicted features of such devices (e.g., the impossibility of global synchronization or higher failure rates), it seems reasonable to foretell that current design techniques will not be able to cope with the requirements of next-generation electronic devices and that novel design tools and programming methods will have to be devised. A tempting source of inspiration to solve the problems implied by a massively parallel organization and inherently error-prone substrates is biology. In fact, living beings possess characteristics, such as robustness to damage and self-organization, which were shown in previous research as interesting to be implemented in hardware. For instance, it was possible to realize relatively simple systems, such as a self-repairing watch. Overall, these bio-inspired approaches seem very promising but their interest for a wider audience is problematic because their heavily hardware-oriented designs lack some of the flexibility achievable with a general purpose processor. In the context of this thesis, we will introduce a processor-grade processing element at the heart of a bio-inspired hardware system. This processor, based on a single-instruction, features some key properties that allow it to maintain the versatility required by the implementation of bio-inspired mechanisms and to realize general computation. We will also demonstrate that the flexibility of such a processor enables it to be evolved so it can be tailored to different types of applications. In the second half of this thesis, we will analyze how the implementation of a large number of these processors can be used on a hardware platform to explore various bio-inspired mechanisms. Based on an extensible platform of many FPGAs, configured as a networked structure of processors, the hardware part of this computing framework is backed by an open library of software components that provides primitives for efficient inter-processor communication and distributed computation. We will show that this dual software–hardware approach allows a very quick exploration of different ways to solve computational problems using bio-inspired techniques. In addition, we also show that the flexibility of our approach allows it to exploit replication as a solution to issues that concern standard embedded applications

Sophisticated Batteryless Sensing

Wireless embedded sensing systems have revolutionized scientific, industrial, and consumer applications. Sensors have become a fixture in our daily lives, as well as the scientific and industrial communities by allowing continuous monitoring of people, wildlife, plants, buildings, roads and highways, pipelines, and countless other objects. Recently a new vision for sensing has emerged---known as the Internet-of-Things (IoT)---where trillions of devices invisibly sense, coordinate, and communicate to support our life and well being. However, the sheer scale of the IoT has presented serious problems for current sensing technologies---mainly, the unsustainable maintenance, ecological, and economic costs of recycling or disposing of trillions of batteries. This energy storage bottleneck has prevented massive deployments of tiny sensing devices at the edge of the IoT. This dissertation explores an alternative---leave the batteries behind, and harvest the energy required for sensing tasks from the environment the device is embedded in. These sensors can be made cheaper, smaller, and will last decades longer than their battery powered counterparts, making them a perfect fit for the requirements of the IoT. These sensors can be deployed where battery powered sensors cannot---embedded in concrete, shot into space, or even implanted in animals and people. However, these batteryless sensors may lose power at any point, with no warning, for unpredictable lengths of time. Programming, profiling, debugging, and building applications with these devices pose significant challenges. First, batteryless devices operate in unpredictable environments, where voltages vary and power failures can occur at any time---often devices are in failure for hours. Second, a device\u27s behavior effects the amount of energy they can harvest---meaning small changes in tasks can drastically change harvester efficiency. Third, the programming interfaces of batteryless devices are ill-defined and non- intuitive; most developers have trouble anticipating the problems inherent with an intermittent power supply. Finally, the lack of community, and a standard usable hardware platform have reduced the resources and prototyping ability of the developer. In this dissertation we present solutions to these challenges in the form of a tool for repeatable and realistic experimentation called Ekho, a reconfigurable hardware platform named Flicker, and a language and runtime for timely execution of intermittent programs called Mayfly