Multidimensional model of estimated resource usage for multimedia NoC QoS

Multiprocessor systems are rapidly entering various high-performance computing segments, like multimedia processing. Instead of an increase in processor clock frequency, the new trend is enabling multiple cores in performing processing, e.g. dual or quadrapule CPUs in one subsystem. In this contribution, we address the problem of modeling the resource requirements of multimedia applications for a distributed computation on a multiprocessor system. This paper shows that the estimation of resource requirements based on input data enables the dynamic activation of tasks and run-time redistribution of application tasks. We also formally specify the optimal selection of the co-executed application with aim to provide the most optimal end-results of such streaming applications within one networks-on-chip (NoC) system. We present a new concept for system optimization which involves the major system parameters and resource usage. Experimental results are based on mapping an arbitrary-shaped MPEG-4 video decoder onto a multiprocessor NoC

A Scalable and Adaptive Network on Chip for Many-Core Architectures

In this work, a scalable network on chip (NoC) for future many-core architectures is proposed and investigated. It supports different QoS mechanisms to ensure predictable communication. Self-optimization is introduced to adapt the energy footprint and the performance of the network to the communication requirements. A fault tolerance concept allows to deal with permanent errors. Moreover, a template-based automated evaluation and design methodology and a synthesis flow for NoCs is introduced

Task complexity analysis and QoS management for mapping dynamic video-processing tasks on a multi-core platform

This paper addresses efficient mapping and reconfiguration of advanced video applications onto a general purpose multi-core platform. By accurately modeling the resource usage for an application, allocation of processing resources on the platform can be based on the actually needed resources instead of a worst-case approach, thereby improving Quality-of-Service (QoS). Here, we exploit a new and strongly upcoming class of dynamic video applications based on image and content analysis for resource management and control. Such applications are characterized by irregular computing behavior and memory usage. It is shown that with linear models and statistical techniques based on the Markov modeling, a rather good accuracy (94–97%) for predicting the resource usage can be obtained. This prediction accuracy is so good that it allows resource prediction at runtime, thereby leading to an actively controlled system management

Run-time management for future MPSoC platforms

In recent years, we are witnessing the dawning of the Multi-Processor Systemon- Chip (MPSoC) era. In essence, this era is triggered by the need to handle more complex applications, while reducing overall cost of embedded (handheld) devices. This cost will mainly be determined by the cost of the hardware platform and the cost of designing applications for that platform. The cost of a hardware platform will partly depend on its production volume. In turn, this means that ??exible, (easily) programmable multi-purpose platforms will exhibit a lower cost. A multi-purpose platform not only requires ??exibility, but should also combine a high performance with a low power consumption. To this end, MPSoC devices integrate computer architectural properties of various computing domains. Just like large-scale parallel and distributed systems, they contain multiple heterogeneous processing elements interconnected by a scalable, network-like structure. This helps in achieving scalable high performance. As in most mobile or portable embedded systems, there is a need for low-power operation and real-time behavior. The cost of designing applications is equally important. Indeed, the actual value of future MPSoC devices is not contained within the embedded multiprocessor IC, but in their capability to provide the user of the device with an amount of services or experiences. So from an application viewpoint, MPSoCs are designed to ef??ciently process multimedia content in applications like video players, video conferencing, 3D gaming, augmented reality, etc. Such applications typically require a lot of processing power and a signi??cant amount of memory. To keep up with ever evolving user needs and with new application standards appearing at a fast pace, MPSoC platforms need to be be easily programmable. Application scalability, i.e. the ability to use just enough platform resources according to the user requirements and with respect to the device capabilities is also an important factor. Hence scalability, ??exibility, real-time behavior, a high performance, a low power consumption and, ??nally, programmability are key components in realizing the success of MPSoC platforms. The run-time manager is logically located between the application layer en the platform layer. It has a crucial role in realizing these MPSoC requirements. As it abstracts the platform hardware, it improves platform programmability. By deciding on resource assignment at run-time and based on the performance requirements of the user, the needs of the application and the capabilities of the platform, it contributes to ??exibility, scalability and to low power operation. As it has an arbiter function between different applications, it enables real-time behavior. This thesis details the key components of such an MPSoC run-time manager and provides a proof-of-concept implementation. These key components include application quality management algorithms linked to MPSoC resource management mechanisms and policies, adapted to the provided MPSoC platform services. First, we describe the role, the responsibilities and the boundary conditions of an MPSoC run-time manager in a generic way. This includes a de??nition of the multiprocessor run-time management design space, a description of the run-time manager design trade-offs and a brief discussion on how these trade-offs affect the key MPSoC requirements. This design space de??nition and the trade-offs are illustrated based on ongoing research and on existing commercial and academic multiprocessor run-time management solutions. Consequently, we introduce a fast and ef??cient resource allocation heuristic that considers FPGA fabric properties such as fragmentation. In addition, this thesis introduces a novel task assignment algorithm for handling soft IP cores denoted as hierarchical con??guration. Hierarchical con??guration managed by the run-time manager enables easier application design and increases the run-time spatial mapping freedom. In turn, this improves the performance of the resource assignment algorithm. Furthermore, we introduce run-time task migration components. We detail a new run-time task migration policy closely coupled to the run-time resource assignment algorithm. In addition to detailing a design-environment supported mechanism that enables moving tasks between an ISP and ??ne-grained recon??gurable hardware, we also propose two novel task migration mechanisms tailored to the Network-on-Chip environment. Finally, we propose a novel mechanism for task migration initiation, based on reusing debug registers in modern embedded microprocessors. We propose a reactive on-chip communication management mechanism. We show that by exploiting an injection rate control mechanism it is possible to provide a communication management system capable of providing a soft (reactive) QoS in a NoC. We introduce a novel, platform independent run-time algorithm to perform quality management, i.e. to select an application quality operating point at run-time based on the user requirements and the available platform resources, as reported by the resource manager. This contribution also proposes a novel way to manage the interaction between the quality manager and the resource manager. In order to have a the realistic, reproducible and ??exible run-time manager testbench with respect to applications with multiple quality levels and implementation tradev offs, we have created an input data generation tool denoted Pareto Surfaces For Free (PSFF). The the PSFF tool is, to the best of our knowledge, the ??rst tool that generates multiple realistic application operating points either based on pro??ling information of a real-life application or based on a designer-controlled random generator. Finally, we provide a proof-of-concept demonstrator that combines these concepts and shows how these mechanisms and policies can operate for real-life situations. In addition, we show that the proposed solutions can be integrated into existing platform operating systems

Erreichen von Performance in Netzwerken-On-Chip für Echtzeitsysteme

In many new applications, such as in automatic driving, high performance requirements have reached safety critical real-time systems. Consequently, Networks-on-Chip (NoCs) must efficiently host new sets of highly dynamic workloads e.g., high resolution sensor fusion and data processing, autonomous decision’s making combined with machine learning. The static platform management, as used in current safety critical systems, is no more sufficient to provide the needed level of service. A dynamic platform management could meet the challenge, but it usually suffers from a lack of predictability and the simplicity necessary for certification of safety and real-time properties. In this work, we propose a novel, global and dynamic arbitration for NoCs with real-time QoS requirements. The mechanism decouples the admission control from arbitration in routers thereby simplifying a dynamic adaptation and real-time analysis. Consequently, the proposed solution allows the deployment of a sophisticated contract-based QoS provisioning without introducing complicated and hard to maintain schemes, known from the frequently applied static arbiters. The presented work introduces an overlay network to synchronize transmissions using arbitration units called Resource Managers (RMs), which allows global and work-conserving scheduling. The description of resource allocation strategies is supplemented by protocol design and verification methodology bringing adaptive control to NoC communication in setups with different QoS requirements and traffic classes. For doing that, a formal worst-case timing analysis for the mechanism has been proposed which demonstrates that this solution not only exposes higher performance in simulation but, even more importantly, consistently reaches smaller formally guaranteed worst-case latencies than other strategies for realistic levels of system's utilization. The approach is not limited to a specific network architecture or topology as the mechanism does not require modifications of routers and therefore can be used together with the majority of existing manycore systems. Indeed, the evaluation followed using the generic performance optimized router designs, as well as two systems-on-chip focused on real-time deployments. The results confirmed that the proposed approach proves to exhibit significantly higher average performance in simulation and execution.In vielen neuen sicherheitskritische Anwendungen, wie z.B. dem automatisierten Fahren, werden große Anforderungen an die Leistung von Echtzeitsysteme gestellt. Daher müssen Networks-on-Chip (NoCs) neue, hochdynamische Workloads wie z.B. hochauflösende Sensorfusion und Datenverarbeitung oder autonome Entscheidungsfindung kombiniert mit maschineller Lernen, effizient auf einem System unterbringen. Die Steuerung der zugrunde liegenden NoC-Architektur, muss die Systemsicherheit vor Fehlern, resultierend aus dem dynamischen Verhalten des Systems schützen und gleichzeitig die geforderte Performance bereitstellen. In dieser Arbeit schlagen wir eine neuartige, globale und dynamische Steuerung für NoCs mit Echtzeit QoS Anforderungen vor. Das Schema entkoppelt die Zutrittskontrolle von der Arbitrierung in Routern. Hierdurch wird eine dynamische Anpassung ermöglicht und die Echtzeitanalyse vereinfacht. Der Einsatz einer ausgefeilten vertragsbasierten Ressourcen-Zuweisung wird so ermöglicht, ohne komplexe und schwer wartbare Mechanismen, welche bereits aus dem statischen Plattformmanagement bekannt sind einzuführen. Diese Arbeit stellt ein übergelagertes Netzwerk vor, welches Übertragungen mit Hilfe von Arbitrierungseinheiten, den so genannten Resource Managern (RMs), synchronisiert. Dieses überlagerte Netzwerk ermöglicht eine globale und lasterhaltende Steuerung. Die Beschreibung verschiedener Ressourcenzuweisungstrategien wird ergänzt durch ein Protokolldesign und Methoden zur Verifikation der adaptiven NoC Steuerung mit unterschiedlichen QoS Anforderungen und Verkehrsklassen. Hierfür wird eine formale Worst Case Timing Analyse präsentiert, welche das vorgestellte Verfahren abbildet. Die Resultate bestätitgen, dass die präsentierte Lösung nicht nur eine höhere Performance in der Simulation bietet, sondern auch formal kleinere Worst-Case Latenzen für realistische Systemauslastungen als andere Strategien garantiert. Der vorgestellte Ansatz ist nicht auf eine bestimmte Netzwerkarchitektur oder Topologie beschränkt, da der Mechanismus keine Änderungen an den unterliegenden Routern erfordert und kann daher zusammen mit bestehenden Manycore-Systemen eingesetzt werden. Die Evaluierung erfolgte auf Basis eines leistungsoptimierten Router-Designs sowie zwei auf Echtzeit-Anwendungen fokusierten Platformen. Die Ergebnisse bestätigten, dass der vorgeschlagene Ansatz im Durchschnitt eine deutlich höhere Leistung in der Simulation und Ausführung liefert

Vorhersagbares und zur Laufzeit adaptierbares On-Chip Netzwerk für gemischt kritische Echtzeitsysteme

The industry of safety-critical and dependable embedded systems calls for even cheaper, high performance platforms that allow flexibility and an efficient verification of safety and real-time requirements. To cope with the increasing complexity of interconnected functions and to reduce the cost and power consumption of the system, multicore systems are used to efficiently integrate different processing units in the same chip. Networks-on-chip (NoCs), as a modular interconnect, are used as a promising solution for such multiprocessor systems on chip (MPSoCs), due to their scalability and performance. For safety-critical systems, a major goal is the avoidance of hazards. For this, safety-critical systems are qualified or even certified to prove the correctness of the functioning under all possible cases. A predictable behaviour of the NoC can help to ease the qualification process of the system. To achieve the required predictability, designers have two classes of solutions: quality of service mechanisms and (formal) analysis. For mixed-criticality systems, isolation and analysis approaches must be combined to efficiently achieve the desired predictability. Traditional NoC analysis and architecture concepts tackle only a subpart of the challenges: they focus on either performance or predictability. Existing, predictable NoCs are deemed too expensive and inflexible to host a variety of applications with opposing constraints. And state-of-the-art analyses neglect certain platform properties to verify the behaviour. Together this leads to a high over-provisioning of the hardware resources as well as adverse impacts on system performance, and on the flexibility of the system. In this work we tackle these challenges and develop a predictable and runtime-adaptable NoC architecture that efficiently integrates mixed-critical applications with opposing constraints. Additionally, we present a modelling and analysis framework for NoCs that accounts for backpressure. This framework enables to evaluate the performance and reliability early at design time. Hence, the designer can assess multiple design decisions by using abstract models and formal approaches.Die Industrie der sicherheitskritischen und zuverlässigen eingebetteten Systeme verlangt nach noch günstigeren, leistungsfähigeren Plattformen, welche Flexibilität und eine effiziente Überprüfung der Sicherheits- und Echtzeitanforderungen ermöglichen. Um der zunehmenden Komplexität der zunehmend vernetzten Funktionen gerecht zu werden und die Kosten und den Stromverbrauch eines Systems zu reduzieren, werden Mehrkern-Systeme eingesetzt. On-Chip Netzwerke werden aufgrund ihrer Skalierbarkeit und Leistung als vielversprechende Lösung für solch Mehrkern-Systeme eingesetzt. Bei sicherheitskritischen Systemen ist die Vermeidung von Gefahren ein wesentliches Ziel. Dazu werden sicherheitskritische Systeme qualifiziert oder zertifiziert, um die Funktionsfähigkeit in allen möglichen Fällen nachzuweisen. Ein vorhersehbares Verhalten des on-Chip Netzwerks kann dabei helfen, den Qualifizierungsprozess des Systems zu erleichtern. Um die erforderliche Vorhersagbarkeit zu erreichen, gibt es zwei Klassen von Lösungen: Quality of Service Mechanismen und (formale) Analyse. Für Systeme mit gemischter Relevanz müssen Isolationsmechanismen und Analyseansätze kombiniert werden, um die gewünschte Vorhersagbarkeit effizient zu erreichen. Traditionelle Analyse- und Architekturkonzepte für on-Chip Netzwerke lösen nur einen Teil dieser Herausforderungen: sie konzentrieren sich entweder auf Leistung oder Vorhersagbarkeit. Existierende vorhersagbare on-Chip Netzwerke werden als zu teuer und unflexibel erachtet, um eine Vielzahl von Anwendungen mit gegensätzlichen Anforderungen zu integrieren. Und state-of-the-art Analysen vernachlässigen bzw. vereinfachen bestimmte Plattformeigenschaften, um das Verhalten überprüfen zu können. Dies führt zu einer hohen Überbereitstellung der Hardware-Ressourcen als auch zu negativen Auswirkungen auf die Systemleistung und auf die Flexibilität des Systems. In dieser Arbeit gehen wir auf diese Herausforderungen ein und entwickeln eine vorhersehbare und zur Laufzeit anpassbare Architektur für on-Chip Netzwerke, welche gemischt-kritische Anwendungen effizient integriert. Zusätzlich stellen wir ein Modellierungs- und Analyseframework für on-Chip Netzwerke vor, das den Paketrückstau berücksichtigt. Dieses Framework ermöglicht es, Designentscheidungen anhand abstrakter Modelle und formaler Ansätze frühzeitig beurteilen

Parallel and Distributed Computing

The 14 chapters presented in this book cover a wide variety of representative works ranging from hardware design to application development. Particularly, the topics that are addressed are programmable and reconfigurable devices and systems, dependability of GPUs (General Purpose Units), network topologies, cache coherence protocols, resource allocation, scheduling algorithms, peertopeer networks, largescale network simulation, and parallel routines and algorithms. In this way, the articles included in this book constitute an excellent reference for engineers and researchers who have particular interests in each of these topics in parallel and distributed computing