Self-adaptivity of applications on network on chip multiprocessors: the case of fault-tolerant Kahn process networks

Technology scaling accompanied with higher operating frequencies and the ability to integrate more functionality in the same chip has been the driving force behind delivering higher performance computing systems at lower costs. Embedded computing systems, which have been riding the same wave of success, have evolved into complex architectures encompassing a high number of cores interconnected by an on-chip network (usually identified as Multiprocessor System-on-Chip). However these trends are hindered by issues that arise as technology scaling continues towards deep submicron scales. Firstly, growing complexity of these systems and the variability introduced by process technologies make it ever harder to perform a thorough optimization of the system at design time. Secondly, designers are faced with a reliability wall that emerges as age-related degradation reduces the lifetime of transistors, and as the probability of defects escaping post-manufacturing testing is increased. In this thesis, we take on these challenges within the context of streaming applications running in network-on-chip based parallel (not necessarily homogeneous) systems-on-chip that adopt the no-remote memory access model. In particular, this thesis tackles two main problems: (1) fault-aware online task remapping, (2) application-level self-adaptation for quality management. For the former, by viewing fault tolerance as a self-adaptation aspect, we adopt a cross-layer approach that aims at graceful performance degradation by addressing permanent faults in processing elements mostly at system-level, in particular by exploiting redundancy available in multi-core platforms. We propose an optimal solution based on an integer linear programming formulation (suitable for design time adoption) as well as heuristic-based solutions to be used at run-time. We assess the impact of our approach on the lifetime reliability. We propose two recovery schemes based on a checkpoint-and-rollback and a rollforward technique. For the latter, we propose two variants of a monitor-controller- adapter loop that adapts application-level parameters to meet performance goals. We demonstrate not only that fault tolerance and self-adaptivity can be achieved in embedded platforms, but also that it can be done without incurring large overheads. In addressing these problems, we present techniques which have been realized (depending on their characteristics) in the form of a design tool, a run-time library or a hardware core to be added to the basic architecture

Framework for Simulation of Heterogeneous MpSoC for Design Space Exploration

Due to the ever-growing requirements in high performance data computation, multiprocessor systems have been proposed to solve the bottlenecks in uniprocessor systems. Developing efficient multiprocessor systems requires effective exploration of design choices like application scheduling, mapping, and architecture design. Also, fault tolerance in multiprocessors needs to be addressed. With the advent of nanometer-process technology for chip manufacturing, realization of multiprocessors on SoC (MpSoC) is an active field of research. Developing efficient low power, fault-tolerant task scheduling, and mapping techniques for MpSoCs require optimized algorithms that consider the various scenarios inherent in multiprocessor environments. Therefore there exists a need to develop a simulation framework to explore and evaluate new algorithms on multiprocessor systems. This work proposes a modular framework for the exploration and evaluation of various design algorithms for MpSoC system. This work also proposes new multiprocessor task scheduling and mapping algorithms for MpSoCs. These algorithms are evaluated using the developed simulation framework. The paper also proposes a dynamic fault-tolerant (FT) scheduling and mapping algorithm for robust application processing. The proposed algorithms consider optimizing the power as one of the design constraints. The framework for a heterogeneous multiprocessor simulation was developed using SystemC/C++ language. Various design variations were implemented and evaluated using standard task graphs. Performance evaluation metrics are evaluated and discussed for various design scenarios

Integrated support for Adaptivity and Fault-tolerance in MPSoCs

The technology improvement and the adoption of more and more complex applications in consumer electronics are forcing a rapid increase in the complexity of multiprocessor systems on chip (MPSoCs). Following this trend, MPSoCs are becoming increasingly dynamic and adaptive, for several reasons. One of these is that applications are getting intrinsically dynamic. Another reason is that the workload on emerging MPSoCs cannot be predicted because modern systems are open to new incoming applications at run-time. A third reason which calls for adaptivity is the decreasing component reliability associated with technology scaling. Components below the 32-nm node are more inclined to temporal or even permanent faults. In case of a malfunctioning system component, the rest of the system is supposed to take over its tasks. Thus, the system adaptivity goal shall influence several de- sign decisions, that have been listed below: 1) The applications should be specified such that system adaptivity can be easily supported. To this end, we consider Polyhedral Process Networks (PPNs) as model of computation to specify applications. PPNs are composed by concurrent and autonomous processes that communicate between each other using bounded FIFO channels. Moreover, in PPNs the control is completely distributed, as well as the memories. This represents a good match with the emerging MPSoC architectures, in which processing elements and memories are usually distributed. Most importantly, the simple operational semantics of PPNs allows for an easy adoption of system adaptivity mechanisms. 2) The hardware platform should guarantee the flexibility that adaptivity mechanisms require. Networks-on-Chip (NoCs) are emerging communication infrastructures for MPSoCs that, among many other advantages, allow for system adaptivity. This is because NoCs are generic, since the same platformcan be used to run different applications, or to run the same application with different mapping of processes. However, there is a mismatch between the generic structure of the NoCs and the semantics of the PPN model. Therefore, in this thesis we investigate and propose several communication approaches to overcome this mismatch. 3) The system must be able to change the process mapping at run-time, using process migration. To this end, a process migration mechanism has been proposed and evaluated. This mechanism takes into account specific requirements of the embedded domain such as predictability and efficiency. To face the problem of graceful degradation of the system, we enriched the MADNESS NoC platform by adding fault tolerance support at both software and hardware level. The proposed process migration mechanism can be exploited to cope with permanent faults by migrating the processes running on the faulty processing element. A fast heuristic is used to determine the new mapping of the processes to tiles. The experimental results prove that the overhead in terms of execution time, due to the execution time of the remapping heuristic, together with the actual process migration, is almost negligible compared to the execution time of the whole application. This means that the proposed approach allows the system to change its performance metrics and to react to faults without a substantial impact on the user experience

Integrated support for Adaptivity and Fault-tolerance in MPSoCs

The technology improvement and the adoption of more and more complex applications in consumer electronics are forcing a rapid increase in the complexity of multiprocessor systems on chip (MPSoCs). Following this trend, MPSoCs are becoming increasingly dynamic and adaptive, for several reasons. One of these is that applications are getting intrinsically dynamic. Another reason is that the workload on emerging MPSoCs cannot be predicted because modern systems are open to new incoming applications at run-time. A third reason which calls for adaptivity is the decreasing component reliability associated with technology scaling. Components below the 32-nm node are more inclined to temporal or even permanent faults. In case of a malfunctioning system component, the rest of the system is supposed to take over its tasks. Thus, the system adaptivity goal shall influence several de- sign decisions, that have been listed below: 1) The applications should be specified such that system adaptivity can be easily supported. To this end, we consider Polyhedral Process Networks (PPNs) as model of computation to specify applications. PPNs are composed by concurrent and autonomous processes that communicate between each other using bounded FIFO channels. Moreover, in PPNs the control is completely distributed, as well as the memories. This represents a good match with the emerging MPSoC architectures, in which processing elements and memories are usually distributed. Most importantly, the simple operational semantics of PPNs allows for an easy adoption of system adaptivity mechanisms. 2) The hardware platform should guarantee the flexibility that adaptivity mechanisms require. Networks-on-Chip (NoCs) are emerging communication infrastructures for MPSoCs that, among many other advantages, allow for system adaptivity. This is because NoCs are generic, since the same platformcan be used to run different applications, or to run the same application with different mapping of processes. However, there is a mismatch between the generic structure of the NoCs and the semantics of the PPN model. Therefore, in this thesis we investigate and propose several communication approaches to overcome this mismatch. 3) The system must be able to change the process mapping at run-time, using process migration. To this end, a process migration mechanism has been proposed and evaluated. This mechanism takes into account specific requirements of the embedded domain such as predictability and efficiency. To face the problem of graceful degradation of the system, we enriched the MADNESS NoC platform by adding fault tolerance support at both software and hardware level. The proposed process migration mechanism can be exploited to cope with permanent faults by migrating the processes running on the faulty processing element. A fast heuristic is used to determine the new mapping of the processes to tiles. The experimental results prove that the overhead in terms of execution time, due to the execution time of the remapping heuristic, together with the actual process migration, is almost negligible compared to the execution time of the whole application. This means that the proposed approach allows the system to change its performance metrics and to react to faults without a substantial impact on the user experience

Zuverlässige und Energieeffiziente gemischt-kritische Echtzeit On-Chip Systeme

Multi- and many-core embedded systems are increasingly becoming the target for many applications that require high performance under varying conditions. A resulting challenge is the control, and reliable operation of such complex multiprocessing architectures under changes, e.g., high temperature and degradation. In mixed-criticality systems where many applications with varying criticalities are consolidated on the same execution platform, fundamental isolation requirements to guarantee non-interference of critical functions are crucially important. While Networks-on-Chip (NoCs) are the prevalent solution to provide scalable and efficient interconnects for the multiprocessing architectures, their associated energy consumption has immensely increased. Specifically, hard real-time NoCs must manifest limited energy consumption as thermal runaway in such a core shared resource jeopardizes the whole system guarantees. Thus, dynamic energy management of NoCs, as opposed to the related work static solutions, is highly necessary to save energy and decrease temperature, while preserving essential temporal requirements. In this thesis, we introduce a centralized management to provide energy-aware NoCs for hard real-time systems. The design relies on an energy control network, developed on top of an existing switch arbitration network to allow isolation between energy optimization and data transmission. The energy control layer includes local units called Power-Aware NoC controllers that dynamically optimize NoC energy depending on the global state and applications’ temporal requirements. Furthermore, to adapt to abnormal situations that might occur in the system due to degradation, we extend the concept of NoC energy control to include the entire system scope. That is, online resource management employing hierarchical control layers to treat system degradation (imminent core failures) is supported. The mechanism applies system reconfiguration that involves workload migration. For mixed-criticality systems, it allows flexible boundaries between safety-critical and non-critical subsystems to safely apply the reconfiguration, preserving fundamental safety requirements and temporal predictability. Simulation and formal analysis-based experiments on various realistic usecases and benchmarks are conducted showing significant improvements in NoC energy-savings and in treatment of system degradation for mixed-criticality systems improving dependability over the status quo.Eingebettete Many- und Multi-core-Systeme werden zunehmend das Ziel für Anwendungen, die hohe Anfordungen unter unterschiedlichen Bedinungen haben. Für solche hochkomplexed Multi-Prozessor-Systeme ist es eine grosse Herausforderung zuverlässigen Betrieb sicherzustellen, insbesondere wenn sich die Umgebungseinflüsse verändern. In Systeme mit gemischter Kritikalität, in denen viele Anwendungen mit unterschiedlicher Kritikalität auf derselben Ausführungsplattform bedient werden müssen, sind grundlegende Isolationsanforderungen zur Gewährleistung der Nichteinmischung kritischer Funktionen von entscheidender Bedeutung. Während On-Chip Netzwerke (NoCs) häufig als skalierbare Verbindung für die Multiprozessor-Architekturen eingesetzt werden, ist der damit verbundene Energieverbrauch immens gestiegen. Daher sind dynamische Plattformverwaltungen, im Gegensatz zu den statischen, zwingend notwendig, um ein System an die oben genannten Veränderungen anzupassen und gleichzeitig Timing zu gewährleisten. In dieser Arbeit entwickeln wir energieeffiziente NoCs für harte Echtzeitsysteme. Das Design basiert auf einem Energiekontrollnetzwerk, das auf einem bestehenden Switch-Arbitration-Netzwerk entwickelt wurde, um eine Isolierung zwischen Energieoptimierung und Datenübertragung zu ermöglichen. Die Energiesteuerungsschicht umfasst lokale Einheiten, die als Power-Aware NoC-Controllers bezeichnet werden und die die NoC-Energie in Abhängigkeit vom globalen Zustand und den zeitlichen Anforderungen der Anwendungen optimieren. Darüber hinaus wird das Konzept der NoC-Energiekontrolle zur Anpassung an Anomalien, die aufgrund von Abnutzung auftreten können, auf den gesamten Systemumfang ausgedehnt. Online- Ressourcenverwaltungen, die hierarchische Kontrollschichten zur Behandlung Abnutzung (drohender Kernausfälle) einsetzen, werden bereitgestellt. Bei Systemen mit gemischter Kritikalität erlaubt es flexible Grenzen zwischen sicherheitskritischen und unkritischen Subsystemen, um die Rekonfiguration sicher anzuwenden, wobei grundlegende Sicherheitsanforderungen erhalten bleiben und Timing Vorhersehbarkeit. Experimente werden auf der Basis von Simulationen und formalen Analysen zu verschiedenen realistischen Anwendungsfallen und Benchmarks durchgeführt, die signifikanten Verbesserungen bei On-Chip Netzwerke-Energieeinsparungen und bei der Behandlung von Abnutzung für Systeme mit gemischter Kritikalität zur Verbesserung die Systemstabilität gegenüber dem bisherigen Status quo zeigen

Design Space Exploration and Resource Management of Multi/Many-Core Systems

The increasing demand of processing a higher number of applications and related data on computing platforms has resulted in reliance on multi-/many-core chips as they facilitate parallel processing. However, there is a desire for these platforms to be energy-efficient and reliable, and they need to perform secure computations for the interest of the whole community. This book provides perspectives on the aforementioned aspects from leading researchers in terms of state-of-the-art contributions and upcoming trends

Run-time management of many-core SoCs: A communication-centric approach

The single core performance hit the power and complexity limits in the beginning of this century, moving the industry towards the design of multi- and many-core system-on-chips (SoCs). The on-chip communication between the cores plays a criticalrole in the performance of these SoCs, with power dissipation, communication latency, scalability to many cores, and reliability against the transistor failures as the main design challenges. Accordingly, we dedicate this thesis to the communicationcentered management of the many-core SoCs, with the goal to advance the state-ofthe-art in addressing these challenges. To this end, we contribute to on-chip communication of many-core SoCs in three main directions. First, we start with a synthesizable SoC with full system simulation. We demonstrate the importance of the networking overhead in a practical system, and propose our sophisticated network interface (NI) that offloads the work from SW to HW. Our results show around 5x and up to 50x higher network performance, compared to previous works. As the second direction of this thesis, we study the significance of run-time application mapping. We demonstrate that contiguous application mapping not only improves the network latency (by 23%) and power dissipation (by 50%), but also improves the system throughput (by 3%) and quality-of-service (QoS) of soft real-time applications (up to 100x less deadline misses). Also our hierarchical run-time application mapping provides 99.41% successful mapping when up to 8 links are broken. As the final direction of the thesis, we propose a fault-tolerant routing algorithm, the maze-routing. It is the first-in-class algorithm that provides guaranteed delivery, a fully-distributed solution, low area overhead (by 16x), and instantaneous reconfiguration (vs. 40K cycles down time of previous works), all at the same time. Besides the individual goals of each contribution, when applicable, we ensure that our solutions scale to extreme network sizes like 12x12 and 16x16. This thesis concludes that the communication overhead and its optimization play a significant role in the performance of many-core SoC

Dynamic Resource Allocation in Embedded, High-Performance and Cloud Computing

The availability of many-core computing platforms enables a wide variety of technical solutions for systems across the embedded, high-performance and cloud computing domains. However, large scale manycore systems are notoriously hard to optimise. Choices regarding resource allocation alone can account for wide variability in timeliness and energy dissipation (up to several orders of magnitude). Dynamic Resource Allocation in Embedded, High-Performance and Cloud Computing covers dynamic resource allocation heuristics for manycore systems, aiming to provide appropriate guarantees on performance and energy efficiency. It addresses different types of systems, aiming to harmonise the approaches to dynamic allocation across the complete spectrum between systems with little flexibility and strict real-time guarantees all the way to highly dynamic systems with soft performance requirements. Technical topics presented in the book include: Load and Resource Models Admission Control Feedback-based Allocation and Optimisation Search-based Allocation Heuristics Distributed Allocation based on Swarm Intelligence Value-Based Allocation Each of the topics is illustrated with examples based on realistic computational platforms such as Network-on-Chip manycore processors, grids and private cloud environments.Note.-- EUR 6,000 BPC fee funded by the EC FP7 Post-Grant Open Access Pilo

Dynamic Resource Allocation in Embedded, High-Performance and Cloud Computing

The availability of many-core computing platforms enables a wide variety of technical solutions for systems across the embedded, high-performance and cloud computing domains. However, large scale manycore systems are notoriously hard to optimise. Choices regarding resource allocation alone can account for wide variability in timeliness and energy dissipation (up to several orders of magnitude). Dynamic Resource Allocation in Embedded, High-Performance and Cloud Computing covers dynamic resource allocation heuristics for manycore systems, aiming to provide appropriate guarantees on performance and energy efficiency. It addresses different types of systems, aiming to harmonise the approaches to dynamic allocation across the complete spectrum between systems with little flexibility and strict real-time guarantees all the way to highly dynamic systems with soft performance requirements. Technical topics presented in the book include: • Load and Resource Models• Admission Control• Feedback-based Allocation and Optimisation• Search-based Allocation Heuristics• Distributed Allocation based on Swarm Intelligence• Value-Based AllocationEach of the topics is illustrated with examples based on realistic computational platforms such as Network-on-Chip manycore processors, grids and private cloud environments