Interconnect yield analysis and fault tolerance for field programmable gate arrays

Imperial Users onl

A fault-tolerant multiprocessor architecture for aircraft, volume 1

A fault-tolerant multiprocessor architecture is reported. This architecture, together with a comprehensive information system architecture, has important potential for future aircraft applications. A preliminary definition and assessment of a suitable multiprocessor architecture for such applications is developed

System configuration and executive requirements specifications for reusable shuttle and space station/base

System configuration and executive requirements specifications for reusable shuttle and space station/bas

Report of activities of the advanced coal extraction systems definition project, 1979 - 1980

During this period effort was devoted to: formulation of system performance goals in the areas of production cost, miner safety, miner health, environmental impact, and coal conservation, survey and in depth assessment of promising technology, and characterization of potential resource targets. Primary system performance goals are to achieve a return on incremental investment of 150% of the value required for a low risk capital improvement project and to reduce deaths and disability injuries per million man-hour by 50%. Although these performance goals were developed to be immediately applicable to the Central Appalachian coal resources, they were also designed to be readily adaptable to other coals by appending a geological description of the new resource. The work done on technology assessment was concerned with the performance of the slurry haulage system

Recovery Time Considerations in Real-Time Systems Employing Software Fault Tolerance

Safety-critical real-time systems like modern automobiles with advanced driving-assist features must employ redundancy for crucial software tasks to tolerate permanent crash faults. This redundancy can be achieved by using techniques like active replication or the primary-backup approach. In such systems, the recovery time which is the amount of time it takes for a redundant task to take over execution on the failure of a primary task becomes a very important design parameter. The recovery time for a given task depends on various factors like task allocation, primary and redundant task priorities, system load and the scheduling policy. Each task can also have a different recovery time requirement (RTR). For example, in automobiles with automated driving features, safety-critical tasks like perception and steering control have strict RTRs, whereas such requirements are more relaxed in the case of tasks like heating control and mission planning. In this paper, we analyze the recovery time for software tasks in a real-time system employing Rate-Monotonic Scheduling (RMS). We derive bounds on the recovery times for different redundant task options and propose techniques to determine the redundant-task type for a task to satisfy its RTR. We also address the fault-tolerant task allocation problem, with the additional constraint of satisfying the RTR of each task in the system. Given that the problem of assigning tasks to processors is a well-known NP-hard bin-packing problem we propose computationally-efficient heuristics to find a feasible allocation of tasks and their redundant copies. We also apply the simulated annealing method to the fault-tolerant task allocation problem with RTR constraints and compare against our heuristics

Transiency-driven Resource Management for Cloud Computing Platforms

Modern distributed server applications are hosted on enterprise or cloud data centers that provide computing, storage, and networking capabilities to these applications. These applications are built using the implicit assumption that the underlying servers will be stable and normally available, barring for occasional faults. In many emerging scenarios, however, data centers and clouds only provide transient, rather than continuous, availability of their servers. Transiency in modern distributed systems arises in many contexts, such as green data centers powered using renewable intermittent sources, and cloud platforms that provide lower-cost transient servers which can be unilaterally revoked by the cloud operator. Transient computing resources are increasingly important, and existing fault-tolerance and resource management techniques are inadequate for transient servers because applications typically assume continuous resource availability. This thesis presents research in distributed systems design that treats transiency as a first-class design principle. I show that combining transiency-specific fault-tolerance mechanisms with resource management policies to suit application characteristics and requirements, can yield significant cost and performance benefits. These mechanisms and policies have been implemented and prototyped as part of software systems, which allow a wide range of applications, such as interactive services and distributed data processing, to be deployed on transient servers, and can reduce cloud computing costs by up to 90\%. This thesis makes contributions to four areas of computer systems research: transiency-specific fault-tolerance, resource allocation, abstractions, and resource reclamation. For reducing the impact of transient server revocations, I develop two fault-tolerance techniques that are tailored to transient server characteristics and application requirements. For interactive applications, I build a derivative cloud platform that masks revocations by transparently moving application-state between servers of different types. Similarly, for distributed data processing applications, I investigate the use of application level periodic checkpointing to reduce the performance impact of server revocations. For managing and reducing the risk of server revocations, I investigate the use of server portfolios that allow transient resource allocation to be tailored to application requirements. Finally, I investigate how resource providers (such as cloud platforms) can provide transient resource availability without revocation, by looking into alternative resource reclamation techniques. I develop resource deflation, wherein a server\u27s resources are fractionally reclaimed, allowing the application to continue execution albeit with fewer resources. Resource deflation generalizes revocation, and the deflation mechanisms and cluster-wide policies can yield both high cluster utilization and low application performance degradation

Predictive Reliability and Fault Management in Exascale Systems: State of the Art and Perspectives

© ACM, 2020. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM Computing Surveys, Vol. 53, No. 5, Article 95. Publication date: September 2020. https://doi.org/10.1145/3403956[EN] Performance and power constraints come together with Complementary Metal Oxide Semiconductor technology scaling in future Exascale systems. Technology scaling makes each individual transistor more prone to faults and, due to the exponential increase in the number of devices per chip, to higher system fault rates. Consequently, High-performance Computing (HPC) systems need to integrate prediction, detection, and recovery mechanisms to cope with faults efficiently. This article reviews fault detection, fault prediction, and recovery techniques in HPC systems, from electronics to system level. We analyze their strengths and limitations. Finally, we identify the promising paths to meet the reliability levels of Exascale systems.This work has received funding from the European Union's Horizon 2020 (H2020) research and innovation program under the FET-HPC Grant Agreement No. 801137 (RECIPE). Jaume Abella was also partially supported by the Ministry of Economy and Competitiveness of Spain under Contract No. TIN2015-65316-P and under Ramon y Cajal Postdoctoral Fellowship No. RYC-2013-14717, as well as by the HiPEAC Network of Excellence. Ramon Canal is partially supported by the Generalitat de Catalunya under Contract No. 2017SGR0962.Canal, R.; Hernández Luz, C.; Tornero-Gavilá, R.; Cilardo, A.; Massari, G.; Reghenzani, F.; Fornaciari, W.... (2020). Predictive Reliability and Fault Management in Exascale Systems: State of the Art and Perspectives. ACM Computing Surveys. 53(5):1-32. https://doi.org/10.1145/3403956S132535Abella, J., Hernandez, C., Quinones, E., Cazorla, F. J., Conmy, P. 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Autonomous Recovery Of Reconfigurable Logic Devices Using Priority Escalation Of Slack

Field Programmable Gate Array (FPGA) devices offer a suitable platform for survivable hardware architectures in mission-critical systems. In this dissertation, active dynamic redundancy-based fault-handling techniques are proposed which exploit the dynamic partial reconfiguration capability of SRAM-based FPGAs. Self-adaptation is realized by employing reconfiguration in detection, diagnosis, and recovery phases. To extend these concepts to semiconductor aging and process variation in the deep submicron era, resilient adaptable processing systems are sought to maintain quality and throughput requirements despite the vulnerabilities of the underlying computational devices. A new approach to autonomous fault-handling which addresses these goals is developed using only a uniplex hardware arrangement. It operates by observing a health metric to achieve Fault Demotion using Recon- figurable Slack (FaDReS). Here an autonomous fault isolation scheme is employed which neither requires test vectors nor suspends the computational throughput, but instead observes the value of a health metric based on runtime input. The deterministic flow of the fault isolation scheme guarantees success in a bounded number of reconfigurations of the FPGA fabric. FaDReS is then extended to the Priority Using Resource Escalation (PURE) online redundancy scheme which considers fault-isolation latency and throughput trade-offs under a dynamic spare arrangement. While deep-submicron designs introduce new challenges, use of adaptive techniques are seen to provide several promising avenues for improving resilience. The scheme developed is demonstrated by hardware design of various signal processing circuits and their implementation on a Xilinx Virtex-4 FPGA device. These include a Discrete Cosine Transform (DCT) core, Motion Estimation (ME) engine, Finite Impulse Response (FIR) Filter, Support Vector Machine (SVM), and Advanced Encryption Standard (AES) blocks in addition to MCNC benchmark circuits. A iii significant reduction in power consumption is achieved ranging from 83% for low motion-activity scenes to 12.5% for high motion activity video scenes in a novel ME engine configuration. For a typical benchmark video sequence, PURE is shown to maintain a PSNR baseline near 32dB. The diagnosability, reconfiguration latency, and resource overhead of each approach is analyzed. Compared to previous alternatives, PURE maintains a PSNR within a difference of 4.02dB to 6.67dB from the fault-free baseline by escalating healthy resources to higher-priority signal processing functions. The results indicate the benefits of priority-aware resiliency over conventional redundancy approaches in terms of fault-recovery, power consumption, and resource-area requirements. Together, these provide a broad range of strategies to achieve autonomous recovery of reconfigurable logic devices under a variety of constraints, operating conditions, and optimization criteria

SUSTAINABLE LIFETIME VALUE CREATION THROUGH INNOVATIVE PRODUCT DESIGN: A PRODUCT ASSURANCE MODEL

In the field of product development, many organizations struggle to create a value proposition that can overcome the headwinds of technology change, regulatory requirements, and intense competition, in an effort to satisfy the long-term goals of sustainability. Today, organizations are realizing that they have lost portfolio value due to poor reliability, early product retirement, and abandoned design platforms. Beyond Lean and Green Manufacturing, shareholder value can be enhanced by taking a broader perspective, and integrating sustainability innovation elements into product designs in order to improve the delivery process and extend the life of product platforms. This research is divided into two parts that lead to closing the loop towards Sustainable Value Creation in product development. The first section presents a framework for achieving Sustainable Lifetime Value through a toolset that bridges the gap between financial success and sustainable product design. Focus is placed on the analysis of the sustainable value proposition between producers, consumers, society, and the environment and the half-life of product platforms. The Half-Life Return Model is presented, designed to provide feedback to producers in the pursuit of improving the return on investment for the primary stakeholders. The second part applies the driving aspects of the framework with the development of an Adaptive Genetic Search Algorithm. The algorithm is designed to improve fault detection and mitigation during the product delivery process. A computer simulation is used to study the effectiveness of primary aspects introduced in the search algorithm, in order to attempt to improve the reliability growth of the system during the development life-cycle. The results of the analysis draw attention to the sensitivity of the driving aspects identified in the product development lifecycle, which affect the long term goals of sustainable product development. With the use of the techniques identified in this research, cost effective test case generation can be improved without a major degradation in the diversity of the search patterns required to insure a high level of fault detection. This in turn can lead to improvements in the driving aspects of the Half-Life Return Model, and ultimately the goal of designing sustainable products and processes