48 research outputs found

    Characterizing the Effects of Intermittent Faults on a Processor for Dependability Enhancement Strategy

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    As semiconductor technology scales into the nanometer regime, intermittent faults have become an increasing threat. This paper focuses on the effects of intermittent faults on NET versus REG on one hand and the implications for dependability strategy on the other. First, the vulnerability characteristics of representative units in OpenSPARC T2 are revealed, and in particular, the highly sensitive modules are identified. Second, an arch-level dependability enhancement strategy is proposed, showing that events such as core/strand running status and core-memory interface events can be candidates of detectable symptoms. A simple watchdog can be deployed to detect application running status (IEXE event). Then SDC (silent data corruption) rate is evaluated demonstrating its potential. Third and last, the effects of traditional protection schemes in the target CMT to intermittent faults are quantitatively studied on behalf of the contribution of each trap type, demonstrating the necessity of taking this factor into account for the strategy

    Dependable Embedded Systems

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    This Open Access book introduces readers to many new techniques for enhancing and optimizing reliability in embedded systems, which have emerged particularly within the last five years. This book introduces the most prominent reliability concerns from today’s points of view and roughly recapitulates the progress in the community so far. Unlike other books that focus on a single abstraction level such circuit level or system level alone, the focus of this book is to deal with the different reliability challenges across different levels starting from the physical level all the way to the system level (cross-layer approaches). The book aims at demonstrating how new hardware/software co-design solution can be proposed to ef-fectively mitigate reliability degradation such as transistor aging, processor variation, temperature effects, soft errors, etc. Provides readers with latest insights into novel, cross-layer methods and models with respect to dependability of embedded systems; Describes cross-layer approaches that can leverage reliability through techniques that are pro-actively designed with respect to techniques at other layers; Explains run-time adaptation and concepts/means of self-organization, in order to achieve error resiliency in complex, future many core systems

    Adaptive Distributed Architectures for Future Semiconductor Technologies.

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    Year after year semiconductor manufacturing has been able to integrate more components in a single computer chip. These improvements have been possible through systematic shrinking in the size of its basic computational element, the transistor. This trend has allowed computers to progressively become faster, more efficient and less expensive. As this trend continues, experts foresee that current computer designs will face new challenges, in utilizing the minuscule devices made available by future semiconductor technologies. Today's microprocessor designs are not fit to overcome these challenges, since they are constrained by their inability to handle component failures by their lack of adaptability to a wide range of custom modules optimized for specific applications and by their limited design modularity. The focus of this thesis is to develop original computer architectures, that can not only survive these new challenges, but also leverage the vast number of transistors available to unlock better performance and efficiency. The work explores and evaluates new software and hardware techniques to enable the development of novel adaptive and modular computer designs. The thesis first explores an infrastructure to quantitatively assess the fallacies of current systems and their inadequacy to operate on unreliable silicon. In light of these findings, specific solutions are then proposed to strengthen digital system architectures, both through hardware and software techniques. The thesis culminates with the proposal of a radically new architecture design that can fully adapt dynamically to operate on the hardware resources available on chip, however limited or abundant those may be.PHDComputer Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/102405/1/apellegr_1.pd

    Improving redundant multithreading performance for soft-error detection in HPC applications

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    Tesis de Graduación (Maestría en Computación) Instituto Tecnológico de Costa Rica, Escuela de Computación, 2018As HPC systems move towards extreme scale, soft errors leading to silent data corruptions become a major concern. In this thesis, we propose a set of three optimizations to the classical Redundant Multithreading (RMT) approach to allow faster soft error detection. First, we leverage the use of Simultaneous Multithreading (SMT) to collocate sibling replicated threads on the same physical core to efficiently exchange data to expose errors. Some HPC applications cannot fully exploit SMT for performance improvement and instead, we propose to use these additional resources for fault tolerance. Second, we present variable aggregation to group several values together and use this merged value to speed up detection of soft errors. Third, we introduce selective checking to decrease the number of checked values to a minimum. The last two techniques reduce the overall performance overhead by relaxing the soft error detection scope. Our experimental evaluation, executed on recent multicore processors with representative HPC benchmarks, proves that the use of SMT for fault tolerance can enhance RMT performance. It also shows that, at constant computing power budget, with optimizations applied, the overhead of the technique can be significantly lower than the classical RMT replicated execution. Furthermore, these results show that RMT can be a viable solution for soft-error detection at extreme scale

    Code optimizations for narrow bitwidth architectures

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    This thesis takes a HW/SW collaborative approach to tackle the problem of computational inefficiency in a holistic manner. The hardware is redesigned by restraining the datapath to merely 16-bit datawidth (integer datapath only) to provide an extremely simple, low-cost, low-complexity execution core which is best at executing the most common case efficiently. This redesign, referred to as the Narrow Bitwidth Architecture, is unique in that although the datapath is squeezed to 16-bits, it continues to offer the advantage of higher memory addressability like the contemporary wider datapath architectures. Its interface to the outside (software) world is termed as the Narrow ISA. The software is responsible for efficiently mapping the current stack of 64-bit applications onto the 16-bit hardware. However, this HW/SW approach introduces a non-negligible penalty both in dynamic code-size and performance-impact even with a reasonably smart code-translator that maps the 64- bit applications on to the 16-bit processor. The goal of this thesis is to design a software layer that harnesses the power of compiler optimizations to assuage this negative performance penalty of the Narrow ISA. More specifically, this thesis focuses on compiler optimizations targeting the problem of how to compile a 64-bit program to a 16-bit datapath machine from the perspective of Minimum Required Computations (MRC). Given a program, the notion of MRC aims to infer how much computation is really required to generate the same (correct) output as the original program. Approaching perfect MRC is an intrinsically ambitious goal and it requires oracle predictions of program behavior. Towards this end, the thesis proposes three heuristic-based optimizations to closely infer the MRC. The perspective of MRC unfolds into a definition of productiveness - if a computation does not alter the storage location, it is non-productive and hence, not necessary to be performed. In this research, the definition of productiveness has been applied to different granularities of the data-flow as well as control-flow of the programs. Three profile-based, code optimization techniques have been proposed : 1. Global Productiveness Propagation (GPP) which applies the concept of productiveness at the granularity of a function. 2. Local Productiveness Pruning (LPP) applies the same concept but at a much finer granularity of a single instruction. 3. Minimal Branch Computation (MBC) is an profile-based, code-reordering optimization technique which applies the principles of MRC for conditional branches. The primary aim of all these techniques is to reduce the dynamic code footprint of the Narrow ISA. The first two optimizations (GPP and LPP) perform the task of speculatively pruning the non-productive (useless) computations using profiles. Further, these two optimization techniques perform backward traversal of the optimization regions to embed checks into the nonspeculative slices, hence, making them self-sufficient to detect mis-speculation dynamically. The MBC optimization is a use case of a broader concept of a lazy computation model. The idea behind MBC is to reorder the backslices containing narrow computations such that the minimal necessary computations to generate the same (correct) output are performed in the most-frequent case; the rest of the computations are performed only when necessary. With the proposed optimizations, it can be concluded that there do exist ways to smartly compile a 64-bit application to a 16- bit ISA such that the overheads are considerably reduced.Esta tesis deriva su motivación en la inherente ineficiencia computacional de los procesadores actuales: a pesar de que muchas aplicaciones contemporáneas tienen unos requisitos de ancho de bits estrechos (aplicaciones de enteros, de red y multimedia), el hardware acaba utilizando el camino de datos completo, utilizando más recursos de los necesarios y consumiendo más energía. Esta tesis utiliza una aproximación HW/SW para atacar, de forma íntegra, el problema de la ineficiencia computacional. El hardware se ha rediseñado para restringir el ancho de bits del camino de datos a sólo 16 bits (únicamente el de enteros) y ofrecer así un núcleo de ejecución simple, de bajo consumo y baja complejidad, el cual está diseñado para ejecutar de forma eficiente el caso común. El rediseño, llamado en esta tesis Arquitectura de Ancho de Bits Estrecho (narrow bitwidth en inglés), es único en el sentido que aunque el camino de datos se ha estrechado a 16 bits, el sistema continúa ofreciendo las ventajas de direccionar grandes cantidades de memoria tal como procesadores con caminos de datos más anchos (64 bits actualmente). Su interface con el mundo exterior se denomina ISA estrecho. En nuestra propuesta el software es responsable de mapear eficientemente la actual pila software de las aplicaciones de 64 bits en el hardware de 16 bits. Sin embargo, esta aproximación HW/SW introduce penalizaciones no despreciables tanto en el tamaño del código dinámico como en el rendimiento, incluso con un traductor de código inteligente que mapea las aplicaciones de 64 bits en el procesador de 16 bits. El objetivo de esta tesis es el de diseñar una capa software que aproveche la capacidad de las optimizaciones para reducir el efecto negativo en el rendimiento del ISA estrecho. Concretamente, esta tesis se centra en optimizaciones que tratan el problema de como compilar programas de 64 bits para una máquina de 16 bits desde la perspectiva de las Mínimas Computaciones Requeridas (MRC en inglés). Dado un programa, la noción de MRC intenta deducir la cantidad de cómputo que realmente se necesita para generar la misma (correcta) salida que el programa original. Aproximarse al MRC perfecto es una meta intrínsecamente ambiciosa y que requiere predicciones perfectas de comportamiento del programa. Con este fin, la tesis propone tres heurísticas basadas en optimizaciones que tratan de inferir el MRC. La utilización de MRC se desarrolla en la definición de productividad: si un cálculo no altera el dato que ya había almacenado, entonces no es productivo y por lo tanto, no es necesario llevarlo a cabo. Se han propuesto tres optimizaciones del código basadas en profile: 1. Propagación Global de la Productividad (GPP en inglés) aplica el concepto de productividad a la granularidad de función. 2. Poda Local de Productividad (LPP en inglés) aplica el mismo concepto pero a una granularidad mucho más fina, la de una única instrucción. 3. Computación Mínima del Salto (MBC en inglés) es una técnica de reordenación de código que aplica los principios de MRC a los saltos condicionales. El objetivo principal de todas esta técnicas es el de reducir el tamaño dinámico del código estrecho. Las primeras dos optimizaciones (GPP y LPP) realizan la tarea de podar especulativamente las computaciones no productivas (innecesarias) utilizando profiles. Además, estas dos optimizaciones realizan un recorrido hacia atrás de las regiones a optimizar para añadir chequeos en el código no especulativo, haciendo de esta forma la técnica autosuficiente para detectar, dinámicamente, los casos de fallo en la especulación. La idea de la optimización MBC es reordenar las instrucciones que generan el salto condicional tal que las mínimas computaciones que general la misma (correcta) salida se ejecuten en la mayoría de los casos; el resto de las computaciones se ejecutarán sólo cuando sea necesario

    Techniques for Processing TCP/IP Flow Content in Network Switches at Gigabit Line Rates

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    The growth of the Internet has enabled it to become a critical component used by businesses, governments and individuals. While most of the traffic on the Internet is legitimate, a proportion of the traffic includes worms, computer viruses, network intrusions, computer espionage, security breaches and illegal behavior. This rogue traffic causes computer and network outages, reduces network throughput, and costs governments and companies billions of dollars each year. This dissertation investigates the problems associated with TCP stream processing in high-speed networks. It describes an architecture that simplifies the processing of TCP data streams in these environments and presents a hardware circuit capable of TCP stream processing on multi-gigabit networks for millions of simultaneous network connections. Live Internet traffic is analyzed using this new TCP processing circuit

    Proceedings of the 5th International Workshop on Reconfigurable Communication-centric Systems on Chip 2010 - ReCoSoC\u2710 - May 17-19, 2010 Karlsruhe, Germany. (KIT Scientific Reports ; 7551)

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    ReCoSoC is intended to be a periodic annual meeting to expose and discuss gathered expertise as well as state of the art research around SoC related topics through plenary invited papers and posters. The workshop aims to provide a prospective view of tomorrow\u27s challenges in the multibillion transistor era, taking into account the emerging techniques and architectures exploring the synergy between flexible on-chip communication and system reconfigurability

    Cross layer reliability estimation for digital systems

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    Forthcoming manufacturing technologies hold the promise to increase multifuctional computing systems performance and functionality thanks to a remarkable growth of the device integration density. Despite the benefits introduced by this technology improvements, reliability is becoming a key challenge for the semiconductor industry. With transistor size reaching the atomic dimensions, vulnerability to unavoidable fluctuations in the manufacturing process and environmental stress rise dramatically. Failing to meet a reliability requirement may add excessive re-design cost to recover and may have severe consequences on the success of a product. %Worst-case design with large margins to guarantee reliable operation has been employed for long time. However, it is reaching a limit that makes it economically unsustainable due to its performance, area, and power cost. One of the open challenges for future technologies is building ``dependable'' systems on top of unreliable components, which will degrade and even fail during normal lifetime of the chip. Conventional design techniques are highly inefficient. They expend significant amount of energy to tolerate the device unpredictability by adding safety margins to a circuit's operating voltage, clock frequency or charge stored per bit. Unfortunately, the additional cost introduced to compensate unreliability are rapidly becoming unacceptable in today's environment where power consumption is often the limiting factor for integrated circuit performance, and energy efficiency is a top concern. Attention should be payed to tailor techniques to improve the reliability of a system on the basis of its requirements, ending up with cost-effective solutions favoring the success of the product on the market. Cross-layer reliability is one of the most promising approaches to achieve this goal. Cross-layer reliability techniques take into account the interactions between the layers composing a complex system (i.e., technology, hardware and software layers) to implement efficient cross-layer fault mitigation mechanisms. Fault tolerance mechanism are carefully implemented at different layers starting from the technology up to the software layer to carefully optimize the system by exploiting the inner capability of each layer to mask lower level faults. For this purpose, cross-layer reliability design techniques need to be complemented with cross-layer reliability evaluation tools, able to precisely assess the reliability level of a selected design early in the design cycle. Accurate and early reliability estimates would enable the exploration of the system design space and the optimization of multiple constraints such as performance, power consumption, cost and reliability. This Ph.D. thesis is devoted to the development of new methodologies and tools to evaluate and optimize the reliability of complex digital systems during the early design stages. More specifically, techniques addressing hardware accelerators (i.e., FPGAs and GPUs), microprocessors and full systems are discussed. All developed methodologies are presented in conjunction with their application to real-world use cases belonging to different computational domains

    A Hybrid-parallel Architecture for Applications in Bioinformatics

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    Since the advent of Next Generation Sequencing (NGS) technology, the amount of data from whole genome sequencing has been rising fast. In turn, the availability of these resources led to the tapping of whole new research fields in molecular and cellular biology, producing even more data. On the other hand, the available computational power is only increasing linearly. In recent years though, special-purpose high-performance devices started to become prevalent in today’s scientific data centers, namely graphics processing units (GPUs) and, to a lesser extent, field-programmable gate arrays (FPGAs). Driven by the need for performance, developers started porting regular applications to GPU frameworks and FPGA configurations to exploit the special operations only these devices may perform in a timely manner. However, applications using both accelerator technologies are still rare. Major challenges in joint GPU/FPGA application development include the required deep knowledge of associated programming paradigms and the efficient communication both types of devices. In this work, two algorithms from bioinformatics are implemented on a custom hybrid-parallel hardware architecture and a highly concurrent software platform. It is shown that such a solution is not only possible to develop but also its ability to outperform implementations on similar- sized GPU or FPGA clusters in terms of both performance and energy consumption. Both algorithms analyze case/control data from genome- wide association studies to find interactions between two or three genes with different methods. Especially in the latter case, the newly available calculation power and method enables analyses of large data sets for the first time without occupying whole data centers for weeks. The success of the hybrid-parallel architecture proposal led to the development of a high- end array of FPGA/GPU accelerator pairs to provide even better runtimes and more possibilities
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