5,405 research outputs found

    Resilient Design for Process and Runtime Variations

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    The main objective of this thesis is to tackle the impact of parameter variations in order to improve the chip performance and extend its lifetime

    Reasoning and Improving on Software Resilience against Unanticipated Exceptions

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    In software, there are the errors anticipated at specification and design time, those encountered at development and testing time, and those that happen in production mode yet never anticipated. In this paper, we aim at reasoning on the ability of software to correctly handle unanticipated exceptions. We propose an algorithm, called short-circuit testing, which injects exceptions during test suite execution so as to simulate unanticipated errors. This algorithm collects data that is used as input for verifying two formal exception contracts that capture two resilience properties. Our evaluation on 9 test suites, with 78% line coverage in average, analyzes 241 executed catch blocks, shows that 101 of them expose resilience properties and that 84 can be transformed to be more resilient

    Enabling System-Level Modeling of Variation-Induced Faults in Networks-on-Chip

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    Process Variation (PV) is increasingly threatening the reliability of Networks-on-Chips. Thus, various resilient router designs have been recently proposed and evaluated. However, these evaluations assume random fault distributions, which result in 52%--81% inaccuracy. We propose an accurate circuit-level fault-modeling tool, which can be plugged into any system-level NoC simulator, quantify the system-level impact of PV-induced faults at runtime, pinpoint fault-prone router components that should be protected, and accurately evaluate alternative resilient multi-core designs.GigaScale Systems Research CenterFocus Center Research Program. Focus Center for Circuit & System Solutions. Semiconductor Research Corporation. Interconnect Focus Cente

    Computing Web-scale Topic Models using an Asynchronous Parameter Server

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    Topic models such as Latent Dirichlet Allocation (LDA) have been widely used in information retrieval for tasks ranging from smoothing and feedback methods to tools for exploratory search and discovery. However, classical methods for inferring topic models do not scale up to the massive size of today's publicly available Web-scale data sets. The state-of-the-art approaches rely on custom strategies, implementations and hardware to facilitate their asynchronous, communication-intensive workloads. We present APS-LDA, which integrates state-of-the-art topic modeling with cluster computing frameworks such as Spark using a novel asynchronous parameter server. Advantages of this integration include convenient usage of existing data processing pipelines and eliminating the need for disk writes as data can be kept in memory from start to finish. Our goal is not to outperform highly customized implementations, but to propose a general high-performance topic modeling framework that can easily be used in today's data processing pipelines. We compare APS-LDA to the existing Spark LDA implementations and show that our system can, on a 480-core cluster, process up to 135 times more data and 10 times more topics without sacrificing model quality.Comment: To appear in SIGIR 201

    Power efficient resilient microarchitectures for PVT variability mitigation

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    Nowadays, the high power density and the process, voltage, and temperature variations became the most critical issues that limit the performance of the digital integrated circuits because of the continuous scaling of the fabrication technology. Dynamic voltage and frequency scaling technique is used to reduce the power consumption while different time relaxation techniques and error recovery microarchitectures are used to tolerate the process, voltage, and temperature variations. These techniques reduce the throughput by scaling down the frequency or flushing and restarting the errant pipeline. This thesis presents a novel resilient microarchitecture which is called ERSUT-based resilient microarchitecture to tolerate the induced delays generated by the voltage scaling or the process, voltage, and temperature variations. The resilient microarchitecture detects and recovers the induced errors without flushing the pipeline and without scaling down the operating frequency. An ERSUT-based resilient 16 × 16 bit MAC unit, implemented using Global Foundries 65 nm technology and ARM standard cells library, is introduced as a case study with 18.26% area overhead and up to 1.5x speedup. At the typical conditions, the maximum frequency of the conventional MAC unit is about 375 MHz while the resilient MAC unit operates correctly at a frequency up to 565 MHz. In case of variations, the resilient MAC unit tolerates induced delays up to 50% of the clock period while keeping its throughput equal to the conventional MAC unit’s maximum throughput. At 375 MHz, the resilient MAC unit is able to scale down the supply voltage from 1.2 V to 1.0 V saving about 29% of the power consumed by the conventional MAC unit. A double-edge-triggered microarchitecture is also introduced to reduce the power consumption extremely by reducing the frequency of the clock tree to the half while preserving the same maximum throughput. This microarchitecture is applied to different ISCAS’89 benchmark circuits in addition to the 16x16 bit MAC unit and the average power reduction of all these circuits is 63.58% while the average area overhead is 31.02%. All these circuits are designed using Global Foundries 65nm technology and ARM standard cells library. Towards the full automation of the ERSUT-based resilient microarchitecture, an ERSUT-based algorithm is introduced in C++ to accelerate the design process of the ERSUT-based microarchitecture. The developed algorithm reduces the design-time efforts dramatically and allows the ERSUT-based microarchitecture to be adopted by larger industrial designs. Depending on the ERSUT-based algorithm, a validation study about applying the ERSUT-based microarchitecture on the MAC unit and different ISCAS’89 benchmark circuits with different complexity weights is introduced. This study shows that 72% of these circuits tolerates more than 14% of their clock periods and 54.5% of these circuits tolerates more than 20% while 27% of these circuits tolerates more than 30%. Consequently, the validation study proves that the ERSUT-based resilient microarchitecture is a valid applicable solution for different circuits with different complexity weights

    Cross-Layer Optimization for Power-Efficient and Robust Digital Circuits and Systems

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    With the increasing digital services demand, performance and power-efficiency become vital requirements for digital circuits and systems. However, the enabling CMOS technology scaling has been facing significant challenges of device uncertainties, such as process, voltage, and temperature variations. To ensure system reliability, worst-case corner assumptions are usually made in each design level. However, the over-pessimistic worst-case margin leads to unnecessary power waste and performance loss as high as 2.2x. Since optimizations are traditionally confined to each specific level, those safe margins can hardly be properly exploited. To tackle the challenge, it is therefore advised in this Ph.D. thesis to perform a cross-layer optimization for digital signal processing circuits and systems, to achieve a global balance of power consumption and output quality. To conclude, the traditional over-pessimistic worst-case approach leads to huge power waste. In contrast, the adaptive voltage scaling approach saves power (25% for the CORDIC application) by providing a just-needed supply voltage. The power saving is maximized (46% for CORDIC) when a more aggressive voltage over-scaling scheme is applied. These sparsely occurred circuit errors produced by aggressive voltage over-scaling are mitigated by higher level error resilient designs. For functions like FFT and CORDIC, smart error mitigation schemes were proposed to enhance reliability (soft-errors and timing-errors, respectively). Applications like Massive MIMO systems are robust against lower level errors, thanks to the intrinsically redundant antennas. This property makes it applicable to embrace digital hardware that trades quality for power savings.Comment: 190 page

    Intelligent Self-Repairable Web Wrappers

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    The amount of information available on the Web grows at an incredible high rate. Systems and procedures devised to extract these data from Web sources already exist, and different approaches and techniques have been investigated during the last years. On the one hand, reliable solutions should provide robust algorithms of Web data mining which could automatically face possible malfunctioning or failures. On the other, in literature there is a lack of solutions about the maintenance of these systems. Procedures that extract Web data may be strictly interconnected with the structure of the data source itself; thus, malfunctioning or acquisition of corrupted data could be caused, for example, by structural modifications of data sources brought by their owners. Nowadays, verification of data integrity and maintenance are mostly manually managed, in order to ensure that these systems work correctly and reliably. In this paper we propose a novel approach to create procedures able to extract data from Web sources -- the so called Web wrappers -- which can face possible malfunctioning caused by modifications of the structure of the data source, and can automatically repair themselves.\u
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