Software Canaries: Software-based Path Delay Fault Testing for Variation-aware Energy-efficient Design

ABSTRACT Software-based path delay fault testing (SPDFT) has been used to identify faulty chips that cannot meet timing constraints due to gross delay defects. In this paper, we propose using SPDFT for a new purpose -aggressively selecting the operating point of a variation-affected design. In order to use SPDFT for this purpose, test routines must provide high coverage of potentially-critical paths and must have low dynamic performance overhead. We describe how to apply SPDFT for selecting an energy-efficient operating point for a variation-affected processor and demonstrate that our test routines achieve ample coverage and low overhead

Integrated Circuit Design for Radiation Sensing and Hardening.

Beyond the 1950s, integrated circuits have been widely used in a number of electronic devices surrounding people’s lives. In addition to computing electronics, scientific and medical equipment have also been undergone a metamorphosis, especially in radiation related fields where compact and precision radiation detection systems for nuclear power plants, positron emission tomography (PET), and radiation hardened by design (RHBD) circuits for space applications fabricated in advanced manufacturing technologies are exposed to the non-negligible probability of soft errors by radiation impact events. The integrated circuit design for radiation measurement equipment not only leads to numerous advantages on size and power consumption, but also raises many challenges regarding the speed and noise to replace conventional design modalities. This thesis presents solutions to front-end receiver designs for radiation sensors as well as an error detection and correction method to microprocessor designs under the condition of soft error occurrence. For the first preamplifier design, a novel technique that enhances the bandwidth and suppresses the input current noise by using two inductors is discussed. With the dual-inductor TIA signal processing configuration, one can reduce the fabrication cost, the area overhead, and the power consumption in a fast readout package. The second front-end receiver is a novel detector capacitance compensation technique by using the Miller effect. The fabricated CSA exhibits minimal variation in the pulse shape as the detector capacitance is increased. Lastly, a modified D flip-flop is discussed that is called Razor-Lite using charge-sharing at internal nodes to provide a compact EDAC design for modern well-balanced processors and RHBD against soft errors by SEE.PhDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111548/1/iykwon_1.pd

Timing speculation and adaptive reliable overclocking techniques for aggressive computer systems

Computers have changed our lives beyond our own imagination in the past several decades. The continued and progressive advancements in VLSI technology and numerous micro-architectural innovations have played a key role in the design of spectacular low-cost high performance computing systems that have become omnipresent in today\u27s technology driven world. Performance and dependability have become key concerns as these ubiquitous computing machines continue to drive our everyday life. Every application has unique demands, as they run in diverse operating environments. Dependable, aggressive and adaptive systems improve efficiency in terms of speed, reliability and energy consumption. Traditional computing systems run at a fixed clock frequency, which is determined by taking into account the worst-case timing paths, operating conditions, and process variations. Timing speculation based reliable overclocking advocates going beyond worst-case limits to achieve best performance while not avoiding, but detecting and correcting a modest number of timing errors. The success of this design methodology relies on the fact that timing critical paths are rarely exercised in a design, and typical execution happens much faster than the timing requirements dictated by worst-case design methodology. Better-than-worst-case design methodology is advocated by several recent research pursuits, which exploit dependability techniques to enhance computer system performance. In this dissertation, we address different aspects of timing speculation based adaptive reliable overclocking schemes, and evaluate their role in the design of low-cost, high performance, energy efficient and dependable systems. We visualize various control knobs in the design that can be favorably controlled to ensure different design targets. As part of this research, we extend the SPRIT3E, or Superscalar PeRformance Improvement Through Tolerating Timing Errors, framework, and characterize the extent of application dependent performance acceleration achievable in superscalar processors by scrutinizing the various parameters that impact the operation beyond worst-case limits. We study the limitations imposed by short-path constraints on our technique, and present ways to exploit them to maximize performance gains. We analyze the sensitivity of our technique\u27s adaptiveness by exploring the necessary hardware requirements for dynamic overclocking schemes. Experimental analysis based on SPEC2000 benchmarks running on a SimpleScalar Alpha processor simulator, augmented with error rate data obtained from hardware simulations of a superscalar processor, are presented. Even though reliable overclocking guarantees functional correctness, it leads to higher power consumption. As a consequence, reliable overclocking without considering on-chip temperatures will bring down the lifetime reliability of the chip. In this thesis, we analyze how reliable overclocking impacts the on-chip temperature of a microprocessor and evaluate the effects of overheating, due to such reliable dynamic frequency tuning mechanisms, on the lifetime reliability of these systems. We then evaluate the effect of performing thermal throttling, a technique that clamps the on-chip temperature below a predefined value, on system performance and reliability. Our study shows that a reliably overclocked system with dynamic thermal management achieves 25% performance improvement, while lasting for 14 years when being operated within 353K. Over the past five decades, technology scaling, as predicted by Moore\u27s law, has been the bedrock of semiconductor technology evolution. The continued downscaling of CMOS technology to deep sub-micron gate lengths has been the primary reason for its dominance in today\u27s omnipresent silicon microchips. Even as the transition to the next technology node is indispensable, the initial cost and time associated in doing so presents a non-level playing field for the competitors in the semiconductor business. As part of this thesis, we evaluate the capability of speculative reliable overclocking mechanisms to maximize performance at a given technology level. We evaluate its competitiveness when compared to technology scaling, in terms of performance, power consumption, energy and energy delay product. We present a comprehensive comparison for integer and floating point SPEC2000 benchmarks running on a simulated Alpha processor at three different technology nodes in normal and enhanced modes. Our results suggest that adopting reliable overclocking strategies will help skip a technology node altogether, or be competitive in the market, while porting to the next technology node. Reliability has become a serious concern as systems embrace nanometer technologies. In this dissertation, we propose a novel fault tolerant aggressive system that combines soft error protection and timing error tolerance. We replicate both the pipeline registers and the pipeline stage combinational logic. The replicated logic receives its inputs from the primary pipeline registers while writing its output to the replicated pipeline registers. The organization of redundancy in the proposed Conjoined Pipeline system supports overclocking, provides concurrent error detection and recovery capability for soft errors, intermittent faults and timing errors, and flags permanent silicon defects. The fast recovery process requires no checkpointing and takes three cycles. Back annotated post-layout gate-level timing simulations, using 45nm technology, of a conjoined two-stage arithmetic pipeline and a conjoined five-stage DLX pipeline processor, with forwarding logic, show that our approach, even under a severe fault injection campaign, achieves near 100% fault coverage and an average performance improvement of about 20%, when dynamically overclocked

Online Timing Slack Measurement and its Application in Field-Programmable Gate Arrays

Reliability, power consumption and timing performance are key concerns for today's integrated circuits. Measurement techniques capable of quantifying the timing characteristics of a circuit, while it is operating, facilitate a range of benefits. Delay variation due to environmental and operational conditions, and degradation can be monitored by tracking changes in timing performance. Using the measurements in a closed-loop to control power supply voltage or clock frequency allows for the reduction of timing safety margins, leading to improvements in power consumption or throughput performance through the exploitation of better-than worst-case operation. This thesis describes a novel online timing slack measurement method which can directly measure the timing performance of a circuit, accurately and with minimal overhead. Enhancements allow for the improvement of absolute accuracy and resolution. A compilation flow is reported that can automatically instrument arbitrary circuits on FPGAs with the measurement circuitry. On its own this measurement method is able to track the "health" of an integrated circuit, from commissioning through its lifetime, warning of impending failure or instigating pre-emptive degradation mitigation techniques. The use of the measurement method in a closed-loop dynamic voltage and frequency scaling scheme has been demonstrated, achieving significant improvements in power consumption and throughput performance.Open Acces

Programmable stochastic processors

As traditional approaches for reducing power in microprocessors are being exhausted, extreme power challenges call for unconventional approaches to power reduction. Recent research has shown substantial promise for application-specific stochastic computing, i.e., computing that exploits application error tolerance to enable careful relaxation of correctness guarantees provided by hardware in order to reduce power. This dissertation explores the feasibility, challenges, and potential benefits of stochastic computing in the context of programmable general purpose processors. Specifically, the dissertation describes design-level techniques that minimize the power of a processor for a non-zero error rate or allow a processor to fail gracefully when operated over a range of non-zero error rates. It presents microarchitectural design principles that allow a processor to trade off reliability and energy more efficiently to minimize energy when exploiting error resilience. It demonstrates the benefit of using compiler optimizations that optimize a binary to enable more energy savings when operating at a non-zero error rate. It also demonstrates significant benefits for a programmable stochastic processor prototype that improves energy efficiency by carefully relaxing correctness and exposing errors in applications running on a commodity processor. This dissertation on programmable stochastic processors conclusively shows that the architecture and design of processors and applications should be approached differently in scenarios where errors are allowed to be exposed from the hardware to higher levels of the compute stack. Significant energy benefits are demonstrated for design-, architecture-, compiler-, and application-level optimizations for general purpose programmable stochastic processors

Algorithmic approaches to enhancing and exploiting application-level error tolerance

As late-CMOS process scaling leads to increasingly variable circuits/logic and as most post-CMOS technologies in sight appear to have largely stochastic characteristics, hardware reliability has become a first-order design concern. To make matters worse, emerging computing systems are becoming increasingly power constrained. Traditional hardware/software approaches are likely to be impractical for these power constrained systems due to their heavy reliance on redundant, worstcase, and conservative designs. The primary goal of this research has been to investigate how we can leverage inherent application and algorithm characteristics (e.g. natural error resilience, spatial and temporal reuse, and fault containment) to build more efficient robust systems. This dissertation research describes algorithmic approaches that leverage application and algorithm-awareness for building such systems. These approaches include (a) application-specific techniques for low-overhead fault detection, (b) an algorithmic approach for error correction using localization, (c) selection of scientific computing solver schemes to leverage application-level error resilience, and (d) a numerical optimization-based methodology for converting applications into a more error tolerant form. This dissertation shows that application and algorithm-awareness can significantly increase the robustness of computing systems, while also reducing the cost of meeting reliability targets