Combined Time and Information Redundancy for SEU-Tolerance in Energy-Efficient Real-Time Systems

Recently the trade-off between energy consumption and fault-tolerance in real-time systems has been highlighted. These works have focused on dynamic voltage scaling (DVS) to reduce dynamic energy dissipation and on time redundancy to achieve transient-fault tolerance. While the time redundancy technique exploits the available slack time to increase the fault-tolerance by performing recovery executions, DVS exploits slack time to save energy. Therefore we believe there is a resource conflict between the time-redundancy technique and DVS. The first aim of this paper is to propose the usage of information redundancy to solve this problem. We demonstrate through analytical and experimental studies that it is possible to achieve both higher transient fault-tolerance (tolerance to single event upsets (SEU)) and less energy using a combination of information and time redundancy when compared with using time redundancy alone. The second aim of this paper is to analyze the interplay of transient-fault tolerance (SEU-tolerance) and adaptive body biasing (ABB) used to reduce static leakage energy, which has not been addressed in previous studies. We show that the same technique (i.e. the combination of time and information redundancy) is applicable to ABB-enabled systems and provides more advantages than time redundancy alone

Low-energy standby-sparing for hard real-time systems

Time-redundancy techniques are commonly used in real-time systems to achieve fault tolerance without incurring high energy overhead. However, reliability requirements of hard real-time systems that are used in safety-critical applications are so stringent that time-redundancy techniques are sometimes unable to achieve them. Standby sparing as a hardwareredundancy technique can be used to meet high reliability requirements of safety-critical applications. However, conventional standby-sparing techniques are not suitable for lowenergy hard real-time systems as they either impose considerable energy overheads or are not proper for hard timing constraints. In this paper we provide a technique to use standby sparing for hard real-time systems with limited energy budgets. The principal contribution of this work is an online energymanagement technique which is specifically developed for standby-sparing systems that are used in hard real-time applications. This technique operates at runtime and exploits dynamic slacks to reduce the energy consumption while guaranteeing hard deadlines. We compared the low-energy standby-sparing (LESS) system with a low-energy timeredundancy system (from a previous work). The results show that for relaxed time constraints, the LESS system is more reliable and provides about 26% energy saving as compared to the time-redundancy system. For tight deadlines when the timeredundancy system is not sufficiently reliable (for safety-critical application), the LESS system preserves its reliability but with about 49% more energy consumptio

Timing-Error Tolerance Techniques for Low-Power DSP: Filters and Transforms

Low-power Digital Signal Processing (DSP) circuits are critical to commercial System-on-Chip design for battery powered devices. Dynamic Voltage Scaling (DVS) of digital circuits can reclaim worst-case supply voltage margins for delay variation, reducing power consumption. However, removing static margins without compromising robustness is tremendously challenging, especially in an era of escalating reliability concerns due to continued process scaling. The Razor DVS scheme addresses these concerns, by ensuring robustness using explicit timing-error detection and correction circuits. Nonetheless, the design of low-complexity and low-power error correction is often challenging. In this thesis, the Razor framework is applied to fixed-precision DSP filters and transforms. The inherent error tolerance of many DSP algorithms is exploited to achieve very low-overhead error correction. Novel error correction schemes for DSP datapaths are proposed, with very low-overhead circuit realisations. Two new approximate error correction approaches are proposed. The first is based on an adapted sum-of-products form that prevents errors in intermediate results reaching the output, while the second approach forces errors to occur only in less significant bits of each result by shaping the critical path distribution. A third approach is described that achieves exact error correction using time borrowing techniques on critical paths. Unlike previously published approaches, all three proposed are suitable for high clock frequency implementations, as demonstrated with fully placed and routed FIR, FFT and DCT implementations in 90nm and 32nm CMOS. Design issues and theoretical modelling are presented for each approach, along with SPICE simulation results demonstrating power savings of 21 – 29%. Finally, the design of a baseband transmitter in 32nm CMOS for the Spectrally Efficient FDM (SEFDM) system is presented. SEFDM systems offer bandwidth savings compared to Orthogonal FDM (OFDM), at the cost of increased complexity and power consumption, which is quantified with the first VLSI architecture

inSense: A Variation and Fault Tolerant Architecture for Nanoscale Devices

Transistor technology scaling has been the driving force in improving the size, speed, and power consumption of digital systems. As devices approach atomic size, however, their reliability and performance are increasingly compromised due to reduced noise margins, difficulties in fabrication, and emergent nano-scale phenomena. Scaled CMOS devices, in particular, suffer from process variations such as random dopant fluctuation (RDF) and line edge roughness (LER), transistor degradation mechanisms such as negative-bias temperature instability (NBTI) and hot-carrier injection (HCI), and increased sensitivity to single event upsets (SEUs). Consequently, future devices may exhibit reduced performance, diminished lifetimes, and poor reliability. This research proposes a variation and fault tolerant architecture, the inSense architecture, as a circuit-level solution to the problems induced by the aforementioned phenomena. The inSense architecture entails augmenting circuits with introspective and sensory capabilities which are able to dynamically detect and compensate for process variations, transistor degradation, and soft errors. This approach creates ``smart\u27\u27 circuits able to function despite the use of unreliable devices and is applicable to current CMOS technology as well as next-generation devices using new materials and structures. Furthermore, this work presents an automated prototype implementation of the inSense architecture targeted to CMOS devices and is evaluated via implementation in ISCAS \u2785 benchmark circuits. The automated prototype implementation is functionally verified and characterized: it is found that error detection capability (with error windows from $\approx$30-400ps) can be added for less than 2\% area overhead for circuits of non-trivial complexity. Single event transient (SET) detection capability (configurable with target set-points) is found to be functional, although it generally tracks the standard DMR implementation with respect to overheads

Dynamic Partial Reconfiguration for Dependable Systems

Moore’s law has served as goal and motivation for consumer electronics manufacturers in the last decades. The results in terms of processing power increase in the consumer electronics devices have been mainly achieved due to cost reduction and technology shrinking. However, reducing physical geometries mainly affects the electronic devices’ dependability, making them more sensitive to soft-errors like Single Event Transient (SET) of Single Event Upset (SEU) and hard (permanent) faults, e.g. due to aging effects. Accordingly, safety critical systems often rely on the adoption of old technology nodes, even if they introduce longer design time w.r.t. consumer electronics. In fact, functional safety requirements are increasingly pushing industry in developing innovative methodologies to design high-dependable systems with the required diagnostic coverage. On the other hand commercial off-the-shelf (COTS) devices adoption began to be considered for safety-related systems due to real-time requirements, the need for the implementation of computationally hungry algorithms and lower design costs. In this field FPGA market share is constantly increased, thanks to their flexibility and low non-recurrent engineering costs, making them suitable for a set of safety critical applications with low production volumes. The works presented in this thesis tries to face new dependability issues in modern reconfigurable systems, exploiting their special features to take proper counteractions with low impacton performances, namely Dynamic Partial Reconfiguration

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

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

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