Proposal of an Adaptive Fault Tolerance Mechanism to Tolerate Intermittent Faults in RAM

[EN] Due to transistor shrinking, intermittent faults are a major concern in current digital systems. This work presents an adaptive fault tolerance mechanism based on error correction codes (ECC), able to modify its behavior when the error conditions change without increasing the redundancy. As a case example, we have designed a mechanism that can detect intermittent faults and swap from an initial generic ECC to a specific ECC capable of tolerating one intermittent fault. We have inserted the mechanism in the memory system of a 32-bit RISC processor and validated it by using VHDL simulation-based fault injection. We have used two (39, 32) codes: a single error correction-double error detection (SEC-DED) and a code developed by our research group, called EPB3932, capable of correcting single errors and double and triple adjacent errors that include a bit previously tagged as error-prone. The results of injecting transient, intermittent, and combinations of intermittent and transient faults show that the proposed mechanism works properly. As an example, the percentage of failures and latent errors is 0% when injecting a triple adjacent fault after an intermittent stuck-at fault. We have synthesized the adaptive fault tolerance mechanism proposed in two types of FPGAs: non-reconfigurable and partially reconfigurable. In both cases, the overhead introduced is affordable in terms of hardware, time and power consumption.This research was supported in part by the Spanish Government, project TIN2016-81,075-R, and by Primeros Proyectos de Investigacion (PAID-06-18), Vicerrectorado de Investigacion, Innovacion y Transferencia de la Universitat Politecnica de Valencia (UPV), project 20190032.Baraza Calvo, JC.; Gracia-Morán, J.; Saiz-Adalid, L.; Gil Tomás, DA.; Gil, P. (2020). Proposal of an Adaptive Fault Tolerance Mechanism to Tolerate Intermittent Faults in RAM. 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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

Energy vs. Reliability Trade-offs Exploration in Biomedical Ultra-Low Power Devices

State-of-the-art wearable devices such as embedded biomedical monitoring systems apply voltage scaling to lower as much as possible their energy consumption and achieve longer battery lifetimes. While embedded memories often rely on Error Correction Codes (ECC) for error protection, in this paper we explore how the characteristics of biomedical applications can be exploited to develop new techniques with lower power overhead. We then introduce the Dynamic eRror compEnsation And Masking (DREAM) technique, that provides partial memory protection with less area and power overheads than ECC. Different tradeoffs between the error correction ability of the techniques and their energy consumption are examined to conclude that, when properly applied, DREAM consumes 21% less energy than a traditional ECC with Single Error Correction and Double Error Detection (SEC/DED) capabilities

Towards Data Reliable, Low-Power, and Repairable Resistive Random Access Memories

A series of breakthroughs in memristive devices have demonstrated the potential of memristor arrays to serve as next generation resistive random access memories (ReRAM), which are fast, low-power, ultra-dense, and non-volatile. However, memristors' unique device characteristics also make them prone to several sources of error. Owing to the stochastic filamentary nature of memristive devices, various recoverable errors can affect the data reliability of a ReRAM. Permanent device failures further limit the lifetime of a ReRAM. This dissertation developed low-power solutions for more reliable and longer-enduring ReRAM systems. In this thesis, we first look into a data reliability issue known as write disturbance. Writing into a memristor in a crossbar could disturb the stored values in other memristors that are on the same memory line as the target cell. Such disturbance is accumulative over time which may lead to complete data corruption. To address this problem, we propose the use of two regular memristors on each word to keep track of the disturbance accumulation and trigger a refresh to restore the weakened data, once it becomes necessary. We also investigate the considerable variation in the write-time characteristics of individual memristors. With such variation, conventional fixed-pulse write schemes not only waste significant energy, but also cannot guarantee reliable completion of the write operations. We address such variation by proposing an adaptive write scheme that adjusts the width of the write pulses for each memristor. Our scheme embeds an online monitor to detect the completion of a write operation and takes into account the parasitic effect of line-shared devices in access-transistor-free memristive arrays. We further investigate the use of this method to shorten the test time of memory march algorithms by eliminating the need of a verifying read right after a write, which is commonly employed in the test sequences of march algorithms.Finally, we propose a novel mechanism to extend the lifetime of a ReRAM by protecting it against hard errors through the exploitation of a unique feature of bipolar memristive devices. Our solution proposes an unorthodox use of complementary resistive switches (a particular implementation of memristive devices) to provide an ``in-place spare'' for each memory cell at negligible extra cost. The in-place spares are then utilized by a repair scheme to repair memristive devices that have failed at a stuck-at-ON state at a page-level granularity. Furthermore, we explore the use of in-place spares in lieu of other memory reliability and yield enhancement solutions, such as error correction codes (ECC) and spare rows. We demonstrate that with the in-place spares, we can yield the same lifetime as a baseline ReRAM with either significantly fewer spare rows or a lighter-weight ECC, both of which can save on energy consumption and area

Methodologies and Toolflows for the Predictable Design of Reliable and Low-Power NoCs

There is today the unmistakable need to evolve design methodologies and tool ows for Network-on-Chip based embedded systems. In particular, the quest for low-power requirements is nowadays a more-than-ever urgent dilemma. Modern circuits feature billion of transistors, and neither power management techniques nor batteries capacity are able to endure the increasingly higher integration capability of digital devices. Besides, power concerns come together with modern nanoscale silicon technology design issues. On one hand, system failure rates are expected to increase exponentially at every technology node when integrated circuit wear-out failure mechanisms are not compensated for. However, error detection and/or correction mechanisms have a non-negligible impact on the network power. On the other hand, to meet the stringent time-to-market deadlines, the design cycle of such a distributed and heterogeneous architecture must not be prolonged by unnecessary design iterations. Overall, there is a clear need to better discriminate reliability strategies and interconnect topology solutions upfront, by ranking designs based on power metric. In this thesis, we tackle this challenge by proposing power-aware design technologies. Finally, we take into account the most aggressive and disruptive methodology for embedded systems with ultra-low power constraints, by migrating NoC basic building blocks to asynchronous (or clockless) design style. We deal with this challenge delivering a standard cell design methodology and mainstream CAD tool ows, in this way partially relaxing the requirement of using asynchronous blocks only as hard macros

Dependable Embedded Systems

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

Concertina: Squeezing in cache content to operate at near-threshold voltage

© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Scaling supply voltage to values near the threshold voltage allows a dramatic decrease in the power consumption of processors; however, the lower the voltage, the higher the sensitivity to process variation, and, hence, the lower the reliability. Large SRAM structures, like the last-level cache (LLC), are extremely vulnerable to process variation because they are aggressively sized to satisfy high density requirements. In this paper, we propose Concertina, an LLC designed to enable reliable operation at low voltages with conventional SRAM cells. Based on the observation that for many applications the LLC contains large amounts of null data, Concertina compresses cache blocks in order that they can be allocated to cache entries with faulty cells, enabling use of 100 percent of the LLC capacity. To distribute blocks among cache entries, Concertina implements a compression- and fault-aware insertion/replacement policy that reduces the LLC miss rate. Concertina reaches the performance of an ideal system implementing an LLC that does not suffer from parameter variation with a modest storage overhead. Specifically, performance degrades by less than 2 percent, even when using small SRAM cells, which implies over 90 percent of cache entries having defective cells, and this represents a notable improvement on previously proposed techniques.Peer ReviewedPostprint (author's final draft

Hardware / Software Architectural and Technological Exploration for Energy-Efficient and Reliable Biomedical Devices

Nowadays, the ubiquity of smart appliances in our everyday lives is increasingly strengthening the links between humans and machines. Beyond making our lives easier and more convenient, smart devices are now playing an important role in personalized healthcare delivery. This technological breakthrough is particularly relevant in a world where population aging and unhealthy habits have made non-communicable diseases the first leading cause of death worldwide according to international public health organizations. In this context, smart health monitoring systems termed Wireless Body Sensor Nodes (WBSNs), represent a paradigm shift in the healthcare landscape by greatly lowering the cost of long-term monitoring of chronic diseases, as well as improving patients' lifestyles. WBSNs are able to autonomously acquire biological signals and embed on-node Digital Signal Processing (DSP) capabilities to deliver clinically-accurate health diagnoses in real-time, even outside of a hospital environment. Energy efficiency and reliability are fundamental requirements for WBSNs, since they must operate for extended periods of time, while relying on compact batteries. These constraints, in turn, impose carefully designed hardware and software architectures for hosting the execution of complex biomedical applications. In this thesis, I develop and explore novel solutions at the architectural and technological level of the integrated circuit design domain, to enhance the energy efficiency and reliability of current WBSNs. Firstly, following a top-down approach driven by the characteristics of biomedical algorithms, I perform an architectural exploration of a heterogeneous and reconfigurable computing platform devoted to bio-signal analysis. By interfacing a shared Coarse-Grained Reconfigurable Array (CGRA) accelerator, this domain-specific platform can achieve higher performance and energy savings, beyond the capabilities offered by a baseline multi-processor system. More precisely, I propose three CGRA architectures, each contributing differently to the maximization of the application parallelization. The proposed Single, Multi and Interleaved-Datapath CGRA designs allow the developed platform to achieve substantial energy savings of up to 37%, when executing complex biomedical applications, with respect to a multi-core-only platform. Secondly, I investigate how the modeling of technology reliability issues in logic and memory components can be exploited to adequately adjust the frequency and supply voltage of a circuit, with the aim of optimizing its computing performance and energy efficiency. To this end, I propose a novel framework for workload-dependent Bias Temperature Instability (BTI) impact analysis on biomedical application results quality. Remarkably, the framework is able to determine the range of safe circuit operating frequencies without introducing worst-case guard bands. Experiments highlight the possibility to safely raise the frequency up to 101% above the maximum obtained with the classical static timing analysis. Finally, through the study of several well-known biomedical algorithms, I propose an approach allowing energy savings by dynamically and unequally protecting an under-powered data memory in a new way compared to regular error protection schemes. This solution relies on the Dynamic eRror compEnsation And Masking (DREAM) technique that reduces by approximately 21% the energy consumed by traditional error correction codes

Fault and Defect Tolerant Computer Architectures: Reliable Computing With Unreliable Devices

This research addresses design of a reliable computer from unreliable device technologies. A system architecture is developed for a fault and defect tolerant (FDT) computer. Trade-offs between different techniques are studied and yield and hardware cost models are developed. Fault and defect tolerant designs are created for the processor and the cache memory. Simulation results for the content-addressable memory (CAM)-based cache show 90% yield with device failure probabilities of 3 x 10(-6), three orders of magnitude better than non fault tolerant caches of the same size. The entire processor achieves 70% yield with device failure probabilities exceeding 10(-6). The required hardware redundancy is approximately 15 times that of a non-fault tolerant design. While larger than current FT designs, this architecture allows the use of devices much more likely to fail than silicon CMOS. As part of model development, an improved model is derived for NAND Multiplexing. The model is the first accurate model for small and medium amounts of redundancy. Previous models are extended to account for dependence between the inputs and produce more accurate results