Cross-layer Soft Error Analysis and Mitigation at Nanoscale Technologies

This thesis addresses the challenge of soft error modeling and mitigation in nansoscale technology nodes and pushes the state-of-the-art forward by proposing novel modeling, analyze and mitigation techniques. The proposed soft error sensitivity analysis platform accurately models both error generation and propagation starting from a technology dependent device level simulations all the way to workload dependent application level analysis

ASSESSING AND IMPROVING THE RELIABILITY AND SECURITY OF CIRCUITS AFFECTED BY NATURAL AND INTENTIONAL FAULTS

The reliability and security vulnerability of modern electronic systems have emerged as concerns due to the increasing natural and intentional interferences. Radiation of high-energy charged particles generated from space environment or packaging materials on the substrate of integrated circuits results in natural faults. As the technology scales down, factors such as critical charge, voltage supply, and frequency change tremendously that increase the sensitivity of integrated circuits to natural faults even for systems operating at sea level. An attacker is able to simulate the impact of natural faults and compromise the circuit or cause denial of service. Therefore, instead of utilizing different approaches to counteract the effect of natural and intentional faults, a unified countermeasure is introduced. The unified countermeasure thwarts the impact of both reliability and security threats without paying the price of more area overhead, power consumption, and required time. This thesis first proposes a systematic analysis method to assess the probability of natural faults propagating the circuit and eventually being latched. The second part of this work focuses on the methods to thwart the impact of intentional faults in cryptosystems. We exploit a power-based side-channel analysis method to analyze the effect of the existing fault detection methods for natural faults on fault attack. Countermeasures for different security threats on cryptosystems are investigated separately. Furthermore, a new micro-architecture is proposed to thwart the combination of fault attacks and side-channel attacks, reducing the fault bypass rate and slowing down the key retrieval speed. The third contribution of this thesis is a unified countermeasure to thwart the impact of both natural faults and attacks. The unified countermeasure utilizes dynamically alternated multiple generator polynomials for the cyclic redundancy check (CRC) codec to resist the reverse engineering attack

Fault-based Analysis of Industrial Cyber-Physical Systems

The fourth industrial revolution called Industry 4.0 tries to bridge the gap between traditional Electronic Design Automation (EDA) technologies and the necessity of innovating in many indus- trial fields, e.g., automotive, avionic, and manufacturing. This complex digitalization process in- volves every industrial facility and comprises the transformation of methodologies, techniques, and tools to improve the efficiency of every industrial process. The enhancement of functional safety in Industry 4.0 applications needs to exploit the studies related to model-based and data-driven anal- yses of the deployed Industrial Cyber-Physical System (ICPS). Modeling an ICPS is possible at different abstraction levels, relying on the physical details included in the model and necessary to describe specific system behaviors. However, it is extremely complicated because an ICPS is com- posed of heterogeneous components related to different physical domains, e.g., digital, electrical, and mechanical. In addition, it is also necessary to consider not only nominal behaviors but even faulty behaviors to perform more specific analyses, e.g., predictive maintenance of specific assets. Nevertheless, these faulty data are usually not present or not available directly from the industrial machinery. To overcome these limitations, constructing a virtual model of an ICPS extended with different classes of faults enables the characterization of faulty behaviors of the system influenced by different faults. In literature, these topics are addressed with non-uniformly approaches and with the absence of standardized and automatic methodologies for describing and simulating faults in the different domains composing an ICPS. This thesis attempts to overcome these state-of-the-art gaps by proposing novel methodologies, techniques, and tools to: model and simulate analog and multi-domain systems; abstract low-level models to higher-level behavioral models; and monitor industrial systems based on the Industrial Internet of Things (IIOT) paradigm. Specifically, the proposed contributions involve the exten- sion of state-of-the-art fault injection practices to improve the ICPSs safety, the development of frameworks for safety operations automatization, and the definition of a monitoring framework for ICPSs. Overall, fault injection in analog and digital models is the state of the practice to en- sure functional safety, as mentioned in the ISO 26262 standard specific for the automotive field. Starting from state-of-the-art defects defined for analog descriptions, new defects are proposed to enhance the IEEE P2427 draft standard for analog defect modeling and coverage. Moreover, dif- ferent techniques to abstract a transistor-level model to a behavioral model are proposed to speed up the simulation of faulty circuits. Therefore, unlike the electrical domain, there is no extensive use of fault injection techniques in the mechanical one. Thus, extending the fault injection to the mechanical and thermal fields allows for supporting the definition and evaluation of more reliable safety mechanisms. Hence, a taxonomy of mechanical faults is derived from the electrical domain by exploiting the physical analogies. Furthermore, specific tools are built for automatically instru- menting different descriptions with multi-domain faults. The entire work is proposed as a basis for supporting the creation of increasingly resilient and secure ICPS that need to preserve functional safety in any operating context

From experiment to design – fault characterization and detection in parallel computer systems using computational accelerators

This dissertation summarizes experimental validation and co-design studies conducted to optimize the fault detection capabilities and overheads in hybrid computer systems (e.g., using CPUs and Graphics Processing Units, or GPUs), and consequently to improve the scalability of parallel computer systems using computational accelerators. The experimental validation studies were conducted to help us understand the failure characteristics of CPU-GPU hybrid computer systems under various types of hardware faults. The main characterization targets were faults that are difficult to detect and/or recover from, e.g., faults that cause long latency failures (Ch. 3), faults in dynamically allocated resources (Ch. 4), faults in GPUs (Ch. 5), faults in MPI programs (Ch. 6), and microarchitecture-level faults with specific timing features (Ch. 7). The co-design studies were based on the characterization results. One of the co-designed systems has a set of source-to-source translators that customize and strategically place error detectors in the source code of target GPU programs (Ch. 5). Another co-designed system uses an extension card to learn the normal behavioral and semantic execution patterns of message-passing processes executing on CPUs, and to detect abnormal behaviors of those parallel processes (Ch. 6). The third co-designed system is a co-processor that has a set of new instructions in order to support software-implemented fault detection techniques (Ch. 7). The work described in this dissertation gains more importance because heterogeneous processors have become an essential component of state-of-the-art supercomputers. GPUs were used in three of the five fastest supercomputers that were operating in 2011. Our work included comprehensive fault characterization studies in CPU-GPU hybrid computers. In CPUs, we monitored the target systems for a long period of time after injecting faults (a temporally comprehensive experiment), and injected faults into various types of program states that included dynamically allocated memory (to be spatially comprehensive). In GPUs, we used fault injection studies to demonstrate the importance of detecting silent data corruption (SDC) errors that are mainly due to the lack of fine-grained protections and the massive use of fault-insensitive data. This dissertation also presents transparent fault tolerance frameworks and techniques that are directly applicable to hybrid computers built using only commercial off-the-shelf hardware components. This dissertation shows that by developing understanding of the failure characteristics and error propagation paths of target programs, we were able to create fault tolerance frameworks and techniques that can quickly detect and recover from hardware faults with low performance and hardware overheads

Design for prognostics and security in field programmable gate arrays (FPGAs).

There is an evolutionary progression of Field Programmable Gate Arrays (FPGAs) toward more complex and high power density architectures such as Systems-on- Chip (SoC) and Adaptive Compute Acceleration Platforms (ACAP). Primarily, this is attributable to the continual transistor miniaturisation and more innovative and efficient IC manufacturing processes. Concurrently, degradation mechanism of Bias Temperature Instability (BTI) has become more pronounced with respect to its ageing impact. It could weaken the reliability of VLSI devices, FPGAs in particular due to their run-time reconfigurability. At the same time, vulnerability of FPGAs to device-level attacks in the increasing cyber and hardware threat environment is also quadrupling as the susceptible reliability realm opens door for the rogue elements to intervene. Insertion of highly stealthy and malicious circuitry, called hardware Trojans, in FPGAs is one of such malicious interventions. On the one hand where such attacks/interventions adversely affect the security ambit of these devices, they also undermine their reliability substantially. Hitherto, the security and reliability are treated as two separate entities impacting the FPGA health. This has resulted in fragmented solutions that do not reflect the true state of the FPGA operational and functional readiness, thereby making them even more prone to hardware attacks. The recent episodes of Spectre and Meltdown vulnerabilities are some of the key examples. This research addresses these concerns by adopting an integrated approach and investigating the FPGA security and reliability as two inter-dependent entities with an additional dimension of health estimation/ prognostics. The design and implementation of a small footprint frequency and threshold voltage-shift detection sensor, a novel hardware Trojan, and an online transistor dynamic scaling circuitry present a viable FPGA security scheme that helps build a strong microarchitectural level defence against unscrupulous hardware attacks. Augmented with an efficient Kernel-based learning technique for FPGA health estimation/prognostics, the optimal integrated solution proves to be more dependable and trustworthy than the prevalent disjointed approach.Samie, Mohammad (Associate)PhD in Transport System

Performance assessment of real-time data management on wireless sensor networks

Technological advances in recent years have allowed the maturity of Wireless Sensor Networks (WSNs), which aim at performing environmental monitoring and data collection. This sort of network is composed of hundreds, thousands or probably even millions of tiny smart computers known as wireless sensor nodes, which may be battery powered, equipped with sensors, a radio transceiver, a Central Processing Unit (CPU) and some memory. However due to the small size and the requirements of low-cost nodes, these sensor node resources such as processing power, storage and especially energy are very limited. Once the sensors perform their measurements from the environment, the problem of data storing and querying arises. In fact, the sensors have restricted storage capacity and the on-going interaction between sensors and environment results huge amounts of data. Techniques for data storage and query in WSN can be based on either external storage or local storage. The external storage, called warehousing approach, is a centralized system on which the data gathered by the sensors are periodically sent to a central database server where user queries are processed. The local storage, in the other hand called distributed approach, exploits the capabilities of sensors calculation and the sensors act as local databases. The data is stored in a central database server and in the devices themselves, enabling one to query both. The WSNs are used in a wide variety of applications, which may perform certain operations on collected sensor data. However, for certain applications, such as real-time applications, the sensor data must closely reflect the current state of the targeted environment. However, the environment changes constantly and the data is collected in discreet moments of time. As such, the collected data has a temporal validity, and as time advances, it becomes less accurate, until it does not reflect the state of the environment any longer. Thus, these applications must query and analyze the data in a bounded time in order to make decisions and to react efficiently, such as industrial automation, aviation, sensors network, and so on. In this context, the design of efficient real-time data management solutions is necessary to deal with both time constraints and energy consumption. This thesis studies the real-time data management techniques for WSNs. It particularly it focuses on the study of the challenges in handling real-time data storage and query for WSNs and on the efficient real-time data management solutions for WSNs. First, the main specifications of real-time data management are identified and the available real-time data management solutions for WSNs in the literature are presented. Secondly, in order to provide an energy-efficient real-time data management solution, the techniques used to manage data and queries in WSNs based on the distributed paradigm are deeply studied. In fact, many research works argue that the distributed approach is the most energy-efficient way of managing data and queries in WSNs, instead of performing the warehousing. In addition, this approach can provide quasi real-time query processing because the most current data will be retrieved from the network. Thirdly, based on these two studies and considering the complexity of developing, testing, and debugging this kind of complex system, a model for a simulation framework of the real-time databases management on WSN that uses a distributed approach and its implementation are proposed. This will help to explore various solutions of real-time database techniques on WSNs before deployment for economizing money and time. Moreover, one may improve the proposed model by adding the simulation of protocols or place part of this simulator on another available simulator. For validating the model, a case study considering real-time constraints as well as energy constraints is discussed. Fourth, a new architecture that combines statistical modeling techniques with the distributed approach and a query processing algorithm to optimize the real-time user query processing are proposed. This combination allows performing a query processing algorithm based on admission control that uses the error tolerance and the probabilistic confidence interval as admission parameters. The experiments based on real world data sets as well as synthetic data sets demonstrate that the proposed solution optimizes the real-time query processing to save more energy while meeting low latency.Fundação para a Ciência e Tecnologi

Robust design of deep-submicron digital circuits

Avec l'augmentation de la probabilité de fautes dans les circuits numériques, les systèmes développés pour les environnements critiques comme les centrales nucléaires, les avions et les applications spatiales doivent être certifies selon des normes industrielles. Cette thèse est un résultat d'une cooperation CIFRE entre l'entreprise Électricité de France (EDF) R&D et Télécom Paristech. EDF est l'un des plus gros producteurs d'énergie au monde et possède de nombreuses centrales nucléaires. Les systèmes de contrôle-commande utilisé dans les centrales sont basés sur des dispositifs électroniques, qui doivent être certifiés selon des normes industrielles comme la CEI 62566, la CEI 60987 et la CEI 61513 à cause de la criticité de l'environnement nucléaire. En particulier, l'utilisation des dispositifs programmables comme les FPGAs peut être considérée comme un défi du fait que la fonctionnalité du dispositif est définie par le concepteur seulement après sa conception physique. Le travail présenté dans ce mémoire porte sur la conception de nouvelles méthodes d'analyse de la fiabilité aussi bien que des méthodes d'amélioration de la fiabilité d'un circuit numérique.The design of circuits to operate at critical environments, such as those used in control-command systems at nuclear power plants, is becoming a great challenge with the technology scaling. These circuits have to pass through a number of tests and analysis procedures in order to be qualified to operate. In case of nuclear power plants, safety is considered as a very high priority constraint, and circuits designed to operate under such critical environment must be in accordance with several technical standards such as the IEC 62566, the IEC 60987, and the IEC 61513. In such standards, reliability is treated as a main consideration, and methods to analyze and improve the circuit reliability are highly required. The present dissertation introduces some methods to analyze and to improve the reliability of circuits in order to facilitate their qualification according to the aforementioned technical standards. Concerning reliability analysis, we first present a fault-injection based tool used to assess the reliability of digital circuits. Next, we introduce a method to evaluate the reliability of circuits taking into account the ability of a given application to tolerate errors. Concerning reliability improvement techniques, first two different strategies to selectively harden a circuit are proposed. Finally, a method to automatically partition a TMR design based on a given reliability requirement is introduced.PARIS-Télécom ParisTech (751132302) / SudocSudocFranceF

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

Signal transduction and contextual modulation in the human visual system

The transduction of luminance contrast is nonlinear. As contrast increases, responses first accelerate, and then saturate. This acceleration is thought to be responsible for the “dipper effect”: the improvement in stimulus sensitivity at low absolute contrasts. Moreover, a stimulus that cannot provoke a neuronal response can still modulate a neuron’s response to its preferred stimuli. Recent evidence suggests that similar computations exist in more complex visual parameter spaces. Furthermore, there is indication that the divisive inhibitory mechanisms of the brain are affected in aging. In this thesis, I present three experiments that explored these possibilities. My first experiment investigated reports that surround suppression of contrast strengthens with age, implying disruption of excitatory/inhibitory balance. I suspected that previous reports may reflect contributions from overlay masking, a distinct form of suppression. Using stimuli that preclude overlay masking, I found surround suppression to be similar in younger and older observers, suggesting that spatial suppression is stable with age. I also reported a novel finding of untuned suprathreshold suppression in central vision. My second experiment explored whether the “dipper effect” can be found in the mid-level perception of global form. I also expanded on reports of enhanced sensitivity to concentric and radial form. By manipulating the saliency of the global form percept elicited by Glass patterns, I reported a dipper effect that was similar across the pattern axes I examined. In my third experiment, using electroencephalography, I investigated whether this global form “dipper effect” is predicted by neuronal responses. At ventral electrodes, I found evidence for a transducer that would produce a dipper effect, though the level of global form for which it predicted peak sensitivity differed from psychophysical predictions. I reasoned that this discrepancy is likely due to methodological limitations, but also provided an explanation from attentional modulation and gain control

The Fifth NASA Symposium on VLSI Design

The fifth annual NASA Symposium on VLSI Design had 13 sessions including Radiation Effects, Architectures, Mixed Signal, Design Techniques, Fault Testing, Synthesis, Signal Processing, and other Featured Presentations. The symposium provides insights into developments in VLSI and digital systems which can be used to increase data systems performance. The presentations share insights into next generation advances that will serve as a basis for future VLSI design