Este trabalho mostra a comparação dos efeitos das falhas provocadas pelos Single-Event Effects em dispositivos 28nm FDSOI, 28nm FDSOI High-K e 32nm Bulk CMOS e células de memória 6T SRAM feitas com estes dispositivos. Para conseguir isso, foram usadas ferramentas TCAD para simular falhas transientes devido a impacto de íons pesados a nível dispositivo e nível circuito. As simulações neste ambiente tem como vantagem a simulação dos fatos e mecanismos que produz as falhas transientes e seus efeitos nos dispositivos, além de também servir para projetar virtualmente estes dispositivos e caraterizar eles para estas simulações. Neste caso, foram projetados três dispositivos para simulação: um transistor NMOS de 32nm Bulk, um transistor NMOS de 28nm FDSOI e um transistor NMOS de 28nm FDSOI High-K para fazer comparações entre eles. Estes dispositivos foram projetados, caraterizados e testados contra o impacto de íons pesados a níveis dispositivo e circuito. Como resultado obtido, transistor Bulk de 32nm teve, no pior caso, uma carga coletada de 7.57 e 7.19 vezes maior que a carga coletada pelo dispositivo FDSOI de 28nm e FDSOI High-K de 28nm respectivamente atingido pelo mesmo íon pesado de 100MeV-cm2/mg. Com estes dados foi possível modelar o comportamento da carga coletada de ambos dispositivos usando este íon pesado, atingindo os terminais de Fonte e Dreno em distintos lugares e ângulos. Usando a mesma ferramenta e os dados obtidos de carga coletada pelos testes anteriores, foram projetadas células de memória SRAM de 6 transistores. Isso foi para testar elas contra os efeitos do impacto de íons pesados nos transistores NMOS de armazenagem da dados. Neste caso, a Transferência Linear de Energia (LET) do íon necessária para fazer que o dado armazenado na SRAM Bulk mude é 12.8 vezes maior que no caso da SRAM FDSOI e 10 maior no caso da SRAM FDSOI High-K, embora a quantidade de carga coletada necessária para que o dado mude em ambas células seja quase a mesma. Com estes dados foi possível modelar os efeitos dos íons pesados em ambos circuitos, descobrir a Carga Crítica destes e qual é o mínimo LET necessário para que o dado armazenado nestas SRAMs mude. / This work shows a comparison of faults due to Single-Event Effects in 28nm Fully Depleted SOI (FDSOI), 28nm FDSOI High-K and 32nm Bulk CMOS devices, and in 6T SRAM memory cells made with these devices. To provide this, was used TCAD tools to simulate transient faults due to heavy ion impacts on device and circuit levels. The simulations in that environment have the advantage to simulate the facts and mechanisms which produce the transient faults and this effects on the electronic devices, it also allow to simulate the virtual device fabrication and to characterize them. In this case, two devices were created for the simulations: a 32nm Bulk NMOS transistor and a 28nm FDSOI NMOS transistor for compare them. These devices were created, characterized and tested against heavy ion impacts at device and circuit levels. The results show that 32nm Bulk transistor has, in the worst case, a collected charge 7.57 and 7.19 times greater than the 28nm FDSOI and 28nm FDSOI High-K respectively collected charge with the same 100MeV-cm2/mg heavy ion. With these data it was possible to model the behavior of the collected charge in both devices with the same heavy-ion, reach the Source and Drain Terminal in different places and angles. Using the same tools and the obtained collected charge data of previous simulations, it was designed 6 transistors SRAM Memory Cells. That is done to test these circuits against the heavy ion effects on the data-storage NMOS transistor. In this case, the necessary Ion Linear Energy Transfer (LET) to flip the Bulk SRAM is 12.8 greater than the FDSOI SRAM and 10 times greater than the FDSOI High- K SRAM case, although the amount of charge to flip the cells is almost the same in both cases. With these data it was possible to model the heavy-ion effects in both circuits, discover the Critical Charge of them and the minimum LET to flips these SRAMs.

Les effets dus à la radiation peuvent provoquer des pannes dans des circuits intégrés. Lorsqu'une particule subatomique, fait se déposer une charge dans les régions sensibles d'un transistor cela provoque une impulsion de courant. Cette impulsion peut alors engendrer l'inversion d'un bit ou se propager dans un réseau de logique combinatoire avant d'être échantillonnée par une bascule en aval.Selon l'état du circuit au moment de la frappe de la particule et selon l'application, cela provoquera une panne observable ou non. Parmi les événements induits par la radiation, seule une petite portion génère des pannes. Il est donc essentiel de déterminer cette fraction afin de prédire la fiabilité du système. En effet, les raisons pour lesquelles une perturbation pourrait être masquée sont multiples, et il est de plus parfois difficile de préciser ce qui constitue une erreur. A cela s'ajoute le fait que les circuits intégrés comportent des milliards de transistors. Comme souvent dans le contexte de la conception assisté par ordinateur, les approches hiérarchiques et les techniques d'abstraction permettent de trouver des solutions.Cette thèse propose donc plusieurs nouvelles techniques pour analyser les effets dus à la radiation. La première technique permet d'accélérer des simulations d'injections de fautes en détectant lorsqu'une faute a été supprimée du système, permettant ainsi d'arrêter la simulation. La deuxième technique permet de regrouper en ensembles les éléments d'un circuit ayant une fonction similaire. Ensuite, une analyse au niveau des ensemble peut être faite, identifiant ainsi ceux qui sont les plus critiques et qui nécessitent donc d'être durcis. Le temps de calcul est ainsi grandement réduit.La troisième technique permet d'analyser les effets des fautes transitoires dans les circuits combinatoires. Il est en effet possible de calculer à l'avance la sensibilité à des fautes transitoires de cellules ainsi que les effets de masquage dans des blocs fréquemment utilisés. Ces modèles peuvent alors être combinés afin d'analyser la sensibilité de grands circuits. La contribution finale de cette thèse consiste en la définition d'un nouveau langage de modélisation appelé RIIF (Reliability Information Ineterchange Format). Ce langage permet de décrire le taux des fautes dans des composants simples en fonction de leur environnement de fonctionnement. Ces composants simples peuvent ensuite être combinés permettant ainsi de modéliser la propagation de leur fautes vers des pannes au niveau système. En outre, l'utilisation d'un langage standard facilite l'échange de données de fiabilité entre les partenaires industriels.Au-delà des contributions principales, cette thèse aborde aussi des techniques permettant de protéger des mémoires associatives ternaires (TCAMs). Les approches classiques de protection (codes correcteurs) ne s'appliquent pas directement. Une des nouvelles techniques proposées consiste à utiliser une structure de données qui peut détecter, d'une manière statistique, quand le résultat n'est pas correct. La probabilité de détection peut être contrôlée par le nombre de bits alloués à cette structure. Une autre technique consiste à utiliser un détecteur de courant embarqué (BICS) afin de diriger un processus de fond directement vers le région touchée par une erreur. La contribution finale consiste en un algorithme qui permet de synthétiser de la logique combinatoire afin de protéger des circuits combinatoires contre les fautes transitoires.Dans leur ensemble, ces techniques facilitent l'analyse des erreurs provoquées par les effets dus à la radiation dans les circuits intégrés, en particulier pour les très grands circuits composés de blocs provenant de divers fournisseurs. Des techniques pour mieux sélectionner les bascules/flip-flops à durcir et des approches pour protéger des TCAMs ont étés étudiées. / The main objective of this thesis is to develop techniques that can beused to analyze and mitigate the effects of radiation-induced soft errors in industrialscale integrated circuits. To achieve this goal, several methods have been developedbased on analyzing the design at higher levels of abstraction. These techniquesaddress both sequential and combinatorial SER.Fault-injection simulations remain the primary method for analyzing the effectsof soft errors. In this thesis, techniques which significantly speed-up fault-injectionsimulations are presented. Soft errors in flip-flops are typically mitigated by selectivelyreplacing the most critical flip-flops with hardened implementations. Selectingan optimal set to harden is a compute intensive problem and the second contributionconsists of a clustering technique which significantly reduces the number offault-injections required to perform selective mitigation.In terrestrial applications, the effect of soft errors in combinatorial logic hasbeen fairly small. It is known that this effect is growing, yet there exist few techniqueswhich can quickly estimate the extent of combinatorial SER for an entireintegrated circuit. The third contribution of this thesis is a hierarchical approachto combinatorial soft error analysis.Systems-on-chip are often developed by re-using design-blocks that come frommultiple sources. In this context, there is a need to develop and exchange reliabilitymodels. The final contribution of this thesis consists of an application specificmodeling language called RIIF (Reliability Information Interchange Format). Thislanguage is able to model how faults at the gate-level propagate up to the block andchip-level. Work is underway to standardize the RIIF modeling language as well asto extend it beyond modeling of radiation-induced failures.In addition to the main axis of research, some tangential topics were studied incollaboration with other teams. One of these consisted in the development of a novelapproach for protecting ternary content addressable memories (TCAMs), a specialtype of memory important in networking applications. The second supplementalproject resulted in an algorithm for quickly generating approximate redundant logicwhich can protect combinatorial networks against permanent faults. Finally anapproach for reducing the detection time for errors in the configuration RAM forField-Programmable Gate-Arrays (FPGAs) was outlined.

Este trabalho mostra a comparação dos efeitos das falhas provocadas pelos Single-Event Effects em dispositivos 28nm FDSOI, 28nm FDSOI High-K e 32nm Bulk CMOS e células de memória 6T SRAM feitas com estes dispositivos. Para conseguir isso, foram usadas ferramentas TCAD para simular falhas transientes devido a impacto de íons pesados a nível dispositivo e nível circuito. As simulações neste ambiente tem como vantagem a simulação dos fatos e mecanismos que produz as falhas transientes e seus efeitos nos dispositivos, além de também servir para projetar virtualmente estes dispositivos e caraterizar eles para estas simulações. Neste caso, foram projetados três dispositivos para simulação: um transistor NMOS de 32nm Bulk, um transistor NMOS de 28nm FDSOI e um transistor NMOS de 28nm FDSOI High-K para fazer comparações entre eles. Estes dispositivos foram projetados, caraterizados e testados contra o impacto de íons pesados a níveis dispositivo e circuito. Como resultado obtido, transistor Bulk de 32nm teve, no pior caso, uma carga coletada de 7.57 e 7.19 vezes maior que a carga coletada pelo dispositivo FDSOI de 28nm e FDSOI High-K de 28nm respectivamente atingido pelo mesmo íon pesado de 100MeV-cm2/mg. Com estes dados foi possível modelar o comportamento da carga coletada de ambos dispositivos usando este íon pesado, atingindo os terminais de Fonte e Dreno em distintos lugares e ângulos. Usando a mesma ferramenta e os dados obtidos de carga coletada pelos testes anteriores, foram projetadas células de memória SRAM de 6 transistores. Isso foi para testar elas contra os efeitos do impacto de íons pesados nos transistores NMOS de armazenagem da dados. Neste caso, a Transferência Linear de Energia (LET) do íon necessária para fazer que o dado armazenado na SRAM Bulk mude é 12.8 vezes maior que no caso da SRAM FDSOI e 10 maior no caso da SRAM FDSOI High-K, embora a quantidade de carga coletada necessária para que o dado mude em ambas células seja quase a mesma. Com estes dados foi possível modelar os efeitos dos íons pesados em ambos circuitos, descobrir a Carga Crítica destes e qual é o mínimo LET necessário para que o dado armazenado nestas SRAMs mude. / This work shows a comparison of faults due to Single-Event Effects in 28nm Fully Depleted SOI (FDSOI), 28nm FDSOI High-K and 32nm Bulk CMOS devices, and in 6T SRAM memory cells made with these devices. To provide this, was used TCAD tools to simulate transient faults due to heavy ion impacts on device and circuit levels. The simulations in that environment have the advantage to simulate the facts and mechanisms which produce the transient faults and this effects on the electronic devices, it also allow to simulate the virtual device fabrication and to characterize them. In this case, two devices were created for the simulations: a 32nm Bulk NMOS transistor and a 28nm FDSOI NMOS transistor for compare them. These devices were created, characterized and tested against heavy ion impacts at device and circuit levels. The results show that 32nm Bulk transistor has, in the worst case, a collected charge 7.57 and 7.19 times greater than the 28nm FDSOI and 28nm FDSOI High-K respectively collected charge with the same 100MeV-cm2/mg heavy ion. With these data it was possible to model the behavior of the collected charge in both devices with the same heavy-ion, reach the Source and Drain Terminal in different places and angles. Using the same tools and the obtained collected charge data of previous simulations, it was designed 6 transistors SRAM Memory Cells. That is done to test these circuits against the heavy ion effects on the data-storage NMOS transistor. In this case, the necessary Ion Linear Energy Transfer (LET) to flip the Bulk SRAM is 12.8 greater than the FDSOI SRAM and 10 times greater than the FDSOI High- K SRAM case, although the amount of charge to flip the cells is almost the same in both cases. With these data it was possible to model the heavy-ion effects in both circuits, discover the Critical Charge of them and the minimum LET to flips these SRAMs.

The performance of a modern computing system is improving with technology scaling due to advancements in the modern semiconductor industry. However, the power efficiency along with reliability does not scale linearly with performance efficiency. High leakage and standby power in sub 100 nm technology are critical challenges faced by circuit designers. Recent developments in device physics have shown that emerging non-volatile memories are very effective in reducing power dissipation because they eliminate stand by power and exhibit almost zero leakage powerThis dissertation studies the use of emerging non-volatile memory devices in designing circuit architecture for improving power dissipation and the performance of the computing system. More specically, it proposes a novel spintronic Ternary Content AddressableMemory (TCAM), a novel memristive TCAM with improved power and performance efficiency. Our experimental evaluation on 45 nm technology for a 256-bit word-size spintronic TCAM at a supply voltage of 1 V with a sense margin of 50 mV show that the delay is lessthan 200 ps and the per-bit search energy is approximately 3 fJ. The proposed spintronic TCAM consumes at least 30% less energy when compared to state-of-the-art TCAM designs. The search delay on a 144-bit proposed memristive TCAM at a supply voltage of 1 V and a sense margin of 140 mV is 175 ps with per bit search energy of 1.2 fJ on a 45 nm technology. It is 1.12 x times faster and dissipates 67% less search energy per bit than the fastest existing 144-bit MTCAM design.Emerging non-volatile memories are well known for their ability to perform fast analog multiplication and addition when they are arranged in crossbar fashion and are especially suited for neural network applications. However, such systems require the on-chip implementation of the backpropagation algorithm to accommodate process variations. This dissertation studies the impact of process variation in training memristive neural network architecture. It proposes a low hardware overhead on-chip implementation of the backpropagation algorithm that utilizes effectively the very dense memristive cross-bar arrayand is resilient to process variations.Another important issue that needs a careful study due to shrinking technology node is the impact of space or terrestrial radiation in Integrated Circuits (ICs) because the probability of a high energy particle causing an error increases with a decrease in thethreshold voltage and the noise margin. Moreover, single-event effects (SEEs) sensitivity depends on the set of input vectors used at the time of testing due to logical masking. This dissertation analyzes the impact of input test set on the cross section of the microprocessorand proposes a mechanism to derive a high-quality input test set using an automatic test pattern generation (ATPG) for radiation testing of microprocessors arithmetic and logical units..

As the feature size of integrated circuits goes down to the nanometer scale, transient and permanent reliability issues are becoming a significant concern for circuit designers. Traditionally, the reliability issues were mostly handled at the device level as a device engineering problem. However, the increasing severity of reliability challenges and higher error rates due to transient upsets favor higher-level design for reliability (DFR). In this work, we develop several methods for DFR at the circuit level. A major source of transient errors is the single event upset (SEU). SEUs are caused by high-energy particles present in the cosmic rays or emitted by radioactive contaminants in the chip packaging materials. When these particles hit a N+/P+ depletion region of an MOS transistor, they may generate a temporary logic fault. Depending on where the MOS transistor is located and what state the circuit is at, an SEU may result in a circuit-level error. We analyze SEUs both in combinational logic and memories (SRAM). For combinational logic circuit, we propose FASER, a Fast Analysis tool of Soft ERror susceptibility for cell-based designs. The efficiency of FASER is achieved through its static and vector-less nature. In order to evaluate the impact of SEU on SRAM, a theory for estimating dynamic noise margins is developed analytically. The results allow predicting the transient error susceptibility of an SRAM cell using a closedform expression. Among the many permanent failure mechanisms that include time-dependent oxide breakdown (TDDB), electro-migration (EM), hot carrier effect (HCE), and negative bias temperature instability (NBTI), NBTI has recently become important. Therefore, the main focus of our work is NBTI. NBTI occurs when the gate of PMOS is negatively biased. The voltage stress across the gate generates interface traps, which degrade the threshold voltage of PMOS. The degraded PMOS may eventually fail to meet timing requirement and cause functional errors. NBTI becomes severe at elevated temperatures. In this dissertation, we propose a NBTI degradation model that takes into account the temperature variation on the chip and gives the accurate estimation of the degraded threshold voltage. In order to account for the degradation of devices, traditional design methods add guard-bands to ensure that the circuit will function properly during its lifetime. However, the worst-case based guard-bands lead to significant penalty in performance. In this dissertation, we propose an effective macromodel-based reliability tracking and management framework, based on a hybrid network of on-chip sensors, consisting of temperature sensors and ring oscillators. The model is concerned specifically with NBTIinduced transistor aging. The key feature of our work, in contrast to the traditional tracking techniques that rely solely on direct measurement of the increase of threshold voltage or circuit delay, is an explicit macromodel which maps operating temperature to circuit degradation (the increase of circuit delay). The macromodel allows for costeffective tracking of reliability using temperature sensors and is also essential for enabling the control loop of the reliability management system. The developed methods improve the over-conservatism of the device-level, worstcase reliability estimation techniques. As the severity of reliability challenges continue to grow with technology scaling, it will become more important for circuit designers/CAD tools to be equipped with the developed methods. / text

With the increment of mobile, biomedical and space applications, digital systems with low-power consumption are required. As a main part in digital systems, low-power memories are especially desired. Reducing the power supply voltages to sub-threshold region is one of the effective approaches for ultra low-power applications. However, the reduced Static Noise Margin (SNM) of Static Random Access Memory (SRAM) imposes great challenges to the subthreshold SRAM design. The conventional 6-transistor SRAM cell does not function properly at sub-threshold supply voltage range because it has no enough noise margin for reliable operation. In order to achieve ultra low-power at sub-threshold operation, previous research work has demonstrated that the read and write decoupled scheme is a good solution to the reduced SNM problem. A Dual Interlocked Storage Cell (DICE) based SRAM cell was proposed to eliminate the drawback of conventional DICE cell during read operation. This cell can mitigate the singleevent effects, improve the stability and also maintain the low-power characteristic of subthreshold SRAM, In order to make the proposed SRAM cell work under different power supply voltages from 0.3 V to 0.6 V, an improved replica sense scheme was applied to produce a reference control signal, with which the optimal read time could be achieved. In this thesis, a 2K~8 bits SRAM test chip was designed, simulated and fabricated in 90nm CMOS technology provided by ST Microelectronics. Simulation results suggest that the operating frequency at VDD = 0.3 V is up to 4.7 MHz with power dissipation 6.0 ÊW, while it is 45.5 MHz at VDD = 0.6 V dissipating 140 ÊW. However, the area occupied by a single cell is larger than that by conventional SRAM due to additional transistors used. The main contribution of this thesis project is that we proposed a new design that could simultaneously solve the ultra low-power and radiation-tolerance problem in large capacity memory design.

With the increment of mobile, biomedical and space applications, digital systems with low-power consumption are required. As a main part in digital systems, low-power memories are especially desired. Reducing the power supply voltages to sub-threshold region is one of the effective approaches for ultra low-power applications. However, the reduced Static Noise Margin (SNM) of Static Random Access Memory (SRAM) imposes great challenges to the subthreshold SRAM design. The conventional 6-transistor SRAM cell does not function properly at sub-threshold supply voltage range because it has no enough noise margin for reliable operation. In order to achieve ultra low-power at sub-threshold operation, previous research work has demonstrated that the read and write decoupled scheme is a good solution to the reduced SNM problem. A Dual Interlocked Storage Cell (DICE) based SRAM cell was proposed to eliminate the drawback of conventional DICE cell during read operation. This cell can mitigate the singleevent effects, improve the stability and also maintain the low-power characteristic of subthreshold SRAM, In order to make the proposed SRAM cell work under different power supply voltages from 0.3 V to 0.6 V, an improved replica sense scheme was applied to produce a reference control signal, with which the optimal read time could be achieved. In this thesis, a 2K~8 bits SRAM test chip was designed, simulated and fabricated in 90nm CMOS technology provided by ST Microelectronics. Simulation results suggest that the operating frequency at VDD = 0.3 V is up to 4.7 MHz with power dissipation 6.0 ÊW, while it is 45.5 MHz at VDD = 0.6 V dissipating 140 ÊW. However, the area occupied by a single cell is larger than that by conventional SRAM due to additional transistors used. The main contribution of this thesis project is that we proposed a new design that could simultaneously solve the ultra low-power and radiation-tolerance problem in large capacity memory design.

The objective of this work is to investigate the suitability of applying silicon-germanium (SiGe) heterojunction bipolar transistor (HBT) bipolar complementary metal oxide semiconductor (BiCMOS) technology to extreme environments and to design high-speed circuits in this technology to demonstrate their reliable operation under these conditions. This research focuses on exploring techniques for hardening SiGe HBT digital logic for single event upset (SEU) based on principles of radiation hardening by design (RHBD) as well as on the cryogenic characterization of SiGe HBTs and designing broadband amplifiers for operation at cryogenic temperatures. Representative circuits ranging from shift registers featuring multiple architectures to broadband analog circuits have been implemented in various generations of this technology to enable this effort.

A mechanistic kinetic model for the hydrocracking of paraffins based on the single-event kinetics approach has been studied. Several elements of the model have been improved and the parameters of the model have been estimated from experimental data on n-hexadecane hydrocracking. A detailed reaction network of elementary steps has been generated based on the carbenium ion chemistry using the Boolean relation matrices. A total of 49,636 elementary steps are involved in the hydrocracking of n-hexadecane. The rate coefficients of these elementary steps are expressed in terms of a limited number of single event rate coefficients. By virtue of the single event concept, the single event rate coefficients of a given type of elementary steps are independent of the structure of reactant and product. Given their fundamental nature they are also independent of the feedstock composition and the reactor configuration. There is no lumping of components involved in the generation of the reaction network. Partial lumping is introduced only at a later stage of the model development and the lumping is strictly based on the criterion that the individual components in any lump will be in thermodynamic equilibrium. This definition of lumping requires a total of 49 pure components/lumps in the kinetic model for the hydrocracking of n-hexadecane. The "global" rate of reaction of a lump to another lump is expressed using lumping coefficients which account for the transformation of all the components of one lump into the components of another lump through to a given type of elementary steps. The rate expressions thus formulated are inserted into a one-dimensional, three-phase plug flow reactor model. Experimental data have been collected for the hydrocracking of n-hexadecane. The model parameters are estimated by constrained optimization using sequential quadratic programming by minimizing the sum of squares of residuals between experimental and model predicted product profiles. The optimized parameters are finally used for the reactor simulation to study the effect of different process variables on the conversion and product distribution of n-hexadecane hydrocracking. The model is also used to predict the product distribution for the hydrocracking of a heavy paraffinic mixture consisting of C9 to C33 normal paraffins.

No description available.