Multi-Processor SoC (MPSOC) design brings to the foreground a large number of challenges, one of the most prominent of which is the design of the chip interconnection. With a number of on-chip blocks presently ranging in the tens, and quickly approaching the hundreds, the novel issue of how to best provide on-chip communication resources is clearly felt. Scaling down of process technologies has increased process and dynamic variations as well as transistor wearout. Because of this, delay variations increase and impact the performance of the MPSoCs. The interconnect architecture inMPSoCs becomes a single point of failure as it connects all other components of the system together. A faulty processing element may be shut down entirely, but the interconnect architecture must be able to tolerate partial failure and variations and operate with performance, power or latency overhead. This dissertation focuses on techniques at different levels of abstraction to face with the reliability and variability issues in on-chip interconnection networks. By showing the test results of a GALS NoC testchip this dissertation motivates the need for techniques to detect and work around manufacturing faults and process variations in MPSoCs’ interconnection infrastructure. As a physical design technique, we propose the bundle routing framework as an effective way to route the Network on Chips’ global links. For architecture-level design, two cases are addressed: (I) Intra-cluster communication where we propose a low-latency interconnect with variability robustness (ii) Inter-cluster communication where an online functional testing with a reliable NoC configuration are proposed. We also propose dualVdd as an orthogonal way of compensating variability at the post-fabrication stage. This is an alternative strategy with respect to the design techniques, since it enforces the compensation at post silicon stage.

Next generation electronic devices have to guarantee high performance while being less power-consuming and highly reliable for several application domains ranging from the entertainment to the business. In this context, multicore platforms have proven the most efficient design choice but new challenges have to be faced. The ever-increasing miniaturization of the components produces unexpected variations on technological parameters and wear-out characterized by soft and hard errors. Even though hardware techniques, which lend themselves to be applied at design time, have been studied with the objective to mitigate these effects, they are not sufficient; thus software adaptive techniques are necessary. In this thesis we focus on multicore task allocation strategies to minimize the energy consumption while meeting performance constraints. We firstly devise a technique based on an Integer Linear Problem formulation which provides the optimal solution but cannot be applied on-line since the algorithm it needs is time-demanding; then we propose a sub-optimal technique based on two steps which can be applied on-line. We demonstrate the effectiveness of the latter solution through an exhaustive comparison against the optimal solution, state-of-the-art policies, and variability-agnostic task allocations by running multimedia applications on the virtual prototype of a next generation industrial multicore platform. We also face the problem of the performance and lifetime degradation. We firstly focus on embedded multicore platforms and propose an idleness distribution policy that increases core expected lifetimes by duty cycling their activity; then, we investigate the use of micro thermoelectrical coolers in general-purpose multicore processors to control the temperature of the cores at runtime with the objective of meeting lifetime constraints without performance loss.

Photovoltaic (PV) conversion is the direct production of electrical energy from sun without involving the emission of polluting substances. In order to be competitive with other energy sources, cost of the PV technology must be reduced ensuring adequate conversion efficiencies. These goals have motivated the interest of researchers in investigating advanced designs of crystalline silicon solar (c-Si) cells. Since lowering the cost of PV devices involves the reduction of the volume of semiconductor, an effective light trapping strategy aimed at increasing the photon absorption is required. Modeling of solar cells by electro-optical numerical simulation is helpful to predict the performance of future generations devices exhibiting advanced light-trapping schemes and to provide new and more specific guidelines to industry. The approaches to optical simulation commonly adopted for c-Si solar cells may lead to inaccurate results in case of thin film and nano-stuctured solar cells. On the other hand, rigorous solvers of Maxwell equations are really cpu- and memory-intensive. Recently, in optical simulation of solar cells, the RCWA method has gained relevance, providing a good trade-off between accuracy and computational resources requirement. This thesis is a contribution to the numerical simulation of advanced silicon solar cells by means of a state-of-the-art numerical 2-D/3-D device simulator, that has been successfully applied to the simulation of selective emitter and the rear point contact solar cells, for which the multi-dimensionality of the transport model is required in order to properly account for all physical competing mechanisms. In the second part of the thesis, the optical problems is discussed. Two novel and computationally efficient RCWA implementations for 2-D simulation domains as well as a third RCWA for 3-D structures based on an eigenvalues calculation approach have been presented. The proposed simulators have been validated in terms of accuracy, numerical convergence, computation time and correctness of results. / La conversione fotovoltaica è la produzione diretta di energia elettrica dal sole che non comporta l'emissione di sostanze inquinanti. Al fine di competere con altre fonti di energia, la tecnologia fotovoltaica deve subire una riduzione del costo garantendo contemporaneamente adeguate efficienze di conversione. Questi obiettivi hanno motivato l'interesse dei ricercatori al progetto ed all'analisi di celle solari avanzate in silicio cristallino. Poiché la riduzione del costo dei dispositivi fotovoltaici comporta tipicamente la riduzione del volume di semiconduttore, è necessaria una strategia efficace di intrappolamento della luce per aumentare l'assorbimento dei fotoni. Gli approcci orientati alla simulazione ottica comunemente adottati per la celle solari in silicio cristallino possono condurre a risultati non accurati in caso di celle a film sottile e nanostrutturate. D'altra parte, i risolutori rigorosi delle equazioni di Maxwell sono altamente onerosi in termini computazionali. Recentemente, nella simulazione ottica di celle solari, il metodo RCWA ha acquisito una forte popolarità, fornendo un buon compromesso tra accuratezza e fabbisogno di risorse computazionali. Questa tesi rappresenta un contributo alla simulazione numerica -sia ottica che elettrica- di celle solari avanzate al silicio. Un simulatore numerico di dispositivi a semiconduttore 2-D/3-D allo stato dell'arte è stato applicato con successo alla simulazione di celle a doppia diffusione di emettitore a di celle con superficie posteriore passivata e contatto locale, per le quali è richiesta la multi-dimensionalità del modello di trasporto al fine di descrivere correttamente tutti i meccanismi fisici. Nella seconda parte della tesi, vengono discussi gli aspetti relativi alla simulazione ottica. Due innovative e computazionalmente efficienti implementazioni del metodo RCWA per domini di simulazione 2-D nonché un terzo simulatore RCWA per strutture 3-D basato sul calcolo di autovalori sono stati presentati in questa tesi. I simulatori proposti sono stati validati in termini di accuratezza, convergenza numerica, tempo di calcolo e correttezza dei risultati.

This thesis presents several data processing and compression techniques capable of addressing the strict requirements of wireless sensor networks. After introducing a general overview of sensor networks, the energy problem is introduced, dividing the different energy reduction approaches according to the different subsystem they try to optimize. To manage the complexity brought by these techniques, a quick overview of the most common middlewares for WSNs is given, describing in detail SPINE2, a framework for data processing in the node environment. The focus is then shifted on the in-network aggregation techniques, used to reduce data sent by the network nodes trying to prolong the network lifetime as long as possible. Among the several techniques, the most promising approach is the Compressive Sensing (CS). To investigate this technique, a practical implementation of the algorithm is compared against a simpler aggregation scheme, deriving a mixed algorithm able to successfully reduce the power consumption. The analysis moves from compression implemented on single nodes to CS for signal ensembles, trying to exploit the correlations among sensors and nodes to improve compression and reconstruction quality. The two main techniques for signal ensembles, Distributed CS (DCS) and Kronecker CS (KCS), are introduced and compared against a common set of data gathered by real deployments. The best trade-off between reconstruction quality and power consumption is then investigated. The usage of CS is also addressed when the signal of interest is sampled at a Sub-Nyquist rate, evaluating the reconstruction performance. Finally the group sparsity CS (GS-CS) is compared to another well-known technique for reconstruction of signals from an highly sub-sampled version. These two frameworks are compared again against a real data-set and an insightful analysis of the trade-off between reconstruction quality and lifetime is given.

It is usual to hear a strange short sentence: «Random is better than...». Why is randomness a good solution to a certain engineering problem? There are many possible answers, and all of them are related to the considered topic. In this thesis I will discuss about two crucial topics that take advantage by randomizing some waveforms involved in signals manipulations. In particular, advantages are guaranteed by shaping the second order statistic of antipodal sequences involved in an intermediate signal processing stages. The first topic is in the area of analog-to-digital conversion, and it is named Compressive Sensing (CS). CS is a novel paradigm in signal processing that tries to merge signal acquisition and compression at the same time. Consequently it allows to direct acquire a signal in a compressed form. In this thesis, after an ample description of the CS methodology and its related architectures, I will present a new approach that tries to achieve high compression by design the second order statistics of a set of additional waveforms involved in the signal acquisition/compression stage. The second topic addressed in this thesis is in the area of communication system, in particular I focused the attention on ultra-wideband (UWB) systems. An option to produce and decode UWB signals is direct-sequence spreading with multiple access based on code division (DS-CDMA). Focusing on this methodology, I will address the coexistence of a DS-CDMA system with a narrowband interferer. To do so, I minimize the joint effect of both multiple access (MAI) and narrowband (NBI) interference on a simple matched filter receiver. I will show that, when spreading sequence statistical properties are suitably designed, performance improvements are possible with respect to a system exploiting chaos-based sequences minimizing MAI only.

Most electronic systems can be described in a very simplified way as an assemblage of analog and digital components put all together in order to perform a certain function. Nowadays, there is an increasing tendency to reduce the analog components, and to replace them by operations performed in the digital domain. This tendency has led to the emergence of new electronic systems that are more flexible, cheaper and robust. However, no matter the amount of digital process implemented, there will be always an analog part to be sorted out and thus, the step of converting digital signals into analog signals and vice versa cannot be avoided. This conversion can be more or less complex depending on the characteristics of the signals. Thus, even if it is desirable to replace functions carried out by analog components by digital processes, it is equally important to do so in a way that simplifies the conversion from digital to analog signals and vice versa. In the present thesis, we have study strategies based on increasing the amount of processing in the digital domain in such a way that the implementation of analog hardware stages can be simplified. To this aim, we have proposed the use of very low quantized signals, i.e. 1-bit, for the acquisition and for the generation of particular classes of signals.

The quest for universal memory is driving the rapid development of memories with superior all-round capabilities in non-volatility, high speed, high endurance and low power. The memory subsystem accounts for a significant cost and power budget of a computer system. Current DRAM-based main memory systems are starting to hit the power and cost limit. To resolve this issue the industry is improving existing technologies such as Flash and exploring new ones. Among those new technologies is the Phase Change Memory (PCM), which overcomes some of the shortcomings of the Flash such as durability and scalability. This alternative non-volatile memory technology, which uses resistance contrast in phase-change materials, offers more density relative to DRAM, and can help to increase main memory capacity of future systems while remaining within the cost and power constraints. Chalcogenide materials can suitably be exploited for manufacturing phase-change memory devices. Charge transport in amorphous chalcogenide-GST used for memory devices is modeled using two contributions: hopping of trapped electrons and motion of band electrons in extended states. Crystalline GST exhibits an almost Ohmic I(V) curve. In contrast amorphous GST shows a high resistance at low biases while, above a threshold voltage, a transition takes place from a highly resistive to a conductive state, characterized by a negative differential-resistance behavior. A clear and complete understanding of the threshold behavior of the amorphous phase is fundamental for exploiting such materials in the fabrication of innovative nonvolatile memories. The type of feedback that produces the snapback phenomenon is described as a filamentation in energy that is controlled by electron–electron interactions between trapped electrons and band electrons. The model thus derived is implemented within a state-of-the-art simulator. An analytical version of the model is also derived and is useful for discussing the snapback behavior and the scaling properties of the device. / Lo sviluppo dei sistemi di memoria di futura generazione è guidato principalmente dalla ricerca di una tecnologia in grado di superare quelle attuali in ogni loro specifica di funzionamento, dalla ritenzione di dato alla velocità di accesso, migliorandone la durata e riducendo il dispendio energetico. Il sottosistema delle memorie assorbe una parte significativa delle risorse del macro sistema costituito dal calcolatore, tanto da aver quasi raggiunto il limite tecnologico nel caso delle odierne memorie di tipo DRAM. La soluzione più promettente sembra essere quella delle memorie a cambiamento di fase (PCM), in grado di colmare anche i limiti mostrati dalla tecnologia Flash nell’ambito della durata e scalabilità. I materiali che consentono di realizzare dispostivi a cambiamento di fase pilotato elettricamente appartengono alla famiglia dei calcogenuri. Tra i diversi composti calcogenuri quello attualmente identificato come soluzione più promettente è il Ge2Sb2Te5 (GST). Il trasporto di carica all’interno di dispositivi di memoria realizzati con tali materiali è stato modellato considerando l’azione di due contributi differenti: hopping di cariche intrappolate e moto di elettroni liberi in stati estesi. Il GST mostra un comportamento elettrico pressoché Ohmico in fase cristallina mentre, in fase amorfa, risulta essere poco conduttivo per basse correnti fino al superamento di una tensione di soglia oltre la quale si assiste al passaggio da uno stato altamente resistivo ad uno altamente conduttivo, caratterizzato da un andamento a resistenza differenziale negativa (NDR). Il meccanismo retroattivo che induce il fenomeno di snapback viene descritto come filamentazione in energia controllata dalle interazioni tra elettroni liberi ed elettroni intrappolati. Il modello fisico ricavato è stato implementato all’interno di un simulatore di dispositivi di ultima generazione ed è stato in seguito riprodotto in una versione analitica semplificata in grado, però, di permettere una prima analisi del comportamento elettrico del dispositivo e delle sue proprietà di scaling.

Reliable electronic systems, namely a set of reliable electronic devices connected to each other and working correctly together for the same functionality, represent an essential ingredient for the large-scale commercial implementation of any technological advancement. Microelectronics technologies and new powerful integrated circuits provide noticeable improvements in performance and cost-effectiveness, and allow introducing electronic systems in increasingly diversified contexts. On the other hand, opening of new fields of application leads to new, unexplored reliability issues. The development of semiconductor device and electrical models (such as the well known SPICE models) able to describe the electrical behavior of devices and circuits, is a useful means to simulate and analyze the functionality of new electronic architectures and new technologies. Moreover, it represents an effective way to point out the reliability issues due to the employment of advanced electronic systems in new application contexts. In this thesis modeling and design of both advanced reliable circuits for general-purpose applications and devices for energy efficiency are considered. More in details, the following activities have been carried out: first, reliability issues in terms of security of standard communication protocols in wireless sensor networks are discussed. A new communication protocol is introduced, allows increasing the network security. Second, a novel scheme for the on-die measurement of either clock jitter or process parameter variations is proposed. The developed scheme can be used for an evaluation of both jitter and process parameter variations at low costs. Then, reliability issues in the field of “energy scavenging systems” have been analyzed. An accurate analysis and modeling of the effects of faults affecting circuit for energy harvesting from mechanical vibrations is performed. Finally, the problem of modeling the electrical and thermal behavior of photovoltaic (PV) cells under hot-spot condition is addressed with the development of an electrical and thermal model.

Ultrasound imaging is widely used in medical diagnostics as it is the fastest, least invasive, and least expensive imaging modality. However, ultrasound images are intrinsically difficult to be interpreted. In this scenario, Computer Aided Detection (CAD) systems can be used to support physicians during diagnosis providing them a second opinion. This thesis discusses efficient ultrasound processing techniques for computer aided medical diagnostics, focusing on two major topics: (i) Ultrasound Tissue Characterization (UTC), aimed at characterizing and differentiating between healthy and diseased tissue; (ii) Ultrasound Image Segmentation (UIS), aimed at detecting the boundaries of anatomical structures to automatically measure organ dimensions and compute clinically relevant functional indices. Research on UTC produced a CAD tool for Prostate Cancer detection to improve the biopsy protocol. In particular, this thesis contributes with: (i) the development of a robust classification system; (ii) the exploitation of parallel computing on GPU for real-time performance; (iii) the introduction of both an innovative Semi-Supervised Learning algorithm and a novel supervised/semi-supervised learning scheme for CAD system training that improve system performance reducing data collection effort and avoiding collected data wasting. The tool provides physicians a risk map highlighting suspect tissue areas, allowing them to perform a lesion-directed biopsy. Clinical validation demonstrated the system validity as a diagnostic support tool and its effectiveness at reducing the number of biopsy cores requested for an accurate diagnosis. For UIS the research developed a heart disease diagnostic tool based on Real-Time 3D Echocardiography. Thesis contributions to this application are: (i) the development of an automated GPU based level-set segmentation framework for 3D images; (ii) the application of this framework to the myocardium segmentation. Experimental results showed the high efficiency and flexibility of the proposed framework. Its effectiveness as a tool for quantitative analysis of 3D cardiac morphology and function was demonstrated through clinical validation. / L’ecografia è una tecnica diagnostica per immagini utilizzata nella pratica clinica, non invasiva, poco costosa e in tempo reale. La bassa qualità delle immagini rende l’interpretazione complessa e soggettiva. Per supportare i medici nella diagnosi è possibile utilizzare sistemi Computer Aided Detection (CAD). La tesi discute tecniche efficienti di elaborazione dei segnali ultrasonici per diagnostica medica supportata da computer. Vengono trattate due tematiche: (i) la caratterizzazione tissutale basata su ultrasuoni, finalizzata al miglioramento del protocollo bioptico per la diagnosi del tumore alla prostata; (ii) la segmentazione di immagini ecocardiografiche, finalizzata all’individuazione dei contorni delle strutture cardiache per misurare in modo automatico le dimensioni dell’organo e calcolare indici di funzionalità clinicamente rilevanti. Nell’ambito del primo tema è stato sviluppato un sistema CAD. I contributi in quest’ambito sono: (i) lo sviluppo di un robusto sistema di classificazione, (i) l’utilizzo di elaborazione parallela su GPU per ottenere prestazioni in tempo reale; (iii) l’introduzione di un nuovo algoritmo di apprendimento semi-supervisionato e di una procedura di addestramento capace di utilizzare tutti i dati raccolti. Il sistema guida il medico indirizzando il campionamento bioptico verso zone potenzialmente patologiche. Una validazione con dati clinici ha dimostrato la validità del sistema come strumento di supporto alla diagnosi in grado di consentire una riduzione del numero di campioni necessari per una diagnosi accurata. Nell’ambito del secondo tema è stato sviluppato uno strumento per la diagnosi dei malfunzionamenti cardiaci tramite ecocardiografia 3D real-time. I contributi della tesi sono: (i) lo sviluppo di un framework di segmentazione automatica per immagini 3D basato sulla tecnica level-set e operante su GPU; (ii) la sua applicazione ad immagini ecocardiografiche tridimensionali. Risultati sperimentali ne hanno dimostrato l’elevata efficienza e flessibilità. Una validazione su dati clinici ne ha dimostrato l’efficacia come strumento di supporto al medico per l’analisi quantitativa della morfologia e della funzionalità cardiaca.

Semiconductors technologies are rapidly evolving driven by the need for higher performance demanded by applications. Thanks to the numerous advantages that it offers, gallium nitride (GaN) is quickly becoming the technology of reference in the field of power amplification at high frequency. The RF power density of AlGaN/GaN HEMTs (High Electron Mobility Transistor) is an order of magnitude higher than the one of gallium arsenide (GaAs) transistors. The first demonstration of GaN devices dates back only to 1993. Although over the past few years some commercial products have started to be available, the development of a new technology is a long process. The technology of AlGaN/GaN HEMT is not yet fully mature, some issues related to dispersive phenomena and also to reliability are still present. Dispersive phenomena, also referred as long-term memory effects, have a detrimental impact on RF performances and are due both to the presence of traps in the device structure and to self-heating effects. A better understanding of these problems is needed to further improve the obtainable performances. Moreover, new models of devices that take into consideration these effects are necessary for accurate circuit designs. New characterization techniques are thus needed both to gain insight into these problems and improve the technology and to develop more accurate device models. This thesis presents the research conducted on the development of new charac- terization and modelling methodologies for GaN-based devices and on the use of this technology for high frequency power amplifier applications.