Special Topics in Information Technology

This open access book presents thirteen outstanding doctoral dissertations in Information Technology from the Department of Electronics, Information and Bioengineering, Politecnico di Milano, Italy. Information Technology has always been highly interdisciplinary, as many aspects have to be considered in IT systems. The doctoral studies program in IT at Politecnico di Milano emphasizes this interdisciplinary nature, which is becoming more and more important in recent technological advances, in collaborative projects, and in the education of young researchers. Accordingly, the focus of advanced research is on pursuing a rigorous approach to specific research topics starting from a broad background in various areas of Information Technology, especially Computer Science and Engineering, Electronics, Systems and Control, and Telecommunications. Each year, more than 50 PhDs graduate from the program. This book gathers the outcomes of the thirteen best theses defended in 2019-20 and selected for the IT PhD Award. Each of the authors provides a chapter summarizing his/her findings, including an introduction, description of methods, main achievements and future work on the topic. Hence, the book provides a cutting-edge overview of the latest research trends in Information Technology at Politecnico di Milano, presented in an easy-to-read format that will also appeal to non-specialists

MOCAST 2021

The 10th International Conference on Modern Circuit and System Technologies on Electronics and Communications (MOCAST 2021) will take place in Thessaloniki, Greece, from July 5th to July 7th, 2021. The MOCAST technical program includes all aspects of circuit and system technologies, from modeling to design, verification, implementation, and application. This Special Issue presents extended versions of top-ranking papers in the conference. The topics of MOCAST include:Analog/RF and mixed signal circuits;Digital circuits and systems design;Nonlinear circuits and systems;Device and circuit modeling;High-performance embedded systems;Systems and applications;Sensors and systems;Machine learning and AI applications;Communication; Network systems;Power management;Imagers, MEMS, medical, and displays;Radiation front ends (nuclear and space application);Education in circuits, systems, and communications

Characterisation of Novel Resistive Switching Memory Devices

Resistive random access memory (RRAM) is widely considered as a disruptive technology that will revolutionize not only non-volatile data storage, but also potentially digital logic and neuromorphic computing. The resistive switching mechanism is generally conceived as the rupture/restoration of defect-formed conductive filament (CF) or defect profile modulation, for filamentary and non-filamentary devices respectively. However, details of the underlying microscopic behaviour of the resistive switching in RRAM are still largely missing. In this thesis, a defect probing technique based on the random telegraph noise (RTN) is developed for both filamentary and non-filamentary devices, which can reveal the resistive switching mechanism at defect level and can also be used to analyse the device performance issues. HfO2 is one of the most matured metal-oxide materials in semiconductor industry and HfO2 RRAM shows promising potential in practical application. An RTN-based defect extraction technique is developed for the HfO2 devices to detect individual defect movement and provide statistical information of CF modification during normal operations. A critical filament region (CFR) is observed and further verified by defect movement tracking. Both defect movements and CFR modification are correlated with operation conditions, endurance failure and recovery. Non-filamentary devices have areal switching characteristics, and are promising in overcoming the drawbacks of filamentary devices that mainly come from the stochastic nature of the CF. a-VMCO is an outstanding non-filamentary device with a set of unique characteristics, but its resistive switching mechanism has not been clearly understood yet. By utilizing the RTN-based defect profiling technique, defect profile modulation in the switching layer is identified and correlated with digital and analogue switching behaviours, for the first time. State instability is analysed and a stable resistance window of 10 for >106 cycles is restored through combining optimizations of device structure and operation conditions, paving the way for its practical application. TaOx-based RRAM has shown fast switching in the sub-nanosecond regime, good CMOS compatibility and record endurance of more than 1012 cycles. Several inconsistent models have been proposed for the Ta2O5/TaOx bilayered structure, and it is difficult to quantify and optimize the performance, largely due to the lack of microscopic description of resistive switching based on experimental results. An indepth analysis of the TiN/Ta2O5/TaOx/TiN structured RRAM is carried out with the RTN-based defect probing technique, for both bipolar and unipolar switching modes. Significant differences in defect profile have been observed and explanations have been provided

Low Power Memory/Memristor Devices and Systems

This reprint focusses on achieving low-power computation using memristive devices. The topic was designed as a convenient reference point: it contains a mix of techniques starting from the fundamental manufacturing of memristive devices all the way to applications such as physically unclonable functions, and also covers perspectives on, e.g., in-memory computing, which is inextricably linked with emerging memory devices such as memristors. Finally, the reprint contains a few articles representing how other communities (from typical CMOS design to photonics) are fighting on their own fronts in the quest towards low-power computation, as a comparison with the memristor literature. We hope that readers will enjoy discovering the articles within

VLSI Design

This book provides some recent advances in design nanometer VLSI chips. The selected topics try to present some open problems and challenges with important topics ranging from design tools, new post-silicon devices, GPU-based parallel computing, emerging 3D integration, and antenna design. The book consists of two parts, with chapters such as: VLSI design for multi-sensor smart systems on a chip, Three-dimensional integrated circuits design for thousand-core processors, Parallel symbolic analysis of large analog circuits on GPU platforms, Algorithms for CAD tools VLSI design, A multilevel memetic algorithm for large SAT-encoded problems, etc

Optics for AI and AI for Optics

Artificial intelligence is deeply involved in our daily lives via reinforcing the digital transformation of modern economies and infrastructure. It relies on powerful computing clusters, which face bottlenecks of power consumption for both data transmission and intensive computing. Meanwhile, optics (especially optical communications, which underpin today’s telecommunications) is penetrating short-reach connections down to the chip level, thus meeting with AI technology and creating numerous opportunities. This book is about the marriage of optics and AI and how each part can benefit from the other. Optics facilitates on-chip neural networks based on fast optical computing and energy-efficient interconnects and communications. On the other hand, AI enables efficient tools to address the challenges of today’s optical communication networks, which behave in an increasingly complex manner. The book collects contributions from pioneering researchers from both academy and industry to discuss the challenges and solutions in each of the respective fields

Nouvelles Architectures Hybrides (Logique / Mémoires Non-Volatiles et technologies associées.)

Les nouvelles approches de technologies mémoires permettront une intégration dite back-end, où les cellules élémentaires de stockage seront fabriquées lors des dernières étapes de réalisation à grande échelle du circuit. Ces approches innovantes sont souvent basées sur l'utilisation de matériaux actifs présentant deux états de résistance distincts. Le passage d'un état à l'autre est contrôlé en courant ou en tension donnant lieu à une caractéristique I-V hystérétique. Nos mémoires résistives sont composées d'argent en métal électrochimiquement actif et de sulfure amorphe agissant comme électrolyte. Leur fonctionnement repose sur la formation réversible et la dissolution d'un filament conducteur. Le potentiel d'application de ces nouveaux dispositifs n'est pas limité aux mémoires ultra-haute densité mais aussi aux circuits embarqués. En empilant ces mémoires dans la troisième dimension au niveau des interconnections des circuits logiques CMOS, de nouvelles architectures hybrides et innovantes deviennent possibles. Il serait alors envisageable d'exploiter un fonctionnement à basse énergie, à haute vitesse d'écriture/lecture et de haute performance telles que l'endurance et la rétention. Dans cette thèse, en se concentrant sur les aspects de la technologie de mémoire en vue de développer de nouvelles architectures, l'introduction d'une fonctionnalité non-volatile au niveau logique est démontrée par trois circuits hybrides: commutateurs de routage non volatiles dans un Field Programmable Gate Arrays, un 6T-SRAM non volatile, et les neurones stochastiques pour un réseau neuronal. Pour améliorer les solutions existantes, les limitations de la performances des dispositifs mémoires sont identifiés et résolus avec des nouveaux empilements ou en fournissant des défauts de circuits tolérants.Novel approaches in the field of memory technology should enable backend integration, where individual storage nodes will be fabricated during the last fabrication steps of the VLSI circuit. In this case, memory operation is often based upon the use of active materials with resistive switching properties. A topology of resistive memory consists of silver as electrochemically active metal and amorphous sulfide acting as electrolyte and relies on the reversible formation and dissolution of a conductive filament. The application potential of these new memories is not limited to stand-alone (ultra-high density), but is also suitable for embedded applications. By stacking these memories in the third dimension at the interconnection level of CMOS logic, new ultra-scalable hybrid architectures becomes possible which exploit low energy operation, fast write/read access and high performance with respect to endurance and retention. In this thesis, focusing on memory technology aspects in view of developing new architectures, the introduction of non-volatile functionality at the logic level is demonstrated through three hybrid (CMOS logic ReRAM devices) circuits: nonvolatile routing switches in a Field Programmable Gate Array, nonvolatile 6T-SRAMs, and stochastic neurons of an hardware neural network. To be competitive or even improve existing solutions, limitations on the memory devices performances are identified and solved by stack engineering of CBRAM devices or providing faults tolerant circuits.SAVOIE-SCD - Bib.électronique (730659901) / SudocGRENOBLE1/INP-Bib.électronique (384210012) / SudocGRENOBLE2/3-Bib.électronique (384219901) / SudocSudocFranceF

A Practical Investigation into Achieving Bio-Plausibility in Evo-Devo Neural Microcircuits Feasible in an FPGA

Many researchers has conjectured, argued, or in some cases demonstrated, that bio-plausibility can bring about emergent properties such as adaptability, scalability, fault-tolerance, self-repair, reliability, and autonomy to bio-inspired intelligent systems. Evolutionary-developmental (evo-devo) spiking neural networks are a very bio-plausible mixture of such bio-inspired intelligent systems that have been proposed and studied by a few researchers. However, the general trend is that the complexity and thus the computational cost grow with the bio-plausibility of the system. FPGAs (Field- Programmable Gate Arrays) have been used and proved to be one of the flexible and cost efficient hardware platforms for research' and development of such evo-devo systems. However, mapping a bio-plausible evo-devo spiking neural network to an FPGA is a daunting task full of different constraints and trade-offs that makes it, if not infeasible, very challenging. This thesis explores the challenges, trade-offs, constraints, practical issues, and some possible approaches in achieving bio-plausibility in creating evolutionary developmental spiking neural microcircuits in an FPGA through a practical investigation along with a series of case studies. In this study, the system performance, cost, reliability, scalability, availability, and design and testing time and complexity are defined as measures for feasibility of a system and structural accuracy and consistency with the current knowledge in biology as measures for bio-plausibility. Investigation of the challenges starts with the hardware platform selection and then neuron, cortex, and evo-devo models and integration of these models into a whole bio-inspired intelligent system are examined one by one. For further practical investigation, a new PLAQIF Digital Neuron model, a novel Cortex model, and a new multicellular LGRN evo-devo model are designed, implemented and tested as case studies. Results and their implications for the researchers, designers of such systems, and FPGA manufacturers are discussed and concluded in form of general trends, trade-offs, suggestions, and recommendations

Journal of Telecommunications and Information Technology

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