A DLL Based Test Solution for 3D ICs

Integrated circuits (ICs) are rapidly changing and vertical integration and packaging strategies have already become an important research topic. 2.5D and 3D IC integrations have obvious advantages over the conventional two dimensional IC implementations in performance, capacity, and power consumption. A passive Si interposer utilizing Through-Silicon via (TSV) technology is used for 2.5D IC integration. TSV is also the enabling technology for 3D IC integration. TSV manufacturing defects can affect the performance of stacked devices and reduce the yield. Manufacturing test methodologies for TSVs have to be developed to ensure fault-free devices. This thesis presents two test methods for TSVs in 2.5D and 3D ICs utilizing Delay-Locked Loop (DLL) modules. In the test method developed for TSVs in 2.5D ICs, a DLL is used to determine the propagation delay for fault detection. TSV faults in 3D ICs are detected through observation of the control voltage of a DLL. The proposed test methods present a robust performance against Process, supply Voltage and Temperature (PVT) variations due to the inherent feedback of DLLs. 3D full-wave simulations are performed to extract circuit level models for TSVs and fragments of an interposer wires using HFSS simulation tools. The extracted TSV models are then used to perform circuit level simulations using ADS tools from Agilent. Simulation results indicate that the proposed test solution for TSVs can detect manufacturing defects affecting the TSV propagation delay

Thermo-Mechanical Effects Of Thermal Cycled Copper Through Silicon Vias

The semiconductor industry is currently facing transistor scaling issues due to fabrication thresholds and quantum effects. In this \u27More-Than-Moore\u27 era, the industry is developing new ways to increase device performance, such as stacking chips for three-dimensional integrated circuits (3D-IC). The 3D-IC\u27s superior performance over their 2D counterparts can be attributed to the use of vertical interconnects, or through silicon vias (TSV). These interconnects are much shorter, reducing signal delay. However TSVs are susceptible to various thermo-mechanical reliability concerns. Heating during fabrication and use, in conjunction with coefficient of thermal expansion mismatch between the copper TSVs and silicon substrate, create harmful stresses in the system. The purpose of this work is to evaluate the signal integrity of Cu-TSVs and determine the major contributing factors of the signal degradation upon in-use conditions. Two series of samples containing blind Cu-TSVs embedded in a Si substrate were studied, each having different types and amounts of voids from manufacturing. The samples were thermally cycled up to 2000 times using three maximum temperatures to simulate three unique in-use conditions. S11 parameter measurements were then conducted to determine the signal integrity of the TSVs. To investigate the internal response from cycling, a protocol was developed for cross-sectioning the copper TSVs. Voids were measured using scanning electron microscope and focused ion beam imaging of the cross-sections, while the microstructural evolution of the copper was monitored with electron backscattering diffraction. An increase in void area was found to occur after cycling. This is thought to be the major contributing factor in the signal degradation of the TSVs, since no microstructural changes were observed in the copper

Decoding function through comparative genomics: from animal evolution to human disease

Deciphering the functionality encoded in the genome constitutes an essential first step to understanding the context through which mutations can cause human disease. In this dissertation, I present multiple studies based on the use or development of comparative genomics techniques to elucidate function (or lack of function) from the genomes of humans and other animal species. Collectively, these studies focus on two biological entities encoded in the human genome: genes related to human disease susceptibility and those that encode microRNAs - small RNAs that have important gene-regulatory roles in normal biological function and in human disease. Extending this work, I investigated the evolution of these biological entities within animals to shed light on how their underlying functions arose and how they can be modeled in non-human species. Additionally, I present a new tool that uses large-scale clinical genomic data to identify human mutations that may affect microRNA regulatory functions, thereby providing a method by which state-of-the-art genomic technologies can be fully utilized in the search for new disease mechanisms and potential drug targets. The scientific contributions made in this dissertation utilize current data sets generated using high-throughput sequencing technologies. For example, recent whole-genome sequencing studies of the most distant animal lineages have effectively restructured the animal tree of life as we understand it. The first two chapters utilize data from this new high-confidence animal phylogeny - in addition to data generated in the course of my work - to demonstrate that (1) certain classes of human disease have uncommonly large proportions of genes that evolved with the earliest animals and/or vertebrates, and (2) that canonical microRNA functionality - absent in at least two of the early branching animal lineages - likely evolved after the first animals. In the third chapter, I expand upon recent research in predicting microRNA target sites, describing a novel tool for predicting clinically significant microRNA target site variants and demonstrating its applicability to the analysis of clinical genomic data. Thus, the studies detailed in this dissertation represent significant advances in our understanding of the functions of disease genes and microRNAs from both an evolutionary and a clinical perspective

Mining metagenomics datasets for novel plastic-degrading enzymes

Dissertação de mestrado em BioinformáticaA crescente quantidade de dados depositados em bases de dados públicas sem anotação pode ocultar uma série de genes e proteínas cuja função ainda é desconhecida. Com base no conhecimento de algumas enzimas capazes de catalisar reações com interesse ambiental ou biotecnológico, será possível encontrar em bases de dados de proteínas ou em conjuntos de dados ómicos, outras com atividade semelhante, que eventualmente poderão ser mais eficientes. No entanto, não existem ferramentas bioinformáticas projetadas para encontrar proteínas de interesse em grandes conjuntos de dados. Neste trabalho, uma ferramenta de bioinformática foi desenvolvida e denominada Mining Protein dAtasets foR Targeted enzYmes (M-PARTY) para minerar enzimas alvo em grandes conjuntos de dados. M-PARTY recebe um ficheiro FASTA contendo as enzimas alvo e automaticamente produz bases de dados de Hidden Markov Model, valida e filtra os modelos não validados. M PARTY procura sequências homólogas em determinados conjuntos de dados e identifica as proteínas mais semelhantes, que apresentam potencialmente as mesmas atividades das enzimas alvo. A M-PARTY é uma Interface de Linha de Comando de uso gratuito, corre no sistema operacional Linux com apenas um comando, é de código aberto e foi desenvolvida em Python. Esta ferramenta foi testada para encontrar enzimas envolvidas na biodegradação do polietileno em metagenomas hidrotermais e marinhos. A partir de 5 sequências proteicas iniciais, 329 HMMs foram gerados pelo M PARTY e 103 foram descartados após a etapa de validação. Um total de 19 proteínas apresentaram homologia significativa com as 5 enzimas alvo, sendo enzimas potencialmente degradadoras de polietileno. Esta ferramenta será muito útil para realizar uma primeira triagem de enzimas de interesse em diferentes ambientes, antecedendo uma posterior confirmação da atividade enzimática e eventual implementação.There is an increasing amount of data deposited in public databases that is poorly annotated and may hide a number of genes and proteins whose function is yet unknown. By knowing some enzymes that are capable to catalyze reactions with environmental or biotechnological interest, it would be possible to find other enzymes in databases or in omics datasets with similar activity, and which could be even more efficient. However, there are no bioinformatics tools designed to find proteins of interest in large datasets, such as those from metagenomics experiments. In this work, a bioinformatics tool was developed, named Mining Protein dAtasets foR Target enzYmes (M-PARTY), for mining target enzymes in big datasets. M-PARTY receives a FASTA file containing the target enzymes, and automatically produces Hidden Markov Model databases, validating, and filtering the non-validated models. M-PARTY searches for homolog sequences in given datasets and identifies the most similar proteins, which present potentially the same activities of the target enzymes. M-PARTY is a free-to-use Command Line Interface, runs on Linux operating system with only a command, is open source, and was developed in Python. This tool was tested to find enzymes involved in polyethylene biodegradation in hydrothermal and marine metagenomes. From 5 initial protein sequences, 329 HMMs were generated by M-PARTY, and 103 were discarded after the validation step. A total of 19 proteins showed significant homology to the 5 target enzymes, being potentially polyethylene-degrading enzymes. This tool will be especially useful for performing a first screening of enzymes of interest in different environments, preceding further enzymatic activity confirmation and eventual implementation on biotechnological processes

Body of Knowledge for Graphics Processing Units (GPUs)

Graphics Processing Units (GPU) have emerged as a proven technology that enables high performance computing and parallel processing in a small form factor. GPUs enhance the traditional computer paradigm by permitting acceleration of complex mathematics and providing the capability to perform weighted calculations, such as those in artificial intelligence systems. Despite the performance enhancements provided by this type of microprocessor, there exist tradeoffs in regards to reliability and radiation susceptibility, which may impact mission success. This report provides an insight into GPU architecture and its potential applications in space and other similar markets. It also discusses reliability, qualification, and radiation considerations for testing GPUs

Molecular dynamics of a subset of central nervous system proteins

Treballs Finals de Grau d'Enginyeria Biomèdica. Facultat de Medicina i Ciències de la Salut. Universitat de Barcelona. Curs: 2022-2023. Tutor/Director: Sala Llonch, Roser, Orozco López, ModestoThe human brain is organized in a hierarchical structure of distinct but closely connected levels. Although our knowledge about each individual level is extensive, what remains unknown is a comprehensive understanding of how events in low levels propagate through higher levels. This is a challenge for neuroscience. This project focuses on low-level protein events. Its aim is to simulate the dynamics of a subset of central nervous system proteins as their mobility and flexibility are essential for neurological signal transduction. In particular, it is centred on the subset of CNS proteins related to Parkinson’s disease. By reproducing their dynamics, the process of signal transduction in the brain can be better understood, as well as helping in the design of neuro-active drugs for Parkinson’s disease. This document provides a detailed description of the development of the project to obtain the dynamics of the proteins of study. The scope of the project goes from generating a list of proteins of interest, running and validating their dynamics and uploading the data to an open access database. A total of 49 simulations were successfully obtained and uploaded. These simulations can be further studied to understand protein functions in neurological pathways as well as study possible drug binding interactions

Heurísticas bioinspiradas para el problema de Floorplanning 3D térmico de dispositivos MPSoCs

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Informática, Departamento de Arquitectura de Computadores y Automática, leída el 20-06-2013Depto. de Arquitectura de Computadores y AutomáticaFac. de InformáticaTRUEunpu

Développement d'architectures HW/SW tolérantes aux fautes et auto-calibrantes pour les technologies Intégrées 3D

Malgré les avantages de l'intégration 3D, le test, le rendement et la fiabilité des Through-Silicon-Vias (TSVs) restent parmi les plus grands défis pour les systèmes 3D à base de Réseaux-sur-Puce (Network-on-Chip - NoC). Dans cette thèse, une stratégie de test hors-ligne a été proposé pour les interconnections TSV des liens inter-die des NoCs 3D. Pour le TSV Interconnect Built-In Self-Test (TSV-IBIST) on propose une nouvelle stratégie pour générer des vecteurs de test qui permet la détection des fautes structuraux (open et short) et paramétriques (fautes de délaye). Des stratégies de correction des fautes transitoires et permanents sur les TSV sont aussi proposées aux plusieurs niveaux d'abstraction: data link et network. Au niveau data link, des techniques qui utilisent des codes de correction (ECC) et retransmission sont utilisées pour protégé les liens verticales. Des codes de correction sont aussi utilisés pour la protection au niveau network. Les défauts de fabrication ou vieillissement des TSVs sont réparé au niveau data link avec des stratégies à base de redondance et sérialisation. Dans le réseau, les liens inter-die défaillante ne sont pas utilisables et un algorithme de routage tolérant aux fautes est proposé. On peut implémenter des techniques de tolérance aux fautes sur plusieurs niveaux. Les résultats ont montré qu'une stratégie multi-level atteint des très hauts niveaux de fiabilité avec un cout plus bas. Malheureusement, il n'y as pas une solution unique et chaque stratégie a ses avantages et limitations. C'est très difficile d'évaluer tôt dans le design flow les couts et l'impact sur la performance. Donc, une méthodologie d'exploration de la résilience aux fautes est proposée pour les NoC 3D mesh.3D technology promises energy-efficient heterogeneous integrated systems, which may open the way to thousands cores chips. Silicon dies containing processing elements are stacked and connected by vertical wires called Through-Silicon-Vias. In 3D chips, interconnecting an increasing number of processing elements requires a scalable high-performance interconnect solution: the 3D Network-on-Chip. Despite the advantages of 3D integration, testing, reliability and yield remain the major challenges for 3D NoC-based systems. In this thesis, the TSV interconnect test issue is addressed by an off-line Interconnect Built-In Self-Test (IBIST) strategy that detects both structural (i.e. opens, shorts) and parametric faults (i.e. delays and delay due to crosstalk). The IBIST circuitry implements a novel algorithm based on the aggressor-victim scenario and alleviates limitations of existing strategies. The proposed Kth-aggressor fault (KAF) model assumes that the aggressors of a victim TSV are neighboring wires within a distance given by the aggressor order K. Using this model, TSV interconnect tests of inter-die 3D NoC links may be performed for different aggressor order, reducing test times and circuitry complexity. In 3D NoCs, TSV permanent and transient faults can be mitigated at different abstraction levels. In this thesis, several error resilience schemes are proposed at data link and network levels. For transient faults, 3D NoC links can be protected using error correction codes (ECC) and retransmission schemes using error detection (Automatic Retransmission Query) and correction codes (i.e. Hybrid error correction and retransmission).For transients along a source-destination path, ECC codes can be implemented at network level (i.e. Network-level Forward Error Correction). Data link solutions also include TSV repair schemes for faults due to fabrication processes (i.e. TSV-Spare-and-Replace and Configurable Serial Links) and aging (i.e. Interconnect Built-In Self-Repair and Adaptive Serialization) defects. At network-level, the faulty inter-die links of 3D mesh NoCs are repaired by implementing a TSV fault-tolerant routing algorithm. Although single-level solutions can achieve the desired yield / reliability targets, error mitigation can be realized by a combination of approaches at several abstraction levels. To this end, multi-level error resilience strategies have been proposed. Experimental results show that there are cases where this multi-layer strategy pays-off both in terms of cost and performance. Unfortunately, one-fits-all solution does not exist, as each strategy has its advantages and limitations. For system designers, it is very difficult to assess early in the design stages the costs and the impact on performance of error resilience. Therefore, an error resilience exploration (ERX) methodology is proposed for 3D NoCs.SAVOIE-SCD - Bib.électronique (730659901) / SudocGRENOBLE1/INP-Bib.électronique (384210012) / SudocGRENOBLE2/3-Bib.électronique (384219901) / SudocSudocFranceF