Design of TSV-sharing topologies for cost-effective 3D networks-on-chip

The Through-Silicon Via (TSV) technology has led to major breakthroughs in 3D stacking by providing higher speed and bandwidth, as well as lower power dissipation for the inter-layer communication. However, the current TSV fabrication suffers from a considerable area footprint and yield loss. Thus, it is necessary to restrict the number of TSVs in order to design cost-effective 3D on-chip networks. This critical issue can be addressed by clustering the network such that all of the routers within each cluster share a single TSV pillar for the vertical packet transmission. In some of the existing topologies, additional cluster routers are augmented into the mesh structure to handle the shared TSVs. However, they impose either performance degradation or power/area overhead to the system. Furthermore, the resulting architecture is no longer a mesh. In this paper, we redefine the clusters by replacing some routers in the mesh with the cluster routers, such that the mesh structure is preserved. The simulation results demonstrate a better equilibrium between performance and cost, using the proposed models

Exploring Adaptive Implementation of On-Chip Networks

As technology geometries have shrunk to the deep submicron regime, the communication delay and power consumption of global interconnections in high performance Multi- Processor Systems-on-Chip (MPSoCs) are becoming a major bottleneck. The Network-on- Chip (NoC) architecture paradigm, based on a modular packet-switched mechanism, can address many of the on-chip communication issues such as performance limitations of long interconnects and integration of large number of Processing Elements (PEs) on a chip. The choice of routing protocol and NoC structure can have a significant impact on performance and power consumption in on-chip networks. In addition, building a high performance, area and energy efficient on-chip network for multicore architectures requires a novel on-chip router allowing a larger network to be integrated on a single die with reduced power consumption. On top of that, network interfaces are employed to decouple computation resources from communication resources, to provide the synchronization between them, and to achieve backward compatibility with existing IP cores. Three adaptive routing algorithms are presented as a part of this thesis. The first presented routing protocol is a congestion-aware adaptive routing algorithm for 2D mesh NoCs which does not support multicast (one-to-many) traffic while the other two protocols are adaptive routing models supporting both unicast (one-to-one) and multicast traffic. A streamlined on-chip router architecture is also presented for avoiding congested areas in 2D mesh NoCs via employing efficient input and output selection. The output selection utilizes an adaptive routing algorithm based on the congestion condition of neighboring routers while the input selection allows packets to be serviced from each input port according to its congestion level. Moreover, in order to increase memory parallelism and bring compatibility with existing IP cores in network-based multiprocessor architectures, adaptive network interface architectures are presented to use multiple SDRAMs which can be accessed simultaneously. In addition, a smart memory controller is integrated in the adaptive network interface to improve the memory utilization and reduce both memory and network latencies. Three Dimensional Integrated Circuits (3D ICs) have been emerging as a viable candidate to achieve better performance and package density as compared to traditional 2D ICs. In addition, combining the benefits of 3D IC and NoC schemes provides a significant performance gain for 3D architectures. In recent years, inter-layer communication across multiple stacked layers (vertical channel) has attracted a lot of interest. In this thesis, a novel adaptive pipeline bus structure is proposed for inter-layer communication to improve the performance by reducing the delay and complexity of traditional bus arbitration. In addition, two mesh-based topologies for 3D architectures are also introduced to mitigate the inter-layer footprint and power dissipation on each layer with a small performance penalty.Siirretty Doriast

Non-acted multi-view audio-visual dyadic interactions. Project non-verbal emotion recognition in dyadic scenarios and speaker segmentation

Treballs finals del Màster de Fonaments de Ciència de Dades, Facultat de matemàtiques, Universitat de Barcelona, Any: 2019, Tutor: Sergio Escalera Guerrero i Cristina Palmero[en] In particular, this Master Thesis is focused on the development of baseline Emotion Recognition System in a dyadic environment using raw and handcraft audio features and cropped faces from the videos. This system is analyzed at frame and utterance level without temporal information. As well, a baseline Speaker Segmenta- tion System has been developed to facilitate the annotation task. For this reason, an exhaustive study of the state-of-the-art on emotion recognition and speaker segmentation techniques has been conducted, paying particular attention on Deep Learning techniques for emotion recognition and clustering for speaker aegmentation. While studying the state-of-the-art from the theoretical point of view, a dataset consisting of videos of sessions of dyadic interactions between individuals in different scenarios has been recorded. Different attributes were captured and labelled from these videos: body pose, hand pose, emotion, age, gender, etc. Once the ar- chitectures for emotion recognition have been trained with other dataset, a proof of concept is done with this new database in order to extract conclusions. In addition, this database can help future systems to achieve better results. A large number of experiments with audio and video are performed to create the emotion recognition system. The IEMOCAP database is used to perform the training and evaluation experiments of the emotion recognition system. Once the audio and video are trained separately with two different architectures, a fusion of both methods is done. In this work, the importance of preprocessing data (face detection, windows analysis length, handcrafted features, etc.) and choosing the correct parameters for the architectures (network depth, fusion, etc.) has been demonstrated and studied. On the other hand, the experiments for the speaker segmentation system are performed with a piece of audio from IEMOCAP database. In this work, the prerprocessing steps, the problems of an unsupervised system such as clustering and the feature representation are studied and discussed. Finally, the conclusions drawn throughout this work are exposed, as well as the possible lines of future work including new systems for emotion recognition and the experiments with the database recorded in this work

Self-consistent field approach to protein structure and stability

The organization of the thesis is as follows: after a short introduction (chapter 1), chapter 2 presents a review of the basic physical principle that govern protein structure and focuses on the thermodynamics as well as kinetics of protein folding and ufolding. Then chapter 3 starts with a discussion on the basic elementary interactions, which contribute, to protein structure and stability, with emphasis on the electrostatic interactions.Electrostatic interactions are described on the basis of novel approach, which uses the idea of a self-consistent field adapted from statistical mechanics. Properties such as titration curves, protein stability and pKa shifts are discussed. The main conclusions are: firstly, the calculated results are in excellent agreement with the experimental data, when the solution of Poisson-Boltzmann equation (PB) is based on the assumption that the ionized residues are seen as part of the high dielectric medium (rather than the interior of the protein molecule); Secondly, the solution of PB equation outside the protein interior, depends on local characteristics, such as the packing of chain portions around ionized residues, rather than on the detailed shape of the protein molecule. Lastly, at "natural-like" conditions the contribution of electrostatic interactions to the free energy difference between the unfolded and folded states of protein molecules is closed to zero. This indicates that the main driving forces for folding of protein molecules under these conditions are hydrophobic and backbone-backbone hydrogen bonding interactions.Chapter 4 concern the application of the theory of electrostatic interactions to the calculation of the pKa's of the 98 residue b-elicitin protein, cryptogein. Unusual in this protein is the existence of four ionized groups buried in the hydrophobic core. The NMR structure of the 98 residue b-elicitin, cryptogein was determined using and labelled protein samples. Calculation of theoretical pKa's show general agreement with experimentally determined values and is similar for both thecrystal and solution structures.In chapter 5 the topological requirement for nucleus formation of a two-state folding reaction is considered. The self-consistent field approach is used to calculate the free energy of the folding nucleus and to approximate the description of the elementary long-range interactions such as hydrogen-bonding, electrostatic and hydrophobic interactions. The local interactions between residues, which are close in sequence - as in the a-, b- or loop regions- are accounted for in an explicit form based on experimental parameters. A theoretical model for the folding of two-state small monomeric proteins is proposed. The folding problem is reduced to the question of how the folding nucleus in the transition state (TS) is formed from the ensemble of rapidly interconverting, partly structured conformations in the denatured state.It is proposed that in the denatured state the folding is energetically favored by certain highly fluctuating nucleation regions (aa b- hairpins). In experiments based on site directed mutagenesis these nucleation regions are revealed by their high F-values. In the TS folding is favored by the packing of these nucleation regions together with other portions of the polypeptide chain thus leading to a broad distribution of the F-values. As a result, the folding nucleus with native-like topology and approximately correctly formed secondary structures and loops is favored over other folding nuclei.In chapter 6 a discussion of the problem of protein fold recognition of small monomeric proteins with less than 80 residues is presented. The fold recognition strategy is based on the fact that: firstly, at the transition state level all possible protein conformations can be split out into different ensembles of similar structures. The crude characteristics of these ensembles can be described by the limited set of thermodynamically most favorable protein folds; secondly, the folding nucleus with native-like overall fold is separated from all other folding alternatives by a high free energy barrier. As a result, at the lowest free energy minimum of the TS state the protein molecules propagates toward its native state approximately isoenergetically through an ensemble of conformations of its native fold. The main contributions, which stabilize the protein folds at the TS level, are the hydrophobic and long-range backbone hydrogen bonding interactions, as well as the free energy of chain bending, and free energies of secondary structures formation.The selection of the protein architectures is mainly determined by the most general characteristics encoded in the protein sequence, such as distribution of hydrophobic and hydrophilic residues along the chain, the ability of amino acids to form different secondary structures in compact chain conformations by hydrogen bonding with their spatial or chain neighbours, and the general rules which govern the packing of the secondary structures. At the TS, the free energies of the native folds are separated by a 'gap' from the lowest free energies of the folds from structurally different packing patterns. However, the difference between the free energies of the native folds and the lowest free energies of the folds from the same packing pattern is rather small. The thesis is concluded with a summary in English, Dutch and Bulgarian.</p

Planning and Scheduling Optimization

Although planning and scheduling optimization have been explored in the literature for many years now, it still remains a hot topic in the current scientific research. The changing market trends, globalization, technical and technological progress, and sustainability considerations make it necessary to deal with new optimization challenges in modern manufacturing, engineering, and healthcare systems. This book provides an overview of the recent advances in different areas connected with operations research models and other applications of intelligent computing techniques used for planning and scheduling optimization. The wide range of theoretical and practical research findings reported in this book confirms that the planning and scheduling problem is a complex issue that is present in different industrial sectors and organizations and opens promising and dynamic perspectives of research and development