Edge AI: Deep Learning techniques for Computer Vision applied to embedded systems

In the last decade, Machine Learning techniques have been used in different fields, ranging from finance to healthcare and even marketing. Amongst all these techniques, the ones adopting a Deep Learning approach were revealed to outperform humans in tasks such as object detection, image classification and speech recognition. This thesis introduces the concept of Edge AI: that is the possibility to build learning models capable of making inference locally, without any dependence on expensive servers or cloud services. A first case study we consider is based on the Google AIY Vision Kit, an intelligent camera equipped with a graphic board to optimize Computer Vision algorithms. Then, we test the performances of CORe50, a dataset for continuous object recognition, on embedded systems. The techniques developed in these chapters will be finally used to solve a challenge within the Audi Autonomous Driving Cup 2018, where a mobile car equipped with a camera, sensors and a graphic board must recognize pedestrians and stop before hitting them

Approche efficace pour la conception des architectures multiprocesseurs sur puce électronique

Les systèmes multiprocesseurs sur puce électronique (On-Chip Multiprocessor [OCM]) sont considérés comme les meilleures structures pour occuper l'espace disponible sur les circuits intégrés actuels. Dans nos travaux, nous nous intéressons à un modèle architectural, appelé architecture isométrique de systèmes multiprocesseurs sur puce, qui permet d'évaluer, de prédire et d'optimiser les systèmes OCM en misant sur une organisation efficace des nœuds (processeurs et mémoires), et à des méthodologies qui permettent d'utiliser efficacement ces architectures. Dans la première partie de la thèse, nous nous intéressons à la topologie du modèle et nous proposons une architecture qui permet d'utiliser efficacement et massivement les mémoires sur la puce. Les processeurs et les mémoires sont organisés selon une approche isométrique qui consiste à rapprocher les données des processus plutôt que d'optimiser les transferts entre les processeurs et les mémoires disposés de manière conventionnelle. L'architecture est un modèle maillé en trois dimensions. La disposition des unités sur ce modèle est inspirée de la structure cristalline du chlorure de sodium (NaCl), où chaque processeur peut accéder à six mémoires à la fois et où chaque mémoire peut communiquer avec autant de processeurs à la fois. Dans la deuxième partie de notre travail, nous nous intéressons à une méthodologie de décomposition où le nombre de nœuds du modèle est idéal et peut être déterminé à partir d'une spécification matricielle de l'application qui est traitée par le modèle proposé. Sachant que la performance d'un modèle dépend de la quantité de flot de données échangées entre ses unités, en l'occurrence leur nombre, et notre but étant de garantir une bonne performance de calcul en fonction de l'application traitée, nous proposons de trouver le nombre idéal de processeurs et de mémoires du système à construire. Aussi, considérons-nous la décomposition de la spécification du modèle à construire ou de l'application à traiter en fonction de l'équilibre de charge des unités. Nous proposons ainsi une approche de décomposition sur trois points : la transformation de la spécification ou de l'application en une matrice d'incidence dont les éléments sont les flots de données entre les processus et les données, une nouvelle méthodologie basée sur le problème de la formation des cellules (Cell Formation Problem [CFP]), et un équilibre de charge de processus dans les processeurs et de données dans les mémoires. Dans la troisième partie, toujours dans le souci de concevoir un système efficace et performant, nous nous intéressons à l'affectation des processeurs et des mémoires par une méthodologie en deux étapes. Dans un premier temps, nous affectons des unités aux nœuds du système, considéré ici comme un graphe non orienté, et dans un deuxième temps, nous affectons des valeurs aux arcs de ce graphe. Pour l'affectation, nous proposons une modélisation des applications décomposées en utilisant une approche matricielle et l'utilisation du problème d'affectation quadratique (Quadratic Assignment Problem [QAP]). Pour l'affectation de valeurs aux arcs, nous proposons une approche de perturbation graduelle, afin de chercher la meilleure combinaison du coût de l'affectation, ceci en respectant certains paramètres comme la température, la dissipation de chaleur, la consommation d'énergie et la surface occupée par la puce. Le but ultime de ce travail est de proposer aux architectes de systèmes multiprocesseurs sur puce une méthodologie non traditionnelle et un outil systématique et efficace d'aide à la conception dès la phase de la spécification fonctionnelle du système.On-Chip Multiprocessor (OCM) systems are considered to be the best structures to occupy the abundant space available on today integrated circuits (IC). In our thesis, we are interested on an architectural model, called Isometric on-Chip Multiprocessor Architecture (ICMA), that optimizes the OCM systems by focusing on an effective organization of cores (processors and memories) and on methodologies that optimize the use of these architectures. In the first part of this work, we study the topology of ICMA and propose an architecture that enables efficient and massive use of on-chip memories. ICMA organizes processors and memories in an isometric structure with the objective to get processed data close to the processors that use them rather than to optimize transfers between processors and memories, arranged in a conventional manner. ICMA is a mesh model in three dimensions. The organization of our architecture is inspired by the crystal structure of sodium chloride (NaCl), where each processor can access six different memories and where each memory can communicate with six processors at once. In the second part of our work, we focus on a methodology of decomposition. This methodology is used to find the optimal number of nodes for a given application or specification. The approach we use is to transform an application or a specification into an incidence matrix, where the entries of this matrix are the interactions between processors and memories as entries. In other words, knowing that the performance of a model depends on the intensity of the data flow exchanged between its units, namely their number, we aim to guarantee a good computing performance by finding the optimal number of processors and memories that are suitable for the application computation. We also consider the load balancing of the units of ICMA during the specification phase of the design. Our proposed decomposition is on three points: the transformation of the specification or application into an incidence matrix, a new methodology based on the Cell Formation Problem (CFP), and load balancing processes in the processors and data in memories. In the third part, we focus on the allocation of processor and memory by a two-step methodology. Initially, we allocate units to the nodes of the system structure, considered here as an undirected graph, and subsequently we assign values to the arcs of this graph. For the assignment, we propose modeling of the decomposed application using a matrix approach and the Quadratic Assignment Problem (QAP). For the assignment of the values to the arcs, we propose an approach of gradual changes of these values in order to seek the best combination of cost allocation, this under certain metric constraints such as temperature, heat dissipation, power consumption and surface occupied by the chip. The ultimate goal of this work is to propose a methodology for non-traditional, systematic and effective decision support design tools for multiprocessor system architects, from the phase of functional specification

Development of decellularised porcine osteochondral scaffolds as matrices for cell implantation

Osteoarthritis currently affects 8.75 million people in the UK alone. This can cause major issues for those living with the disease, such as immobility and pain, which are often accompanied with psychological distress due to a loss in quality of life. One cause of osteoarthritis is damage to the articular cartilage which triggers inflammation and progressive degeneration. Early intervention strategies are employed to prevent disease progression such as microfracture, mosaicplasty and more recently autologous chondrocyte implantation. However, these all have their limitations in either, insufficient quality of repair material, donor site morbidity or limited biomechanical function prior to tissue regeneration. This study first aimed to investigate the applicability of decellularised porcine osteochondral scaffolds in the treatment of large shallow cartilage lesions. This project built upon previous work, with an aim of enhancing these scaffolds through application with chondrocytes and self-assembling peptide hydrogel with chondroitin sulphate (P11-8/CS) incorporated. The hypothesis was that the resultant scaffold would be an ideal tissue replacement due to the retained native extracellular matrix structure, the increased regenerative potential offered by the cells and the enhanced biomechanical function from the addition of SAP-CS. These benefits, would ideally allow faster restoration of the healthy biomechanical function of the joint. Potential for cost-effectiveness versus matrix assisted chondrocyte implantation was observed. The dimensions of the decellularised scaffolds were adapted to dimensions which are clinically appropriate for the treatment of large shallow lesions. The resultant decellularisation quality, cytocompatibility and mechanical properties were all conserved, despite larger dimensions. Following this, a recellularization process was established for these decellularised scaffolds based using lyophilisation to increase cell penetration. These scaffolds were evaluated in a natural knee joint simulation model, which indicated viability of recellularised chondrocytes at Day 7. Following this, the ability of the P11-8/CS hydrogel alone to support chondrocyte cell proliferation and survival over a 14-day timecourse was demonstrated, whilst chondrogenic gene expression of encapsulated primary porcine chondrocytes was shown. The lyophilisation method was then developed to deliver SAP-GAG to the osteochondral scaffolds, which showed a trend for improved biomechanical properties. Overall, this work has shown the potential for both recellularised decellularised scaffolds and self-assembling peptides, as devices to support chondrocyte implantation to aid the regeneration of large shallow cartilage lesions and early stage lesions respectively