International Professional University of Technology in Nagoya Repository
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Napier, John
No full textInternational audienceBiographical entry for John Napier, inventor of logarithm
Analytical modeling of losses in FDP protocol of HbbTV based push-VOD services over DVB networks
No full textInternational audienceHybrid broadcast broadband TV (HbbTV) is a technique providing Push-VOD services over an interactive hybrid TV. These services are broadcast using File Delivery Protocol (FDP) characterized by three levels of data represen- tation and give rise to three loss distribution that may result in QoS degradation and poor Forward Error Correction (FEC) recovery capabilities (if FEC is used within FDP). In this paper, we address for the first time the issue of depth analysis of loss propagation within FDP system to understand and foretell the perceptual VOD quality and the FEC behavior at receiver side. We first propose analytical models based on Markov chains to accurately predict the losses and the burstiness along the FDP system levels allowing to avoid the analysis by experimental NP-hard method. Then, based on simulation, we validate the proposed models for all tested average loss rates and average burst loss lengths. Finally, we show that the proposed Markov models allow to guess ahead effectively VOD QoS and FEC behavior. © 2017 IEEE
Analysis of a heterogeneous multi-core, multi-hw-accelerator-based system designed using PREESM and SDSoC
No full textInternational audienceNowadays, new heterogeneous system technologies are flooding the market: through the past years, it is possible to observe the move from single CPUs to multi-core devices featuring CPUs, GPUs and large FPGAs, such as Xilinx Zynq-7000 or Zynq UltraScale+ MPSoC architectures. In this context, providing developers with transparent deployment capabilities to efficiently execute different applications on such complex devices is important. In this paper, a design flow that combines, on one side, PREESM, a dataflow-based prototyping framework and, on the other side, Xilinx SDSoC, an HLS-based framework to automatically generate and manage hardware accelerators, is presented. This integration leverages the automatic, static task scheduling obtained from PREESM with asynchronous invocations that trigger the parallel execution of multiple hardware accelerators from some of their associated sequential software threads. An image processing application is used as a proof of concept, showing the interoperability possibilities of both tools, the level of design automation achieved and, for the resulting computing architecture, the good performance scalability according to the number of accelerators and sw threads. © 2017 IEEE
Evaluation of single-artifact based video quality metrics in video communication context
No full textInternational audienceFor an accurate assessment of media quality, it is essential not only to compute an overall quality measure, but also to identify the type of occurring distortions. In this paper, we focus on a set of no-reference single-artifact based metrics developed by the MOAVI project. We carried out a correlation analysis in order to evaluate the performance of these metrics on three databases with a large sample of distortion types. This study will be used for setting up a video quality monitoring tool box. © 2017 IEEE
Optimizing Context-Aware Resource and Network Assignment in Heterogeneous Wireless Networks
No full textInternational audienceThis paper discusses the problem of user association and downlink resource allocation in heterogeneous wireless networks (HWNs) where a mobile node (MN) can associate to a single network at a time. A context-aware optimization problem is formulated to maximize the aggregate user-centric profit in the system while taking into consideration the network constraints, user preferences, and the amount of data rate requested by each MN. To achieve its purpose, the formulated problem employs contextual information related to the MN measurements and requirements, the HWN architecture, and the available resources at each network. The user-centric profit is based on the quality of the received signal and the power consumption at the MN. The formulated optimization problem is discrete (binary) with high complexity; based on the continuous relaxation of the problem, a solution with polynomial-time complexity is proposed. It is shown through simulations that the proposed solution achieves a near-optimal performance in terms of average user-centric profit and percentage of blocked data rate. Moreover, the proposed solution requests lower number of handovers
DEMOS : a Domain dEcomposition MOdel for Scattering in forest environments compared with mono and bistatic measurements on scaled models
No full textInternational audienceWe developed an efficient model to evaluate the electromagnetic scattering from large scenes composed by targets (metallic objects) placed in natural environment (dielectric object). Our model, named DEMOS, is a hybrid volume/surface model that integrate both metallic and dielectric scatterers. In this paper we compare the scattered field obtained with DEMOS with measurements done in an anechoïc chamber on scaled models composed of dielectric and metallic structures
Lexicographic Relay Selection and Channel Allocation for Multichannel Cooperative Multicast
No full textInternational audienceCooperative multicast has been demonstrated to achieve significant performance gain over the classic source-destination transmission paradigm by exploiting spatial diversity through the participation of multiple relay nodes. As a major technical challenge, the selection of relays for a multicast session has significant impact on the multicast performance. The challenge is even more pronounced when the number of channels are limited as the relay selection is in this context coupled with channel allocation. We establish an analytical framework for joint relay selection and channel allocation problem and develop a lexicographic max-min multicast relay selection scheme. Our design consists of two technical steps. 1) We consider the maximization of the minimal data rate. By decoupling relay selection and channel allocation, the problem is transformed to a max-min-max problem, which is difficult to solve. To make this problem tractable, we reformulate it as a convex optimization problem via relaxation and smoothing, and prove the asymptotic equivalence from a geometrical perspective. 2) We propose an adjustment algorithm based on the initial max-min solution, and prove that the proposed scheme achieves lexicographic optimality
Localisation de Source par les Systèmes MIMO
No full textSources localization is used in radar, sonar, andtelecommunication. Radar has numerous civilian andmilitary applications. Radar system has gone throughmany developments over the last few decades andreached the latest version known as MIMO radar. AMIMO radar is composed of multiple transmitting andreceiving antennas like a conventional phased arrayradar. However, its transmitting antennas transmit linearlyindependent signals so that they can be easilyidentified by the matched filters bank at its receivingend. The matched filtered signals are then processedto extract the ranges, DOAs, DODs, velocities, etc. ofthe targets. A bistatic MIMO radar system provideshigh resolution, spatial diversity, parameter identifiability,etc. which inspired us to use it in this work. Thereare many existing methods to deal with the far field regionof MIMO radar system. However, little work canbe found on the near field region of a bistatic MIMOradar which motivated the work in this thesis. Nearfield targets localization is also important because ofmany indoor applications. Most of the existing nearfield sources localization techniques use Fresnel approximationin which the real spherical wavefront is assumedquadric unlike planar in far field situation. Inthis work we have proposed a novel near field targetslocalization method using Fresnel approximation. TheFresnel approximation leads to a biased estimation ofthe location parameters because the true wavefront isspherical. Consequently, we have proposed two correctionmethods to reduce the effects of Fresnel approximationand other two methods which directly usethe exact signal model based on spherical wavefront.Dans cette thèse, nous considérons la dernière générationdu radar. Il s’agit d’un radar MIMO bistatiquequi est composé de plusieurs antennes d’émission etde réception. Pour ce système, les antennes émettricestransmettent des signaux linéairement indépendantsafin qu’ils puissent être identifiés à l’aide d’unbanc de filtres adaptés au niveau des antennes deréception. Les signaux filtrés sont alors traités pourextraire les paramètres des cibles, tels que les DOA,DOD, vitesse, etc. Un radar MIMO bistatique offre unegrande diversité spatiale et une excellente identifiabilitédes paramètres, etc., ce qui nous a incités à l’utiliserdans ce travail. La situation en champ lointaind’un radar MIMO bistatique est largement traitée dansla littérature. Mais, peu de travaux existe sur la situationen champ proche, c’est ce qui a motivé le travailde cette thèse. La localisation de cibles en champproche est importante en raison de nombreuses applicationsà l’intérieur des constructions. A ce sujet, laplupart des méthodes actuelles utilisent l’approximationde Fresnel dans laquelle le front d’onde sphériquedes signaux reçus est supposé quadrique plutôt queplanaire comme en champ lointain. Dans ce travail dethèse, nous avons proposé une nouvelle méthode delocalisation des cibles en champ proche qui utilise l’approximationde Fresnel. Celle-ci conduit à une estimationbiaisée des paramètres de localisation car en réalitéle front d’onde est sphérique. Nous avons proposéalors deux méthodes de correction pour réduire les effetsde l’approximation de Fresnel et deux autres méthodesqui utilisent directement le modèle exacte basésur le front d’onde sphérique
Mass spectrometry as a versatile ancillary technique for the rapid in situ identification of lichen metabolites directly from TLC plates
No full textInternational audienceThin-layer chromatography (TLC) still enjoys widespread popularity among lichenologists as one of the fastest and simplest analytical strategies, today remaining the primary method of assessing the secondary product content of lichens. The pitfalls associated with this approach are well known as TLC leads to characterizing compounds by comparison with standards rather than properly identifying them, which might lead to erroneous assignments, accounting for the long-held interest in hyphenating TLC with dedicated identification tools. As such, commercially available TLC/Mass Spectrometry (MS) interfaces can be easily connected to any brand of mass spectrometer without adjustments. The spots of interest are extracted from the TLC plate to retrieve mass spectrometric signals within one minute, thereby ensuring accurate identification of the chromatographed substances. The results of this hyphenated strategy for lichens are presented here by 1) describing the TLC migration and direct MS analysis of single lichen metabolites of various structural classes, 2) highlighting it through the chemical profiling of crude acetone extracts of a set of lichens of known chemical composition, and finally 3) applying it to a lichen of unknown profile, Usnea trachycarpa
Un solveur parallèle itératif pour les grands systèmes linéaires creux, amélioré par la randomisation et l'utilisation des accélérateurs GPU, et sa résilience aux fautes logicielles
No full textIn this PhD thesis, we address three challenges faced by linear algebra solvers in the perspective of future exascale systems: accelerating convergence using innovative techniques at the algorithm level, taking advantage of GPU (Graphics Processing Units) accelerators to enhance the performance of computations on hybrid CPU/GPU systems, evaluating the impact of errors in the context of an increasing level of parallelism in supercomputers. We are interested in studying methods that enable us to accelerate convergence and execution time of iterative solvers for large sparse linear systems. The solver specifically considered in this work is the parallel Algebraic Recursive Multilevel Solver (pARMS), which is a distributed-memory parallel solver based on Krylov subspace methods.First we integrate a randomization technique referred to as Random Butterfly Transformations (RBT) that has been successfully applied to remove the cost of pivoting in the solution of dense linear systems. Our objective is to apply this method in the ARMS preconditioner to solve more efficiently the last Schur complement system in the application of the recursive multilevel process in pARMS. The experimental results show an improvement of the convergence and the accuracy. Due to memory concerns for some test problems, we also propose to use a sparse variant of RBT followed by a sparse direct solver (SuperLU), resulting in an improvement of the execution time.Then we explain how a non intrusive approach can be applied to implement GPU computing into the pARMS solver, more especially for the local preconditioning phase that represents a significant part of the time to compute the solution. We compare the CPU-only and hybrid CPU/GPU variant of the solver on several test problems coming from physical applications. The performance results of the hybrid CPU/GPU solver using the ARMS preconditioning combined with RBT, or the ILU(0) preconditioning, show a performance gain of up to 30% on the test problems considered in our experiments.Finally we study the effect of soft fault errors on the convergence of the commonly used flexible GMRES (FGMRES) algorithm which is also used to solve the preconditioned system in pARMS. The test problem in our experiments is an elliptical PDE problem on a regular grid. We consider two types of preconditioners: an incomplete LU factorization with dual threshold (ILUT), and the ARMS preconditioner combined with RBT randomization. We consider two soft fault error modeling approaches where we perturb the matrix-vector multiplication and the application of the preconditioner, and we compare their potential impact on the convergence of the solver.Dans cette thèse de doctorat, nous abordons trois défis auxquels sont confrontés les solveurs d'algèbres linéaires dans la perspective des futurs systèmes exascale: accélérer la convergence en utilisant des techniques innovantes au niveau algorithmique, en profitant des accélérateurs GPU (Graphics Processing Units) pour améliorer le calcul sur plusieurs systèmes, en évaluant l'impact des erreurs due à l'augmentation du parallélisme dans les superordinateurs. Nous nous intéressons à l'étude des méthodes permettant d'accélérer la convergence et le temps d'exécution des solveurs itératifs pour les grands systèmes linéaires creux. Le solveur plus spécifiquement considéré dans ce travail est le “parallel Algebraic Recursive Multilevel Solver (pARMS)” qui est un soldeur parallèle sur mémoire distribuée basé sur les méthodes de sous-espace de Krylov.Tout d'abord, nous proposons d'intégrer une technique de randomisation appelée “Random Butterfly Transformations (RBT)” qui a été proposée avec succès pour éliminer le coût du pivotage dans la résolution des systèmes linéaires denses. Notre objectif est d'appliquer cette technique dans le préconditionneur ARMS de pARMS pour résoudre plus efficacement le dernier système Complément de Schur dans l'application du processus à multi-niveaux récursif. En raison de l'importance considérable du dernier Complément de Schur pour certains problèmes de test, nous proposons également d'utiliser une variante creux de RBT suivie d'un solveur direct creux (SuperLU). Les résultats expérimentaux sur certaines matrices de la collection de Davis montrent une amélioration de la convergence et de la précision par rapport aux implémentations existantes.Ensuite, nous illustrons comment une approche non intrusive peut être appliquée pour implémenter des calculs GPU dans le solveur pARMS, plus particulièrement pour la phase de préconditionnement locale qui représente une partie importante du temps pour la résolution. Nous comparons les solveurs purement CPU avec les solveurs hybrides CPU / GPU sur plusieurs problèmes de test issus d'applications physiques. Les résultats de performance du solveur hybride CPU / GPU utilisant le préconditionnement ARMS combiné avec RBT, ou le préconditionnement ILU(0), montrent un gain de performance jusqu'à 30% sur les problèmes de test considérés dans nos expériences.Enfin, nous étudions l'effet des défaillances logicielles variable sur la convergence de la méthode itérative flexible GMRES (FGMRES) qui est couramment utilisée pour résoudre le système préconditionné dans pARMS. Le problème ciblé dans nos expériences est un problème elliptique PDE sur une grille régulière. Nous considérons deux types de préconditionneurs: une factorisation LU incomplète à double seuil (ILUT) et le préconditionneur ARMS combiné avec randomisation RBT. Nous considérons deux modèle de fautes logicielles différentes où nous perturbons la multiplication du vecteur matriciel et la phase de préconditionnement, et nous comparons leur impact potentiel sur la convergence