La conception d'applications scientifiques à base de couplage de code est une tâche complexe car elle demande de concilier une facilité de programmation et une obtention de haute performance. En outre, les ressources matérielles (supercalculateurs, grappes de calcul, grilles) permettant leur exécution forment un ensemble hétérogène en constante évolution. Les modèles à base de composants logiciels forment une piste prometteuse pour gérer ces deux sources de complexité car ils permettent d’exprimer les interactions entre les différents constituants d’une application tout en offrant des possibilités d'abstraction des ressources. Néanmoins, les modèles existants ne permettent pas d'exprimer de manière satisfaisante les applications constituées de motifs répliqués dynamiques et hiérarchiques. Ainsi, cette thèse vise à améliorer l'existant – et en particulier la plate-forme générique de simulation numérique SALOME – pour une classe d'applications très répandue : les applications à base de décomposition de domaine et la variante utilisant le raffinement de maillage adaptatif. Tout d'abord, nous avons proposé d’étendre le modèle de composition spatial et temporel de SALOME en ajoutant la possibilité de définir dynamiquement la cardinalité des composants. Cela demande en particulier de gérer les communications de groupes ainsi induites. La proposition a été implémentée dans SALOME et validée via une application de décomposition de domaine à base de couplage de plusieurs instances de Code_Aster. Ensuite, nous avons étudié la pertinence d'utiliser un modèle de composant supportant des connecteurs natifs (MPI, mémoire partagée, appel de méthode) pour permettre une composition plus fine des interactions entre composants. Les résultats d'expériences montrent que des performances équivalentes aux versions natives sont obtenues tout en permettant de manipuler facilement l'architecture de l'application. Enfin, nous avons étudié les extensions nécessaires aux modèles à composants (abstraction,hiérarchie, dynamicité) pour la conception d’applications de raffinement de maillage adaptatif. Les modèles de composants spatio-temporels les plus avancés permettent ainsi d'exprimer ce type d'application mais les performances sont limitées par leur mise en œuvre centralisée ainsi que par le manque de moyens efficaces pour modifier à la volée des assemblages de composants. / Designing scientific applications based on code coupling is a complex task. It requires both an easy programming process and high-performance. In addition, execution resources (supercomputers, computer clusters, grids)  are heterogeneous and constantly evolving. Software components models offer a promising perspective to manage this double complexity because they can express interactions between the different parts of an application while providing abstraction of resources. However, existing models cannot accurately express the applications made of dynamic and hierarchical patterns. The aim of this thesis is to improve the existing models, and in particular the generic platform for numerical simulation SALOME, for a class of widespread applications : applications based on domain decomposition, and its dynamic variant using adaptive mesh refinement. Firstly, we proposed to extend the spatial and temporal composition model provided by SALOME, by adding the ability to dynamically set component cardinality. This requires in particular to manage group communications induced. The proposal has been implemented into SALOME and validated via a domain decomposition application based on coupling several instances of Code_Aster.Then, we have studied the relevance of using a component model supporting native connectors (MPI, shared memory, method invocation), in order to allow finer composition interactions between components.The experiment results show that performances obtained are equivalent to those of the native versions, while allowing to easily manipulate the application architecture. Finally, we studied the necessary component models extensions (abstraction, hierarchy, dynamicity) for designing adaptative mesh refinement applications. The most advanced spatio-temporal component models can express this type of application but performances are limited by their centralized implementation and by the lack of efficient ways of modifying component assembling at execution time.

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Student Number : 0214677F - PhD thesis - School of Camputational and Applied Mathematics - Faculty of Science / Many real-life problems are formulated as global optimization problems with continuous variables. These problems are in most cases nonsmooth, nonconvex and often simulation based, making gradient based methods impossible to be used to solve them. Therefore, ef#2;cient, reliable and derivative-free global optimization methods for solving such problems are needed. In this thesis, we focus on improving the ef#2;ciency and reliability of some global optimization methods. In particular, we concentrate on improving some population set-based methods for unconstrained global optimization, mainly through hybridization. Hybridization has widely been recognized to be one of the most attractive areas of unconstrained global optimization. Experiments have shown that through hybridization, new methods that inherit the strength of the original elements but not their weakness can be formed. We suggest a number of new hybridized population set-based methods based on differential evolution (de), controlled random search (crs2) and real coded genetic algorithm (ga). We propose #2;ve new versions of de. In the #2;rst version, we introduce a localization, called random localization, in the mutation phase of de. In the second version, we propose a localization in the acceptance phase of de. In the third version, we form a de hybrid algorithm by probabilistically combining the point generation scheme of crs2 with that of de in the de algorithm. The fourth and #2;fth versions are also de hybrids. These versions hybridize the mutation of de with the point generation rule of the electromagnetism-like (em) algorithm. We also propose #2;ve new versions of crs2. The #2;rst version modi#2;es the point generation scheme of crs2 by introducing a local mutation technique. In the second and third modi#2;cations, we probabilistically combine the point generation scheme of crs2 with the linear interpolation scheme of a trust-region based method. The fourth version is a crs hybrid that probabilistically combines the quadratic interpolation scheme with the linear interpolation scheme in crs2. In the #2;fth version, we form a crs2 hybrid algorithm by probabilistically combining the point generation scheme of crs2 with that of de in the crs2 algorithm. Finally, we propose #2;ve new versions of the real coded genetic algorithm (ga) with arithmetic crossover. In the #2;rst version of ga, we introduce a local technique. We propose, in the second version, an integrated crossover rule that generates two children at a time using two different crossover rules. We introduce a local technique in the second version to obtain the third version. The fourth and #2;fth versions are based on the probabilistic adaptation of crossover rules. The ef#2;ciency and reliability of the new methods are evaluated through numerical experiments using a large test suite of both simple and dif#2;cult problems from the literature. Results indicate that the new hybrids are much better than their original counterparts both in reliability and ef#2;ciency. Therefore, the new hybrids proposed in this study offer an alternative to many currently available stochastic algorithms for solving global optimization problems in which the gradient information is not readily available.

Made available in DSpace on 2016-03-22T17:26:09Z (GMT). No. of bitstreams: 1 Vanessa_Souza_da_Fonseca.pdf: 1687661 bytes, checksum: 6dbf2a6dc47f997aa3e8aa0c8f37aced (MD5) Previous issue date: 2008-08-07 / This research describes the main contributions of the VirD-GM (Virtual Distributed Geometric Machine Model) for the model of parallelism and distribution of the Project D-GM (Distributed Geometric Machine Project). In order to provide the abstractions of the GM model (Geometric Machine) on a platform to support the implementation distributed and / or parallel computations, the middleware EXEHDA (Execution Environment for High Distributed Applications) is considered as the execution environment. The work enabled to create and manage an environment of parallel and directed programming, and promote the implementation, in this environment, of applications developed in the visual environment VPE-GM (Visual Programming Environment for the Geometric Machine Model). These applications are, by nature, parallel and restricted to the study of parallel algorithms for Scientific Computation. The work focuses on the design and construction of the software architecture of the VirD-GM, which is responsible for managing parallel computations obtained by the application of process constructors defined by the GM model. In this context, this research does not only disposes the construction of the structural vision of the project D-GM but also consolidates its integration with the functional vision. It is characterized by an extension of the visual environment VPEGM, which is responsible for the environment development and code generation for the Project D-GM. Among the main contributions, one may consider: (i) formalization of the concepts of concurrency and conflict intermittent with the notions of communication and synchronization of processes, directly related to the space-time structure of the GM model; (ii) modeling and implementation of the loading, management and control structures of the VirD-GM; (iii) implementation and customization of services provided by the EXEHDA; (iv) construction of the levels of applications, support of execution environment and basic systems; (v) data flow control and manipulation of adjacency matrix related to concurrent computations, including the implementation of barriers of synchronization. The prototyping of VirD-GM and avaliaton achieved through the development of test applications have implemented the viability of theoretical-practical approach proposed in Project D-GM / Este trabalho descreve as principais contribuic¸ oes da VirD-GM (Virtual Distributed Geometric Machine Model) para o modelo de distribuic¸ ao e paralelismo do Projeto D-GM (Distributed Geometric Machine Project). Para disponibilizar as abstrac¸ oes do modelo GM (Geometric Machine) em uma plataforma com suporte `a execuc¸ ao distribu ´ıda e/ou concorrente, considera-se o middleware EXEHDA ( Execution Environment for High Distributed Applications) como ambiente de suporte `a execuc¸ ao. O trabalho possibilitou criar e gerenciar um ambiente de programac¸ ao paralela e distribu´ıda, bem como promover a execuc¸ ao, sob este ambiente, das aplicac¸ oes desenvolvidas no ambiente visual VPE-GM (Visual Programming Environment for the Geometric Machine Model). Estas aplicac¸ oes s ao, por natureza, paralelas e direcionadas ao estudo de algoritmos paralelos para a Computac¸ ao Cient´ıfica. O trabalho est´a centrado na concepc¸ ao e construc¸ ao da arquitetura de software da VirD-GM, respons´avel pelo gerenciamento das computac¸ oes paralelas obtidas pela aplicac¸ ao de construtores de processos definidos no modelo GM. Neste contexto, esta dissertac¸ ao n ao s´o viabilizou construc¸ ao da vis ao estrutural do projeto D-GM como tamb´em consolidou sua integrac¸ ao com a vis ao funcional, caracterizada pela extens ao do ambiente VPE-GM, respons´avel pelo ambiente de desenvolvimento e gerac¸ ao de c´odigo para o Projeto D-GM. Dentre as principais contribuic¸ oes, destacam-se: (i) formalizac¸ ao das noc¸ oes de concorr encia e conflito intermitentes com as noc¸ oes de comunicac¸ ao e sincronizac¸ ao de processos, diretamente relacionadas com a estrutura espac¸o-temporal do modelo GM; (ii) definic¸ ao compreendendo a modelagem e implementac¸ ao dos m´odulos de carregamento, gerenciamento e controle da VirD-GM; (iii) estudo, aplicac¸ ao e customizac¸ ao dos servic¸os disponibilizados pelo middleware EXEHDA; (iv) implementac¸ ao das camadas de aplicac¸ ao, de suporte ao ambiente de execuc¸ ao e de sistemas b´asicos; (v) controle do fluxo de dados e manipulac¸ ao das depend encias entre as computac¸ oes concorrentes pelo uso de matrizes de adjac encias, incluindo a implementac¸ ao de barreiras de sincronizac¸ ao, garantindo a correta execuc¸ ao. A prototipac¸ ao da VirD-GM e a avaliac¸ ao obtida com o desenvolvimento de aplicac¸ oes de teste demonstraram a viabilidade da abordagem te´orica-pr´atica proposta no Projeto D-GM

Avec l’émergence de plates-formes distribuées très hétérogènes, dynamiques et à large-échelle, la nécessité d’un moyen de les programmer efficacement et de les gérer a surgi. Le concept de l’informatique autonomique propose de créer des systèmes autogérables — des systèmes qui sont conscients de leurs composants et de leur environnement, et peuvent se configurer, s’optimiser, se guérir et se protéger. Dans le cadre de la réalisation de tels systèmes, la programmation déclarative, dont l’objectif est de faciliter la tâche du programmeur en séparant le contrôle de la logique du calcul, a retrouvé beaucoup d’intérêt ce dernier temps. En particulier, la programmation à base de des règles est considérée comme un modèle prometteur dans cette quête pour des abstractions de programmation adéquates pour ces plates-formes. Cependant, bien que ces modèles gagnent beaucoup d’attention, ils créent une demande pour des outils génériques capables de les exécuter à large échelle. Le modèle de programmation chimique, qui a été conçu suite à la métaphore chimique, est un modéle de programmation à bas de règles et d’ordre supérieur, avec une exécution non-déterministe modèle, où les règles sont appliquées simultanément sur un multi-ensemble de données. Dans cette thèse, nous proposons la conception, le développement et l’expérimentation d’un intergiciel distribué pour l’exécution de programmes chimique sur des plates-formes à large échelle et génériques. L’architecture proposée combine une couche de communication pair-à-pair avec un protocole de capture atomique d’objets sur lesquels les règles doivent être appliquées, et un système efficace de détection de terminaison. Nous décrivons le prototype d’intergiciel mettant en œuvre cette architecture. Basé sur son déploiement dans un banc d’essai réel, nous présentons les résultats de performance, qui confirment les complexités analytiques obtenues et montrons expérimentalement la viabilité d’un tel modèle de programmation. / With the emergence of highly heterogeneous, dynamic and large distributed platforms, the need for a way to efficiently program and manage them has arisen. The concept of autonomic computing proposes to create self-manageable systems — systems which are aware of their components and their environment, and can configure, optimise, heal and protect themselves. In the context of realisation of such systems, declarative programming, whose goal is to ease the programmer’s task by separating the control from the logic of a computation, has regained a lot of interest recently. In particular, rule-based programming is regarded as a promising model in this quest for adequate programming abstractions for these platforms. However, while these models are gaining a lot of attention, there is a demand for generic tools able to run such models at large scale. The chemical programming model, which was designed following the chemical metaphor, is a higher-order, rule-based programming model, with a non-deterministic execution model, where rules are applied concurrently on a multiset of data. In this thesis, we propose the design, development, and experimentation of a distributed chemical runtime for generic, largely-distributed platforms. The architecture proposed combines a peer-to-peer communication layer with an adaptive protocol for atomically capturing objects on which rules should be applied, and an efficient termination-detection scheme. We describe the software prototype implementing this architecture. Based on its deployment over a real-world test-bed, we present its performance results, which confirm analytically obtained complexities, and experimentally show the sustainability of such a programming model.

Efficient management of limited water resources in an irrigation reservoir system is necessary to increase crop productivity. To achieve this, a reservoir release policy should be integrated with an optimal crop water allocation. Variations in hydrologic variables such as reservoir inflow, soil moisture, reservoir storage, rainfall and evapotranspiration must be considered in the reservoir operating policy model. Uncertainties due to imprecision, subjectivity, vagueness and lack of adequate data can be handled using the fuzzy set theory. A fuzzy stochastic dynamic programming (FSDP) model with reservoir storage and soil moisture of the crops as fuzzy state variables and inflow as a stochastic variable, is developed to obtain a steady state reservoir operating policy. The model integrates the reservoir operating policy with the crop water allocation decisions by maintaining the storage continuity and the soil moisture balance. The reservoir release decisions are made in the model in 10-day periods and water is allocated to the crops on a daily basis. On comparison with the classical stochastic dynamic programming (SDP) model and a conceptual operation policy model, it is observed that the FSDP model, in general, results in lower release from the reservoir while maintaining lower soil moisture stress. However the steady state reservoir operation policy obtained using the FSDP model may not perform well in a short-term reservoir simulation. A fuzzy state short-term reservoir operation policy model with storage and soil moistures of the crops as fuzzy variables, is developed to obtain a real time release policy using forecasted inflow and forecasted rainfall. The distinguishing features of the model are accounting for (a) spatial variation of soil moisture and rainfall using gridded rainfall forecasts and (b) ponding depth requirement of the Paddy. On comparison with a conceptual operation policy model, the fuzzy state real time operation model is found most suitable for the application of the short term real time operation for irrigation. The real time operation model maintains high storage in the reservoir during most of the 10-day time periods of a year and results in a slightly lower annual releases as compared to the conceptual operation policy model. The effect of inflow forecast uncertainty is examined using different sets of forecasted inflows, and it is observed that the system performance is quite sensitive to inflow forecast uncertainties. The use of the satellite based gridded soil moisture in the real time operation model shows consideration of realistic situations. Further, three performance measures, viz., fuzzy reliability, fuzzy resiliency and fuzzy vulnerability are developed to evaluate the performance of the irrigation reservoir system under a specified operating policy. A fuzzy set with an appropriate membership function is defined to describe the working and failed states to account for the system being in partly working and partly failed state. The degree of failure of the irrigation reservoir system is defined based on the evapotranspiration deficit in a period. Inclusion of fuzziness in the performance measures enables realistic representation of uncertainties in the state of the system. A case study of Bhadra reservoir system in Karnataka, India is chosen for demonstrating the model applications.

La Radio Logicielle (SDR) est une radio dont les transformations de la forme d’onde, modulation, démodulation des signaux d’un système radio sont mises en œuvre par du logiciel plutôt que par du matériel à fonctionnalité spécifique. Avec cette approche, l’adaptation du système à une autre norme de communication, ou même l’évolution vers une technologie plus récente peuvent être réalisés par mise à jour du logiciel sans remplacement du matériel qui serait long et coûteux. L’architecture de communication logicielle (Software Communication Architecture, SCA), est une architecture ouverte largement acceptée pour les projets de SDR. La spécification SCA minimise le coût de portage des applications en fournissant une couche d’abstraction qui rend transparentes les méthodes spécifiques de chaque système. Dans cette thèse, on s’intéresse au développement et à la programmation d’une plateforme SDR conforme à SCA.Les nouvelles plateformes de SDR sont en général implémentées sur des plateformes multiprocesseurs système sur puce (MPSoC) exploitant ses importantes ressources de calculs avec une bonne efficacité énergique. Les possibilités d’un rapide développement, déploiement et vérification des logiciels embarqués parallèles sur ces nouvelles plateformes MPSoC sont autant de points clés pour satisfaire les objectifs de performance tout en respectant les délais de mise à disposition sur le marché et le coût de développement.On a proposé un flot de conception pour la SDR avec l’exploration architecturale systématique et l’optimisation multi-objective utilisant le modèle de programmation hybride (distribué client/serveur + parallèle).On a étudié aussi la synthèse de topologie de réseau-sur-puce (PSTRP) qui est une partie du flot de conception. Le problème de la synthèse de la topologie du réseau-sur-puce peut se modéliser sous forme de programme linéaire en nombres entiers. Les résultats montrent que les contraintes d’implémentation, comme la hiérarchie du réseau sur puce, doivent être prises en compte pour obtenir un résultat à la fois mathématiquement optimisé et électroniquement réalisable. / The Software Defined Radio (SDR) is a reconfigurable radio whose functionality is controlled by software, which greatly enhances the reusability and flexibility of waveform applications. The system update is also made easily achievable through software update instead of hardware replacement. The Software Communication Architecture (SCA), on the other hand, is an open architecture framework which specifies an Operating Environment (OE) in which waveform applications are executed. A SCA compliant SDR greatly improves the portability, reusability and interoperability of waveforms applications between different SDR implementations.The multiprocessor system on chip (MPSoC) consisting of large, heterogeneous sets of embedded processors, reconfiguration hardware and network-on-chip (NoC) interconnection is emerging as a potential solution for the continued increase in the data processing bandwidth, as well as expenses for the manufacturing and design of nanoscale system-on-chip (SoC) in the face of continued time-to-market pressures.We studied the challenges of efficiently deploying a SCA compliant platform on an MPSoC. We conclude that for realizing efficiently an SDR system with high data bandwidth requirement, a design flow with systematic design space exploration and optimization, and an efficient programming model are necessary. We propose a hybrid programming model combining distributed client/server model and parallel shared memory model. A design flow is proposed which also integrates a NoC topology synthesis engine for applications that are to be accelerated with parallel programming and multiple processing elements (PEs). We prototyped an integrated SW/HW development environment in which a CORBA based integrated distributed system is developed which depends on the network-on-chip for protocol/packet routing, and software components are deployed with unified interface despite the underlying heterogeneous architecture and os; while the hardware components (processors, IPs, etc) are integrated through interface conforming to the Open Core Protocol (OCP).

Distributed parameter systems (DPS) comprise an important class of engineering systems ranging from "traditional" such as tubular reactors, to cutting edge processes such as nano-scale coatings. DPS have been studied extensively and significant advances have been noted, enabling their accurate simulation. To this end a variety of tools have been developed. However, extending these advances for systems design is not a trivial task . Rigorous design and operation policies entail systematic procedures for optimisation and control. These tasks are "upper-level" and utilize existing models and simulators. The higher the accuracy of the underlying models, the more the design procedure benefits. However, employing such models in the context of conventional algorithms may lead to inefficient formulations. The optimisation and control of DPS is a challenging task. These systems are typically discretised over a computational mesh, leading to large-scale problems. Handling the resulting large-scale systems may prove to be an intimidating task and requires special methodologies. Furthermore, it is often the case that the underlying physical phenomena span various temporal and spatial scales, thus complicating the analysis. Stiffness may also potentially be exhibited in the (nonlinear) models of such phenomena. The objective of this work is to design reliable and practical procedures for the optimisation and control of DPS. It has been observed in many systems of engineering interest that although they are described by infinite-dimensional Partial Differential Equations (PDEs) resulting in large discretisation problems, their behaviour has a finite number of significant components , as a result of their dissipative nature. This property has been exploited in various systematic model reduction techniques. Of key importance in this work is the identification of a low-dimensional dominant subspace for the system. This subspace is heuristically found to correspond to part of the eigenspectrum of the system and can therefore be identified efficiently using iterative matrix-free techniques. In this light, only low-dimensional Jacobians and Hessian matrices are involved in the formulation of the proposed algorithms, which are projections of the original matrices onto appropriate low-dimensional subspaces, computed efficiently with directional perturbations.The optimisation algorithm presented employs a 2-step projection scheme, firstly onto the dominant subspace of the system (corresponding to the right-most eigenvalues of the linearised system) and secondly onto the subspace of decision variables. This algorithm is inspired by reduced Hessian Sequential Quadratic Programming methods and therefore locates a local optimum of the nonlinear programming problem given by solving a sequence of reduced quadratic programming (QP) subproblems . This optimisation algorithm is appropriate for systems with a relatively small number of decision variables. Inequality constraints can be accommodated following a penalty-based strategy which aggregates all constraints using an appropriate function , or by employing a partial reduction technique in which only equality constraints are considered for the reduction and the inequalities are linearised and passed on to the QP subproblem . The control algorithm presented is based on the online adaptive construction of low-order linear models used in the context of a linear Model Predictive Control (MPC) algorithm , in which the discrete-time state-space model is recomputed at every sampling time in a receding horizon fashion. Successive linearisation around the current state on the closed-loop trajectory is combined with model reduction, resulting in an efficient procedure for the computation of reduced linearised models, projected onto the dominant subspace of the system. In this case, this subspace corresponds to the eigenvalues of largest magnitude of the discretised dynamical system. Control actions are computed from low-order QP problems solved efficiently online.The optimisation and control algorithms presented may employ input/output simulators (such as commercial packages) extending their use to upper-level tasks. They are also suitable for systems governed by microscopic rules, the equations of which do not exist in closed form. Illustrative case studies are presented, based on tubular reactor models, which exhibit rich parametric behaviour.

El presente proyecto diseña una metodología para mitigar los principales problemas operativos y logísticos en una empresa 3PL en chorrillos-Lima-Perú con el fin de reducir los costos y aumentar el margen de contribución. En la investigación se identificó oportunidades de mejora dentro del sector se servicios logísticos los cuales abarcaban costos de transporte y mejora de procesos. La información se obtuvo a través de análisis de mercado, benchmarking (entidades privadas), entidades públicas (estadística del MTC, Sutran), e información de estudios profesionales y científicos. La tesis se divide en 5 capítulos. En el primer capítulo, se explica el estado del arte, investigaciones anteriores y el marco conceptual-teórico. El segundo capítulo presenta los antecedentes y realidad problemática en una empresa del sector logístico peruano. Además, presenta los objetivos generales y específicos y las hipótesis del proyecto. El tercer capítulo diseña y desarrolla la propuesta de mejora para la optimización de costos. La propuesta de mejora integra 4 herramientas de la filosofía Lean (just in time, balance de línea, Kanban, 5s) y un modelo de programación lineal. El cuarto capítulo presenta la validación económica, funcional, ambiental y de riesgos. Por último, el capítulo cinco expone las conclusiones y recomendaciones generales y específicas. / This project designs a methodology to mitigate the main operational and logistical problems in a 3PL company in order to reduce costs and increase the contribution margin at Chorrillos-Lima-Peru The research identified opportunities for improvement within the logistics services sector which included transportation costs and process improvement. The information was obtained through market analysis, benchmarking (private entities), public entities (MTC statistics, Sutran), and information from professional and scientific studies. The thesis is divided into 5 chapters. In the first chapter, the state of the art, previous investigations and the conceptual-theoretical framework are explained. The second chapter presents the background and the problematic reality in a company in the Peruvian logistics sector. In addition, it presents the general and specific objectives and hypotheses of the project. The third chapter designs and develops the improvement proposal for cost optimization. The improvement proposal integrates 4 tools of the Lean philosophy (just in time, line balance, Kanban, 5s) and a lineal programming model. The fourth chapter presents economic, functional, environmental and risk validation. Finally, chapter five sets out the general and specific conclusions and recommendations. / Trabajo de Suficiencia Profesional