805 resultados para hardware computing


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A first-rate e-Health system saves lives, provides better patient care, allows complex but useful epidemiologic analysis and saves money. However, there may also be concerns about the costs and complexities associated with e-health implementation, and the need to solve issues about the energy footprint of the high-demanding computing facilities. This paper proposes a novel and evolved computing paradigm that: (i) provides the required computing and sensing resources; (ii) allows the population-wide diffusion; (iii) exploits the storage, communication and computing services provided by the Cloud; (iv) tackles the energy-optimization issue as a first-class requirement, taking it into account during the whole development cycle. The novel computing concept and the multi-layer top-down energy-optimization methodology obtain promising results in a realistic scenario for cardiovascular tracking and analysis, making the Home Assisted Living a reality.

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As advanced Cloud services are becoming mainstream, the contribution of data centers in the overall power consumption of modern cities is growing dramatically. The average consumption of a single data center is equivalent to the energy consumption of 25.000 households. Modeling the power consumption for these infrastructures is crucial to anticipate the effects of aggressive optimization policies, but accurate and fast power modeling is a complex challenge for high-end servers not yet satisfied by analytical approaches. This work proposes an automatic method, based on Multi-Objective Particle Swarm Optimization, for the identification of power models of enterprise servers in Cloud data centers. Our approach, as opposed to previous procedures, does not only consider the workload consolidation for deriving the power model, but also incorporates other non traditional factors like the static power consumption and its dependence with temperature. Our experimental results shows that we reach slightly better models than classical approaches, but simul- taneously simplifying the power model structure and thus the numbers of sensors needed, which is very promising for a short-term energy prediction. This work, validated with real Cloud applications, broadens the possibilities to derive efficient energy saving techniques for Cloud facilities.

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Current fusion devices consist of multiple diagnostics and hundreds or even thousands of signals. This situation forces on multiple occasions to use distributed data acquisition systems as the best approach. In this type of distributed systems, one of the most important issues is the synchronization between signals, so that it is possible to have a temporal correlation as accurate as possible between the acquired samples of all channels. In last decades, many fusion devices use different types of video cameras to provide inside views of the vessel during operations and to monitor plasma behavior. The synchronization between each video frame and the rest of the different signals acquired from any other diagnostics is essential in order to know correctly the plasma evolution, since it is possible to analyze jointly all the information having accurate knowledge of their temporal correlation. The developed system described in this paper allows timestamping image frames in a real-time acquisition and processing system using 1588 clock distribution. The system has been implemented using FPGA based devices together with a 1588 synchronized timing card (see Fig.1). The solution is based on a previous system [1] that allows image acquisition and real-time image processing based on PXIe technology. This architecture is fully compatible with the ITER Fast Controllers [2] and offers integration with EPICS to control and monitor the entire system. However, this set-up is not able to timestamp the frames acquired since the frame grabber module does not present any type of timing input (IRIG-B, GPS, PTP). To solve this lack, an IEEE1588 PXI timing device its used to provide an accurate way to synchronize distributed data acquisition systems using the Precision Time Protocol (PTP) IEEE 1588 2008 standard. This local timing device can be connected to a master clock device for global synchronization. The timing device has a buffer timestamp for each PXI trigger line and requires tha- a software application assigns each frame the corresponding timestamp. The previous action is critical and cannot be achieved if the frame rate is high. To solve this problem, it has been designed a solution that distributes the clock from the IEEE 1588 timing card to all FlexRIO devices [3]. This solution uses two PXI trigger lines that provide the capacity to assign timestamps to every frame acquired and register events by hardware in a deterministic way. The system provides a solution for timestamping frames to synchronize them with the rest of the different signals.

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Conceptos de representación binaria y de arquitecturas hardware y software con prácticas de laboratorio sobre Linux y ejercicios resueltos.

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This is the final report on reproducibility@xsede, a one-day workshop held in conjunction with XSEDE14, the annual conference of the Extreme Science and Engineering Discovery Environment (XSEDE). The workshop's discussion-oriented agenda focused on reproducibility in large-scale computational research. Two important themes capture the spirit of the workshop submissions and discussions: (1) organizational stakeholders, especially supercomputer centers, are in a unique position to promote, enable, and support reproducible research; and (2) individual researchers should conduct each experiment as though someone will replicate that experiment. Participants documented numerous issues, questions, technologies, practices, and potentially promising initiatives emerging from the discussion, but also highlighted four areas of particular interest to XSEDE: (1) documentation and training that promotes reproducible research; (2) system-level tools that provide build- and run-time information at the level of the individual job; (3) the need to model best practices in research collaborations involving XSEDE staff; and (4) continued work on gateways and related technologies. In addition, an intriguing question emerged from the day's interactions: would there be value in establishing an annual award for excellence in reproducible research? Overview

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The Internet of Things makes use of a huge disparity of technologies at very different levels that help one to the other to accomplish goals that were previously regarded as unthinkable in terms of ubiquity or scalability. If the Internet of Things is expected to interconnect every day devices or appliances and enable communications between them, a broad range of new services, applications and products can be foreseen. For example, monitoring is a process where sensors have widespread use for measuring environmental parameters (temperature, light, chemical agents, etc.) but obtaining readings at the exact physical point they want to be obtained from, or about the exact wanted parameter can be a clumsy, time-consuming task that is not easily adaptable to new requirements. In order to tackle this challenge, a proposal on a system used to monitor any conceivable environment, which additionally is able to monitor the status of its own components and heal some of the most usual issues of a Wireless Sensor Network, is presented here in detail, covering all the layers that give it shape in terms of devices, communications or services.

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Dynamic and Partial Reconfiguration allows systems to change some parts of their hardware at run time. This feature favours the inclusion of evolutionary strategies to provide optimised solutions to the same problem so that they can be mixed and compared in a way that only the best ones prevail. At the same time, distributed intelligence permits systems to work in a collaborative way to jointly improve their global capabilities. This work presents a combination of both approaches where hardware evolution is performed both at local and network level in order to improve an image filter application in terms of performance, robustness and providing the capacity of avoiding local minimums, which is the main drawback of some evolutionary approaches.

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Brain-Computer Interfaces are usually tackled from a medical point of view, correlating observed phenomena to physical facts known about the brain. Existing methods of classification lie in the application of deterministic algorithms and depend on certain degree of knowledge about the underlying phenomena so as to process data. In this demo, different architectures for an evolvable hardware classifier implemented on an FPGA are proposed, in line with the objective of generalizing evolutionary algorithms regardless of the application.

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Dynamic and Partial Reconfiguration (DPR) allows a system to be able to modify certain parts of itself during run-time. This feature gives rise to the capability of evolution: changing parts of the configuration according to the online evaluation of performance or other parameters. The evolution is achieved through a bio-inspired model in which the features of the system are identified as genes. The objective of the evolution may not be a single one; in this work, power consumption is taken into consideration, together with the quality of filtering, as the measure of performance, of a noisy image. Pareto optimality is applied to the evolutionary process, in order to find a representative set of optimal solutions as for performance and power consumption. The main contributions of this paper are: implementing an evolvable system on a low-power Spartan-6 FPGA included in a Wireless Sensor Network node and, by enabling the availability of a real measure of power consumption at run-time, achieving the capability of multi-objective evolution, that yields different optimal configurations, among which the selected one will depend on the relative “weights” of performance and power consumption.

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Recientemente, el paradigma de la computación en la nube ha recibido mucho interés por parte tanto de la industria como del mundo académico. Las infraestructuras cloud públicas están posibilitando nuevos modelos de negocio y ayudando a reducir costes. Sin embargo, una compañía podría desear ubicar sus datos y servicios en sus propias instalaciones, o tener que atenerse a leyes de protección de datos. Estas circunstancias hacen a las infraestructuras cloud privadas ciertamente deseables, ya sea para complementar a las públicas o para sustituirlas por completo. Por desgracia, las carencias en materia de estándares han impedido que las soluciones para la gestión de infraestructuras privadas se hayan desarrollado adecuadamente. Además, la multitud de opciones disponibles ha creado en los clientes el miedo a depender de una tecnología concreta (technology lock-in). Una de las causas de este problema es la falta de alineación entre la investigación académica y los productos comerciales, ya que aquella está centrada en el estudio de escenarios idealizados sin correspondencia con el mundo real, mientras que éstos consisten en soluciones desarrolladas sin tener en cuenta cómo van a encajar con los estándares más comunes o sin preocuparse de hacer públicos sus resultados. Con objeto de resolver este problema, propongo un sistema de gestión modular para infraestructuras cloud privadas enfocado en tratar con las aplicaciones en lugar de centrarse únicamente en los recursos hardware. Este sistema de gestión sigue el paradigma de la computación autónoma y está diseñado en torno a un modelo de información sencillo, desarrollado para ser compatible con los estándares más comunes. Este modelo divide el entorno en dos vistas, que sirven para separar aquello que debe preocupar a cada actor involucrado del resto de información, pero al mismo tiempo permitiendo relacionar el entorno físico con las máquinas virtuales que se despliegan encima de él. En dicho modelo, las aplicaciones cloud están divididas en tres tipos genéricos (Servicios, Trabajos de Big Data y Reservas de Instancias), para que así el sistema de gestión pueda sacar partido de las características propias de cada tipo. El modelo de información está complementado por un conjunto de acciones de gestión atómicas, reversibles e independientes, que determinan las operaciones que se pueden llevar a cabo sobre el entorno y que es usado para hacer posible la escalabilidad en el entorno. También describo un motor de gestión encargado de, a partir del estado del entorno y usando el ya mencionado conjunto de acciones, la colocación de recursos. Está dividido en dos niveles: la capa de Gestores de Aplicación, encargada de tratar sólo con las aplicaciones; y la capa del Gestor de Infraestructura, responsable de los recursos físicos. Dicho motor de gestión obedece un ciclo de vida con dos fases, para así modelar mejor el comportamiento de una infraestructura real. El problema de la colocación de recursos es atacado durante una de las fases (la de consolidación) por un resolutor de programación entera, y durante la otra (la online) por un heurístico hecho ex-profeso. Varias pruebas han demostrado que este acercamiento combinado es superior a otras estrategias. Para terminar, el sistema de gestión está acoplado a arquitecturas de monitorización y de actuadores. Aquella estando encargada de recolectar información del entorno, y ésta siendo modular en su diseño y capaz de conectarse con varias tecnologías y ofrecer varios modos de acceso. ABSTRACT The cloud computing paradigm has raised in popularity within the industry and the academia. Public cloud infrastructures are enabling new business models and helping to reduce costs. However, the desire to host company’s data and services on premises, and the need to abide to data protection laws, make private cloud infrastructures desirable, either to complement or even fully substitute public oferings. Unfortunately, a lack of standardization has precluded private infrastructure management solutions to be developed to a certain level, and a myriad of diferent options have induced the fear of lock-in in customers. One of the causes of this problem is the misalignment between academic research and industry ofering, with the former focusing in studying idealized scenarios dissimilar from real-world situations, and the latter developing solutions without taking care about how they f t with common standards, or even not disseminating their results. With the aim to solve this problem I propose a modular management system for private cloud infrastructures that is focused on the applications instead of just the hardware resources. This management system follows the autonomic system paradigm, and is designed around a simple information model developed to be compatible with common standards. This model splits the environment in two views that serve to separate the concerns of the stakeholders while at the same time enabling the traceability between the physical environment and the virtual machines deployed onto it. In it, cloud applications are classifed in three broad types (Services, Big Data Jobs and Instance Reservations), in order for the management system to take advantage of each type’s features. The information model is paired with a set of atomic, reversible and independent management actions which determine the operations that can be performed over the environment and is used to realize the cloud environment’s scalability. From the environment’s state and using the aforementioned set of actions, I also describe a management engine tasked with the resource placement. It is divided in two tiers: the Application Managers layer, concerned just with applications; and the Infrastructure Manager layer, responsible of the actual physical resources. This management engine follows a lifecycle with two phases, to better model the behavior of a real infrastructure. The placement problem is tackled during one phase (consolidation) by using an integer programming solver, and during the other (online) with a custom heuristic. Tests have demonstrated that this combined approach is superior to other strategies. Finally, the management system is paired with monitoring and actuators architectures. The former able to collect the necessary information from the environment, and the later modular in design and capable of interfacing with several technologies and ofering several access interfaces.

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Con el auge del Cloud Computing, las aplicaciones de proceso de datos han sufrido un incremento de demanda, y por ello ha cobrado importancia lograr m�ás eficiencia en los Centros de Proceso de datos. El objetivo de este trabajo es la obtenci�ón de herramientas que permitan analizar la viabilidad y rentabilidad de diseñar Centros de Datos especializados para procesamiento de datos, con una arquitectura, sistemas de refrigeraci�ón, etc. adaptados. Algunas aplicaciones de procesamiento de datos se benefician de las arquitecturas software, mientras que en otras puede ser m�ás eficiente un procesamiento con arquitectura hardware. Debido a que ya hay software con muy buenos resultados en el procesamiento de grafos, como el sistema XPregel, en este proyecto se realizará una arquitectura hardware en VHDL, implementando el algoritmo PageRank de Google de forma escalable. Se ha escogido este algoritmo ya que podr��á ser m�ás eficiente en arquitectura hardware, debido a sus características concretas que se indicaráan m�ás adelante. PageRank sirve para ordenar las p�áginas por su relevancia en la web, utilizando para ello la teorí��a de grafos, siendo cada página web un vértice de un grafo; y los enlaces entre páginas, las aristas del citado grafo. En este proyecto, primero se realizará un an�álisis del estado de la técnica. Se supone que la implementaci�ón en XPregel, un sistema de procesamiento de grafos, es una de las m�ás eficientes. Por ello se estudiará esta �ultima implementaci�ón. Sin embargo, debido a que Xpregel procesa, en general, algoritmos que trabajan con grafos; no tiene en cuenta ciertas caracterí��sticas del algoritmo PageRank, por lo que la implementaci�on no es �optima. Esto es debido a que en PageRank, almacenar todos los datos que manda un mismo v�értice es un gasto innecesario de memoria ya que todos los mensajes que manda un vértice son iguales entre sí e iguales a su PageRank. Se realizará el diseño en VHDL teniendo en cuenta esta caracter��ística del citado algoritmo,evitando almacenar varias veces los mensajes que son iguales. Se ha elegido implementar PageRank en VHDL porque actualmente las arquitecturas de los sistemas operativos no escalan adecuadamente. Se busca evaluar si con otra arquitectura se obtienen mejores resultados. Se realizará un diseño partiendo de cero, utilizando la memoria ROM de IPcore de Xillinx (Software de desarrollo en VHDL), generada autom�áticamente. Se considera hacer cuatro tipos de módulos para que as�� el procesamiento se pueda hacer en paralelo. Se simplificar�á la estructura de XPregel con el fin de intentar aprovechar la particularidad de PageRank mencionada, que hace que XPregel no le saque el m�aximo partido. Despu�és se escribirá el c�ódigo, realizando una estructura escalable, ya que en la computación intervienen millones de páginas web. A continuación, se sintetizar�á y se probará el código en una FPGA. El �ultimo paso será una evaluaci�ón de la implementaci�ón, y de posibles mejoras en cuanto al consumo.

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Abstract. Receptive fields of retinal and other sensory neurons show a large variety of spatiotemporal linear and non linear types of responses to local stimuli. In visual neurons, these responses present either asymmetric sensitive zones or center-surround organization. In most cases, the nature of the responses suggests the existence of a kind of distributed computation prior to the integration by the final cell which is evidently supported by the anatomy. We describe a new kind of discrete and continuous filters to model the kind of computations taking place in the receptive fields of retinal cells. To show their performance in the analysis of diferent non-trivial neuron-like structures, we use a computer tool specifically programmed by the authors to that efect. This tool is also extended to study the efect of lesions on the whole performance of our model nets.

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Nowadays, devices that monitor the health of structures consume a lot of power and need a lot of time to acquire, process, and send the information about the structure to the main processing unit. To decrease this time, fast electronic devices are starting to be used to accelerate this processing. In this paper some hardware algorithms implemented in an electronic logic programming device are described. The goal of this implementation is accelerate the process and diminish the information that has to be send. By reaching this goal, the time the processor needs for treating all the information is reduced and so the power consumption is reduced too.

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Due to the significant increase of population and their natural desire of improving their standard of living, usage of energy extracted from world commodities, especially shaped as electricity, has increased in an intense manner during the last decades. This fact brings up a challenge with a complicated solution, which is how to guarantee that there will be enough energy so as to satisfy the energy demand of the world population. Among all the possible solutions that can be adopted to mitigate this problem one of them is almost of mandatory adoption, which consists of rationalizing energy utilization, in a way that its wasteful usage is minimized and it can be leveraged during a longer period of time. One of the ways to achieve it is by means of the improvement of the power distribution grid, so that it will be able to react in a more efficient manner against common issues, such as energy demand peaks or inaccurate electricity consumption forecasts. However, in order to be able to implement this improvement it is necessary to use technologies from the ICT (Information and Communication Technologies) sphere that often present challenges in some key areas: advanced metering infrastructure integration, interoperability and interconnectivity of the devices, interfaces to offer the applications, security measures design, etc. All these challenges may imply slowing down the adoption of the smart grid as a system to prolong the lifespan and utilization of the available energy. A proposal for an intermediation architecture that will make possible solving these challenges is put forward in this Master Thesis. Besides, one implementation and the tests that have been carried out to know the performance of the presented concepts have been included as well, in a way that it can be proved that the challenges set out by the smart grid can be resolved. RESUMEN. Debido al incremento significativo de la población y su deseo natural de mejorar su nivel de vida, la utilización de la energía extraída de las materias primas mundiales, especialmente en forma de electricidad, ha aumentado de manera intensa durante las últimas décadas. Este hecho plantea un reto de solución complicada, el cual es cómo garantizar que se dispondrá de la energía suficiente como para satisfacer la demanda energética de la población mundial. De entre todas las soluciones posibles que se pueden adoptar para mitigar este problema una de ellas es de casi obligatoria adopción, la cual consiste en racionalizar la utilización de la energía, de tal forma que se minimice su malgasto y pueda aprovecharse durante más tiempo. Una de las maneras de conseguirlo es mediante la mejora de la red de distribución de electricidad para que ésta pueda reaccionar de manera más eficaz contra problemas comunes, tales como los picos de demanda de energía o previsiones imprecisas acerca del consumo de electricidad. Sin embargo, para poder implementar esta mejora es necesario utilizar tecnologías del ámbito de las TIC (Tecnologías de la Información y la Comunicación) que a menudo presentan problemas en algunas áreas clave: integración de infraestructura de medición avanzada, interoperabilidad e interconectividad de los dispositivos, interfaces que ofrecer a las aplicaciones, diseño de medidas de seguridad, etc. Todos estos retos pueden implicar una ralentización en la adopción de la red eléctrica inteligente como un sistema para alargar la vida y la utilización de la energía disponible. En este Trabajo Fin de Máster se sugiere una propuesta para una arquitectura de intermediación que posibilite la resolución de estos retos. Además, una implementación y las pruebas que se han llevado a cabo para conocer el rendimiento de los conceptos presentados también han sido incluidas, de tal forma que se demuestre que los retos que plantea la red eléctrica inteligente pueden ser solventados.

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Los sistemas de videoconferencia y colaboración en tiempo real para múltiples usuarios permiten a sus usuarios comunicarse por medio de vídeo, audio y datos. Históricamente estos han sido sistemas caros de obtener y de mantener. El paso de las décadas ha limado estos problemas acercado el mundo de comunicación en tiempo real a un grupo mucho más amplio, llegando a usarse en diversos ámbitos como la educación o la medicina. En este sentido, el último gran salto evolutivo al que hemos asistido ha sido la transición de este tipo de aplicaciones hacia la Web. Varias tecnologías han permitido este viaje hacia el navegador. Las Aplicaciones Ricas de Internet (RIAs), que permiten crear aplicaciones Web interactivas huyendo del clásico esquema de petición y respuesta y llevando funcionalidades propias de las aplicaciones nativas a la Web. Por otro lado, la computación en la nube o Cloud Computing, con su modelo de pago por uso de recursos virtualizados, ha llevado a la creación de servicios que se adaptan mejor a la demanda, han habilitado este viaje hacia el navegador. No obstante, como cada cambio, este salto presenta una serie de retos para los sistemas de videoconferencia establecidos. Esta tesis doctoral propone un conjunto de arquitecturas, mecanismos y algoritmos para adaptar los sistemas de multiconferencia al entorno Web, teniendo en cuenta que este es accedido desde dispositivos diferentes y mediante redes de acceso variadas. Para ello se comienza por el estudio de los requisitos que debe cumplir un sistema de videoconferencia en la Web. Como resultado se diseña, implementa y desarrolla un servicio de videoconferencia que permite la colaboración avanzada entre múltiples usuarios mediante vídeo, audio y compartición de escritorio. Posteriormente, se plantea un sistema de comunicación entre una aplicación nativa y Web, proponiendo técnicas de adaptación entre los dos entornos que permiten la conversación de manera transparente para los usuarios. Estos sistemas permiten facilitar la transición hacia tecnologías Web. Como siguiente paso, se identificaron los principales problemas que existen para la comunicación multiusuario en dispositivos de tamaño reducido (teléfonos inteligentes) utilizando redes de acceso heterogéneas. Se propone un mecanismo, combinación de transcodificación y algoritmos de adaptación de calidad para superar estas limitaciones y permitir a los usuarios de este tipo de dispositivos participar en igualdad de condiciones. La aparición de WebRTC como tecnología disruptiva en este entorno, permitiendo nuevas posibilidades de comunicación en navegadores, motiva la segunda iteración de esta tesis. Aquí se presenta un nuevo esquema de adaptación a la demanda para servidores de videoconferencia diseñado para las necesidades del entorno Web y para aprovechar las características de Cloud Computing. Finalmente, esta tesis repasa las conclusiones obtenidas como fruto del trabajo llevado a cabo, reflejando la evolución de la videoconferencia Web desde sus inicios hasta nuestros días. ABSTRACT Multiuser Videoconferencing and real-time collaboration systems allow users to communicate using video, audio and data streams. These systems have been historically expensive to obtain and maintain. Over the last few decades, technological breakthroughs have mitigated those costs and popularized real time video communication, allowing its use in environments such as education or health. The last big evolutionary leap forward has been the transition of these types of applications towards theWeb. Several technologies have allowed this journey to theWeb browser. Firstly, Rich Internet Applications (RIAs) enable the creation of dynamic Web pages that defy the classical request-response interaction and provide an experience similar to their native counterparts. On the other hand, Cloud Computing brings the leasing of virtualized hardware resources in a pay-peruse model and, with it, better scalability in resource-demanding services. However, as with every change, this evolution imposes a set of challenges on existing videoconferencing solutions. This dissertation proposes a set of architectures, mechanisms and algorithms that aim to adapt multi-conferencing systems to the Web platform, taking into account the variety of devices and access networks that come with it. To this end, this thesis starts with a study concerning the requirements that must be met by new Web videoconferencing systems. The result of this study is the design, development and implementation of a new videoconferencing services that provides advanced collaboration to its user by providing video and audio communication as well as desktop sharing. After this, a new communication system between Web and native applications is presented. This system proposes adaptation mechanisms to bridge the two worlds providing a seamless integration transparent to users who can now access the powerful native application via an easy Web interface. The next step is to identify the main challenges posed by multi-conferencing on small devices (smartphones) with heterogeneous access networks. This dissertation proposes a mechanism that combines transcoding and adaptive quality algorithms to overcome those limitations. A second iteration in this dissertation is motivated by WebRTC. WebRTC appears as a disrupting technology by enabling new real-time communication possibilities in browsers. A new mechanism for flexible videoconferencing server scalability is presented. This mechanism aims to address the strong scalability requirements in the Web environment by taking advantage of Cloud Computing. Finally, the dissertation discusses the results obtained throughout the study, capturing the evolution of Web videoconferencing systems.