832 resultados para Distribute-Map-Reduce
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Panoramica delle caratteristiche dei database NoSQL, con dettaglio su MongoDB: filosofia di progettazione, modello dei dati, indicizzazione, algoritmo Map-Reduce e gestione della memoria.
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Dissertação para obtenção do Grau de Mestre em Engenharia Informática
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In this paper we advocate the Loop-of-stencil-reduce pattern as a way to simplify the parallel programming of heterogeneous platforms (multicore+GPUs). Loop-of-Stencil-reduce is general enough to subsume map, reduce, map-reduce, stencil, stencil-reduce, and, crucially, their usage in a loop. It transparently targets (by using OpenCL) combinations of CPU cores and GPUs, and it makes it possible to simplify the deployment of a single stencil computation kernel on different GPUs. The paper discusses the implementation of Loop-of-stencil-reduce within the FastFlow parallel framework, considering a simple iterative data-parallel application as running example (Game of Life) and a highly effective parallel filter for visual data restoration to assess performance. Thanks to the high-level design of the Loop-of-stencil-reduce, it was possible to run the filter seamlessly on a multicore machine, on multi-GPUs, and on both.
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We advocate the Loop-of-stencil-reduce pattern as a means of simplifying the implementation of data-parallel programs on heterogeneous multi-core platforms. Loop-of-stencil-reduce is general enough to subsume map, reduce, map-reduce, stencil, stencil-reduce, and, crucially, their usage in a loop in both data-parallel and streaming applications, or a combination of both. The pattern makes it possible to deploy a single stencil computation kernel on different GPUs. We discuss the implementation of Loop-of-stencil-reduce in FastFlow, a framework for the implementation of applications based on the parallel patterns. Experiments are presented to illustrate the use of Loop-of-stencil-reduce in developing data-parallel kernels running on heterogeneous systems.
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Floating-point computing with more than one TFLOP of peak performance is already a reality in recent Field-Programmable Gate Arrays (FPGA). General-Purpose Graphics Processing Units (GPGPU) and recent many-core CPUs have also taken advantage of the recent technological innovations in integrated circuit (IC) design and had also dramatically improved their peak performances. In this paper, we compare the trends of these computing architectures for high-performance computing and survey these platforms in the execution of algorithms belonging to different scientific application domains. Trends in peak performance, power consumption and sustained performances, for particular applications, show that FPGAs are increasing the gap to GPUs and many-core CPUs moving them away from high-performance computing with intensive floating-point calculations. FPGAs become competitive for custom floating-point or fixed-point representations, for smaller input sizes of certain algorithms, for combinational logic problems and parallel map-reduce problems. © 2014 Technical University of Munich (TUM).
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L’èxit del Projecte Genoma Humà (PGH) l’any 2000 va fer de la “medicina personalitzada” una realitat més propera. Els descobriments del PGH han simplificat les tècniques de seqüenciació de tal manera que actualment qualsevol persona pot aconseguir la seva seqüència d’ADN complerta. La tecnologia de Read Mapping destaca en aquest tipus de tècniques i es caracteritza per manegar una gran quantitat de dades. Hadoop, el framework d’Apache per aplicacions intensives de dades sota el paradigma Map Reduce, resulta un aliat perfecte per aquest tipus de tecnologia i ha sigut l’opció escollida per a realitzar aquest projecte. Durant tot el treball es realitza l’estudi, l’anàlisi i les experimentacions necessàries per aconseguir un Algorisme Genètic innovador que utilitzi tot el potencial de Hadoop.
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El presente Trabajo de Fin de Grado se enmarca dentro de un sistema de control y desarrollo de sistemas inteligentes de transporte (ITS). Este Trabajo consta de varias líneas de desarrollo, que se engloban dentro de dicho marco y surgen de la necesidad de aumentar la seguridad, flujo, estructura y mantenimiento de las carreteras incorporando las tecnologías más recientes. En primer lugar, el presente Trabajo se centra en el desarrollo de un nuevo sistema de procesamiento de datos de tráfico en tiempo real que aprovecha las tecnologías de Big Data, Cloud Computing y Map-Reduce que han surgido estos últimos años. Para ello se realiza un estudio previo de los datos de tráfico vial que originan los vehículos que viajan por carreteras. Centrándose en el sistema empleado por la Dirección General de Tráfico de España y comparándolos con el de las Empresas basadas en servicios de localización (LBS). Se expone el modelo Hadoop utilizado así como el proceso Map-Reduce implementado en este sistema analizador. Por último los datos de salida son preparados y enviados a un módulo web básico que actúa como Sistema de Información Geográfica (GIS).---ABSTRACT---This Final Degree Project is part of a control system and development of intelligent transport systems (ITS). This work is part of a several lines of development, which are included within this framework and arise from the need to increase security, flow, structure and maintenance of roads incorporating the latest technologies. First, this paper focuses on the development of a new data processing system of real-time traffic that takes advantage of Big Data, Cloud Computing and Map-Reduce technologies emerged in our recent years. It is made a preliminary study of road traffic data originated by vehicles traveling by road. Focusing on the system used by the Dirección General de Tráfico of Spain and compared with that of the companies offering location based services (LBS). It is exposed the used Hadoop model and the Map-Reduce process implemented on this analyzer system. Finally, the output data is prepared and sent to a basic web module that acts as Geographic Information System (GIS).
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Mode of access: Internet.
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Granulocyte-colony stimulating factor (G-CSF) is a current pharmacological approach to increase peripheral neutrophil counts after anti-tumor therapies. Pain is most relevant side effect of G-CSF in healthy volunteers and cancer patients. Therefore, the mechanisms of G-CSF-induced hyperalgesia were investigated focusing on the role of spinal mitogen-activated protein (MAP) kinases ERK (extracellular signal-regulated kinase). JNK (Jun N-terminal Kinase) and p38, and PI(3)K (phosphatidylinositol 3-kinase). G-CSF induced dose (30-300 ng/paw)-dependent mechanical hyperalgesia, which was inhibited by local post-treatment with morphine. This effect of morphine was reversed by naloxone (opioid receptor antagonist). Furthermore, G-CSF-induced hyperalgesia was inhibited in a dose-dependent manner by intrathecal pre-treatment with ERK (PD98059), JNK (SB600125), p38 (SB202190) or PI(3)K (wortmanin) inhibitors. The co-treatment with MAP kinase and PI(3)K inhibitors, at doses that were ineffective as single treatment, significantly inhibited G-CSF-induced hyperalgesia. Concluding, in addition to systemic opioids, peripheral opioids as well as spinal treatment with MAP kinases and PI(3)K inhibitors also reduce G-CSF-induced pain. (C) 2011 Elsevier Inc. All rights reserved.
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The global malaria situation has scarcely improved in the last 100 years, despite major advances in our knowledge of the basic biology, epidemiology and clinical basis of the disease. Effective malaria control, leading to a significant decrease in the morbidity and mortality attributable to malaria, will require a multidisciplinary approach. New tools - drugs, vaccine and insecticides - are needed but there is also much to be gained by better use of existing tools: using drugs in combination in order to slow the development of drug resistance; targeting resources to areas of greatest need; using geographic information systems to map the populations at risk and more sophisticated marketing techniques to distribute bed nets and insecticides. Sustainable malaria control may require the deployment of a highly effective vaccine, but there is much that can be done in the meantime to reduce the burden of disease.
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High-field (>or=3 T) cardiac MRI is challenged by inhomogeneities of both the static magnetic field (B(0)) and the transmit radiofrequency field (B(1)+). The inhomogeneous B fields not only demand improved shimming methods but also impede the correct determination of the zero-order terms, i.e., the local resonance frequency f(0) and the radiofrequency power to generate the intended local B(1)+ field. In this work, dual echo time B(0)-map and dual flip angle B(1)+-map acquisition methods are combined to acquire multislice B(0)- and B(1)+-maps simultaneously covering the entire heart in a single breath hold of 18 heartbeats. A previously proposed excitation pulse shape dependent slice profile correction is tested and applied to reduce systematic errors of the multislice B(1)+-map. Localized higher-order shim correction values including the zero-order terms for frequency f(0) and radiofrequency power can be determined based on the acquired B(0)- and B(1)+-maps. This method has been tested in 7 healthy adult human subjects at 3 T and improved the B(0) field homogeneity (standard deviation) from 60 Hz to 35 Hz and the average B(1)+ field from 77% to 100% of the desired B(1)+ field when compared to more commonly used preparation methods.
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We consider the stability properties of spatial and temporal periodic orbits of one-dimensional coupled-map lattices. The stability matrices for them are of the block-circulant form. This helps us to reduce the problem of stability of spatially periodic orbits to the smaller orbits corresponding to the building blocks of spatial periodicity, enabling us to obtain the conditions for stability in terms of those for smaller orbits.
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The applicability of AI methods to the Chagas' disease diagnosis is carried out by the use of Kohonen's self-organizing feature maps. Electrodiagnosis indicators calculated from ECG records are used as features in input vectors to train the network. Cross-validation results are used to modify the maps, providing an outstanding improvement to the interpretation of the resulting output. As a result, the map might be used to reduce the need for invasive explorations in chronic Chagas' disease.
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The aim of this project is to provide an explanation for recently obtained binding constants for two similar guest molecules, NDMG and N-MAP, with a p-sulfonatocalix[6]arene host in ammonium acetate buffer. This work was done primarily using pressure perturbation calorimetry, which is a technique that determines the coefficient of thermal expansion, α, which is in turn related to the solute molecule's effect on the order of the surrounding water molecules. A series of experiments were designed to test the effects of suspected confounding variables on the validity of PPC data. PPC was then used to study NDMG and N-MAP in ammonium acetate buffer. NDMG exhibited a minimum in α as function of temperature, while N-MAP did not. This difference was theorized to be due to the formation of an intramolecular hydrogen bond in monocationic NDMG that would lower the heat capacity of the molecule and better distribute the molecule's charge. Computational work and nuclear magnetic resonance spectroscopy confirmed that monocationic, ring-closed NDMG has less concentrated charge and more constrained motion than monocationic, ring-open NDMG. This evidence supports the theory that monocationic NDMG forms an intramolecular hydrogen bond and that this may be responsible for the minimum in α. This difference may explain the differences in binding constants between NDMG and N-MAP.