61 resultados para Gzip OpenMP
Resumo:
En el entorno actual, diversas ramas de las ciencias, tienen la necesidad de auxiliarse de la computación de altas prestaciones para la obtención de resultados a relativamente corto plazo. Ello es debido fundamentalmente, al alto volumen de información que necesita ser procesada y también al costo computacional que demandan dichos cálculos. El beneficio al realizar este procesamiento de manera distribuida y paralela, logra acortar los tiempos de espera en la obtención de los resultados y de esta forma posibilita una toma decisiones con mayor anticipación. Para soportar ello, existen fundamentalmente dos modelos de programación ampliamente extendidos: el modelo de paso de mensajes a través de librerías basadas en el estándar MPI, y el de memoria compartida con la utilización de OpenMP. Las aplicaciones híbridas son aquellas que combinan ambos modelos con el fin de aprovechar en cada caso, las potencialidades específicas del paralelismo en cada uno. Lamentablemente, la práctica ha demostrado que la utilización de esta combinación de modelos, no garantiza necesariamente una mejoría en el comportamiento de las aplicaciones. Por lo tanto, un análisis de los factores que influyen en el rendimiento de las mismas, nos beneficiaría a la hora de implementarlas pero también, sería un primer paso con el fin de llegar a predecir su comportamiento. Adicionalmente, supondría una vía para determinar que parámetros de la aplicación modificar con el fin de mejorar su rendimiento. En el trabajo actual nos proponemos definir una metodología para la identificación de factores de rendimiento en aplicaciones híbridas y en congruencia, la identificación de algunos factores que influyen en el rendimiento de las mismas.
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El rápido crecimiento del los sistemas multicore y los diversos enfoques que estos han tomado, permiten que procesos complejos que antes solo eran posibles de ejecutar en supercomputadores, hoy puedan ser ejecutados en soluciones de bajo coste también denominadas "hardware de comodidad". Dichas soluciones pueden ser implementadas usando los procesadores de mayor demanda en el mercado de consumo masivo (Intel y AMD). Al escalar dichas soluciones a requerimientos de cálculo científico se hace indispensable contar con métodos para medir el rendimiento que los mismos ofrecen y la manera como los mismos se comportan ante diferentes cargas de trabajo. Debido a la gran cantidad de tipos de cargas existentes en el mercado, e incluso dentro de la computación científica, se hace necesario establecer medidas "típicas" que puedan servir como soporte en los procesos de evaluación y adquisición de soluciones, teniendo un alto grado de certeza de funcionamiento. En la presente investigación se propone un enfoque práctico para dicha evaluación y se presentan los resultados de las pruebas ejecutadas sobre equipos de arquitecturas multicore AMD e Intel.
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En aquest projecte es desenvolupa una aplicació FreeRTOS per a la mota LPC1769 connectada amb un mòdul WiFly que agafa un fitxer d'Internet, el comprimeix i el desa un altre cop a Internet tot afegint les estadístiques bàsiques de temps i percentatge de compressió.
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Remote sensing spatial, spectral, and temporal resolutions of images, acquired over a reasonably sized image extent, result in imagery that can be processed to represent land cover over large areas with an amount of spatial detail that is very attractive for monitoring, management, and scienti c activities. With Moore's Law alive and well, more and more parallelism is introduced into all computing platforms, at all levels of integration and programming to achieve higher performance and energy e ciency. Being the geometric calibration process one of the most time consuming processes when using remote sensing images, the aim of this work is to accelerate this process by taking advantage of new computing architectures and technologies, specially focusing in exploiting computation over shared memory multi-threading hardware. A parallel implementation of the most time consuming process in the remote sensing geometric correction has been implemented using OpenMP directives. This work compares the performance of the original serial binary versus the parallelized implementation, using several multi-threaded modern CPU architectures, discussing about the approach to nd the optimum hardware for a cost-e ective execution.
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SUMMARY: A top scoring pair (TSP) classifier consists of a pair of variables whose relative ordering can be used for accurately predicting the class label of a sample. This classification rule has the advantage of being easily interpretable and more robust against technical variations in data, as those due to different microarray platforms. Here we describe a parallel implementation of this classifier which significantly reduces the training time, and a number of extensions, including a multi-class approach, which has the potential of improving the classification performance. AVAILABILITY AND IMPLEMENTATION: Full C++ source code and R package Rgtsp are freely available from http://lausanne.isb-sib.ch/~vpopovic/research/. The implementation relies on existing OpenMP libraries.
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Data traffic caused by mobile advertising client software when it is communicating with the network server can be a pain point for many application developers who are considering advertising-funded application distribution, since the cost of the data transfer might scare their users away from using the applications. For the thesis project, a simulation environment was built to mimic the real client-server solution for measuring the data transfer over varying types of connections with different usage scenarios. For optimising data transfer, a few general-purpose compressors and XML-specific compressors were tried for compressing the XML data, and a few protocol optimisations were implemented. For optimising the cost, cache usage was improved and pre-loading was enhanced to use free connections to load the data. The data traffic structure and the various optimisations were analysed, and it was found that the cache usage and pre-loading should be enhanced and that the protocol should be changed, with report aggregation and compression using WBXML or gzip.
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This paper describes our plans to evaluate the present state of affairs concerning parallel programming and its systems. Three subprojects are proposed: a survey among programmers and scientists, a comparison of parallel programming systems using a standard set of test programs, and a wiki resource for the parallel programming community - the Parawiki. We would like to invite you to participate and turn these subprojects into true community efforts.
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In this publication, we report on an online survey that was carried out among parallel programmers. More than 250 people worldwide have submitted answers to our questions, and their responses are analyzed here. Although not statistically sound, the data we provide give useful insights about which parallel programming systems and languages are known and in actual use. For instance, the collected data indicate that for our survey group MPI and (to a lesser extent) C are the most widely used parallel programming system and language, respectively.
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Security and Privacy Online - this is the resource and flyer created for INFO2009 which provides an interactive web presentation to make the general public aware of the dangers of using the internet unsafely, and how they can protect themselves.
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Since its introduction in 1993, the Message Passing Interface (MPI) has become a de facto standard for writing High Performance Computing (HPC) applications on clusters and Massively Parallel Processors (MPPs). The recent emergence of multi-core processor systems presents a new challenge for established parallel programming paradigms, including those based on MPI. This paper presents a new Java messaging system called MPJ Express. Using this system, we exploit multiple levels of parallelism - messaging and threading - to improve application performance on multi-core processors. We refer to our approach as nested parallelism. This MPI-like Java library can support nested parallelism by using Java or Java OpenMP (JOMP) threads within an MPJ Express process. Practicality of this approach is assessed by porting to Java a massively parallel structure formation code from Cosmology called Gadget-2. We introduce nested parallelism in the Java version of the simulation code and report good speed-ups. To the best of our knowledge it is the first time this kind of hybrid parallelism is demonstrated in a high performance Java application. (C) 2009 Elsevier Inc. All rights reserved.
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Artificial neural networks are usually applied to solve complex problems. In problems with more complexity, by increasing the number of layers and neurons, it is possible to achieve greater functional efficiency. Nevertheless, this leads to a greater computational effort. The response time is an important factor in the decision to use neural networks in some systems. Many argue that the computational cost is higher in the training period. However, this phase is held only once. Once the network trained, it is necessary to use the existing computational resources efficiently. In the multicore era, the problem boils down to efficient use of all available processing cores. However, it is necessary to consider the overhead of parallel computing. In this sense, this paper proposes a modular structure that proved to be more suitable for parallel implementations. It is proposed to parallelize the feedforward process of an RNA-type MLP, implemented with OpenMP on a shared memory computer architecture. The research consistes on testing and analizing execution times. Speedup, efficiency and parallel scalability are analyzed. In the proposed approach, by reducing the number of connections between remote neurons, the response time of the network decreases and, consequently, so does the total execution time. The time required for communication and synchronization is directly linked to the number of remote neurons in the network, and so it is necessary to investigate which one is the best distribution of remote connections
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The seismic method is of extreme importance in geophysics. Mainly associated with oil exploration, this line of research focuses most of all investment in this area. The acquisition, processing and interpretation of seismic data are the parts that instantiate a seismic study. Seismic processing in particular is focused on the imaging that represents the geological structures in subsurface. Seismic processing has evolved significantly in recent decades due to the demands of the oil industry, and also due to the technological advances of hardware that achieved higher storage and digital information processing capabilities, which enabled the development of more sophisticated processing algorithms such as the ones that use of parallel architectures. One of the most important steps in seismic processing is imaging. Migration of seismic data is one of the techniques used for imaging, with the goal of obtaining a seismic section image that represents the geological structures the most accurately and faithfully as possible. The result of migration is a 2D or 3D image which it is possible to identify faults and salt domes among other structures of interest, such as potential hydrocarbon reservoirs. However, a migration fulfilled with quality and accuracy may be a long time consuming process, due to the mathematical algorithm heuristics and the extensive amount of data inputs and outputs involved in this process, which may take days, weeks and even months of uninterrupted execution on the supercomputers, representing large computational and financial costs, that could derail the implementation of these methods. Aiming at performance improvement, this work conducted the core parallelization of a Reverse Time Migration (RTM) algorithm, using the parallel programming model Open Multi-Processing (OpenMP), due to the large computational effort required by this migration technique. Furthermore, analyzes such as speedup, efficiency were performed, and ultimately, the identification of the algorithmic scalability degree with respect to the technological advancement expected by future processors
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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We report cross sections for elastic electron scattering by gas phase glycine (neutral form), obtained with the Schwinger multichannel method. The present results are the first obtained with a new implementation that combines parallelization with OpenMP directives and pseudopotentials. The position of the well known pi* shape resonance ranged from 2.3 eV to 2.8 eV depending on the polarization model and conformer. For the most stable isomer, the present result (2.4 eV) is in fair agreement with electron transmission spectroscopy assignments (1.93 +/- 0.05 eV) and available calculations. Our results also point out a shape resonance around 9.5 eV in the A' symmetry that would be weakly coupled to vibrations of the hydroxyl group. Since electron attachment to a broad and lower lying sigma* orbital located on the OH bond has been suggested the underlying mechanism leading to dissociative electron attachment at low energies, we sought for a shape resonance around similar to 4 eV. Though we obtained cross sections with the target molecule at the equilibrium geometry and with stretched OH bond lengths, least-squares fits to the calculated eigenphase sums did not point out signatures of this anion state (though, in principle, it could be hidden in the large background). The low energy (similar to 1 eV) integral cross section strongly scales as the bond length is stretched, and this could indicate a virtual state pole, since dipole supported bound states are not expected at the geometries addressed here. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.3687345]
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This paper presents a new parallel methodology for calculating the determinant of matrices of the order n, with computational complexity O(n), using the Gauss-Jordan Elimination Method and Chio's Rule as references. We intend to present our step-by-step methodology using clear mathematical language, where we will demonstrate how to calculate the determinant of a matrix of the order n in an analytical format. We will also present a computational model with one sequential algorithm and one parallel algorithm using a pseudo-code.