888 resultados para Parallel processing (Electronic computers) - Research
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Managing software maintenance is rarely a precise task due to uncertainties concerned with resources and services descriptions. Even when a well-established maintenance process is followed, the risk of delaying tasks remains if the new services are not precisely described or when resources change during process execution. Also, the delay of a task at an early process stage may represent a different delay at the end of the process, depending on complexity or services reliability requirements. This paper presents a knowledge-based representation (Bayesian Networks) for maintenance project delays based on specialists experience and a corresponding tool to help in managing software maintenance projects. (c) 2006 Elsevier Ltd. All rights reserved.
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Notification Services mediate between information publishers and consumers that wish to subscribe to periodic updates. In many cases, however, there is a mismatch between the dissemination of these updates and the delivery preferences of the consumer, often in terms of frequency of delivery, quality, etc. In this paper, we present an automated negotiation engine that identifies mutually acceptable terms; we study its performance, and discuss its application to a Grid Notification Service. We also demonstrate how the negotiation engine enables users to control the Quality of Service levels they require.
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In this thesis, we present a novel approach to combine both reuse and prediction of dynamic sequences of instructions called Reuse through Speculation on Traces (RST). Our technique allows the dynamic identification of instruction traces that are redundant or predictable, and the reuse (speculative or not) of these traces. RST addresses the issue, present on Dynamic Trace Memoization (DTM), of traces not being reused because some of their inputs are not ready for the reuse test. These traces were measured to be 69% of all reusable traces in previous studies. One of the main advantages of RST over just combining a value prediction technique with an unrelated reuse technique is that RST does not require extra tables to store the values to be predicted. Applying reuse and value prediction in unrelated mechanisms but at the same time may require a prohibitive amount of storage in tables. In RST, the values are already stored in the Trace Memoization Table, and there is no extra cost in reading them if compared with a non-speculative trace reuse technique. . The input context of each trace (the input values of all instructions in the trace) already stores the values for the reuse test, which may also be used for prediction. Our main contributions include: (i) a speculative trace reuse framework that can be adapted to different processor architectures; (ii) specification of the modifications in a superscalar, superpipelined processor in order to implement our mechanism; (iii) study of implementation issues related to this architecture; (iv) study of the performance limits of our technique; (v) a performance study of a realistic, constrained implementation of RST; and (vi) simulation tools that can be used in other studies which represent a superscalar, superpipelined processor in detail. In a constrained architecture with realistic confidence, our RST technique is able to achieve average speedups (harmonic means) of 1.29 over the baseline architecture without reuse and 1.09 over a non-speculative trace reuse technique (DTM).
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O objetivo central desta pesquisa foi o de explorar, descrever e discutir de que forma e em que extensão as empresas se utilizam das informações contábeis tratadas por mecanismos que considerem os reflexos das variações no poder aquisitivo da moeda (Inflação) e das flutuações específicas de preços sobre os resultado e patrimônio empresarial, nos seus sistemas de controles internos e, consequentemente, em seus processos de tomada de decisão, avaliação de desempenho e fixação de tendências para o empreendimento. Em função dos objetivos propostos, a operacionalização desta pesquisa foi desenvolvida em duas etapas. A primeira fase, de caráter qualitativo, constituiu-se no levantamento dos dados básicos necessários ao atingimento dos objetivos desejados, através da aplicação de questionários em 12 (doze) empresas. Através dos dados levantados, foi possível inferir-se que o sistema contábil configura-se na base primária dos relatórios gerenciais das empresas pesquisadas. o modelo da Correção Integral teve sua validade conceitual confirmada, não obstante algumas simpliflcações metodológicas adotadas e o problema da lnadequacidade do padrão monetário utilizado principalmente em 1990. Em que pese ter havido consenso na indicação das distorções provocadas pelo problema do indexador, apenas duas empresas adotaram mecanismos tendentes a anular seus efeitos. Uma importante constatação também, foi o fato de que nas empresas em que se utilizavam sistemas contábeis baseados na metodologia da Lei Societária, como fonte primária, para geração de relatórios gerenciais, as suas adminlstrações não utilizavam tais relatórios como suporte aos seus processos de tomada de decisão, como por exemplo, no processo de estabelecimento de preços. Ressalte-se, também, que o pouco conhecimento da filosofia conceitual e vantagens informativas do modelo da Contabilidade a Custo Corrente Corrigido, tem impedido a sua implantação de forma mais ampla. Saliente-se que 60% das empresas da amostra já se utilizam de mecanismos de avaliação de ativos não monetários, com base em valores correntes (captaçao dos efeitos das flutuações especificas de preços), só que restritos aos itens circulantes (estoques) . Este é, certamente, o caminho para a aplicação plena do modelo, principalmente no âmbito gerencial. A segunda fase, cujo enfoque direcionou-se aos aspectos quantitativos, através do cálculo de indicadores econômicos-financeiros extraídos das demonstrações contábeis das empresas pesquisadas, relativos ao exercício de 1990, e elaborados em consonân ia com as metodologias da Correção Integral e da Lei Societária, buscou-se , mediante análise comparativa, avaliar as pricipais distorções encolvidas, que corroboram, de certa forma, os comentários feitos no parágrafo anterior. A natureza exploratória deste assunto, com deslocamento da ênfase da análise quantitativa, e com enfoque estritamente gerencial, é que o diferencia dos demais desenvolvidos em tempos recentes. Além disso, apresenta como caraterística acessória a busca por informações sugestivas para o desenvolvimento de pesquisas futuras.
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The number of applications based on embedded systems grows significantly every year, even with the fact that embedded systems have restrictions, and simple processing units, the performance of these has improved every day. However the complexity of applications also increase, a better performance will always be necessary. So even such advances, there are cases, which an embedded system with a single unit of processing is not sufficient to achieve the information processing in real time. To improve the performance of these systems, an implementation with parallel processing can be used in more complex applications that require high performance. The idea is to move beyond applications that already use embedded systems, exploring the use of a set of units processing working together to implement an intelligent algorithm. The number of existing works in the areas of parallel processing, systems intelligent and embedded systems is wide. However works that link these three areas to solve any problem are reduced. In this context, this work aimed to use tools available for FPGA architectures, to develop a platform with multiple processors to use in pattern classification with artificial neural networks
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The metaheuristics techiniques are known to solve optimization problems classified as NP-complete and are successful in obtaining good quality solutions. They use non-deterministic approaches to generate solutions that are close to the optimal, without the guarantee of finding the global optimum. Motivated by the difficulties in the resolution of these problems, this work proposes the development of parallel hybrid methods using the reinforcement learning, the metaheuristics GRASP and Genetic Algorithms. With the use of these techniques, we aim to contribute to improved efficiency in obtaining efficient solutions. In this case, instead of using the Q-learning algorithm by reinforcement learning, just as a technique for generating the initial solutions of metaheuristics, we use it in a cooperative and competitive approach with the Genetic Algorithm and GRASP, in an parallel implementation. In this context, was possible to verify that the implementations in this study showed satisfactory results, in both strategies, that is, in cooperation and competition between them and the cooperation and competition between groups. In some instances were found the global optimum, in others theses implementations reach close to it. In this sense was an analyze of the performance for this proposed approach was done and it shows a good performance on the requeriments that prove the efficiency and speedup (gain in speed with the parallel processing) of the implementations performed
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This study shows the implementation and the embedding of an Artificial Neural Network (ANN) in hardware, or in a programmable device, as a field programmable gate array (FPGA). This work allowed the exploration of different implementations, described in VHDL, of multilayer perceptrons ANN. Due to the parallelism inherent to ANNs, there are disadvantages in software implementations due to the sequential nature of the Von Neumann architectures. As an alternative to this problem, there is a hardware implementation that allows to exploit all the parallelism implicit in this model. Currently, there is an increase in use of FPGAs as a platform to implement neural networks in hardware, exploiting the high processing power, low cost, ease of programming and ability to reconfigure the circuit, allowing the network to adapt to different applications. Given this context, the aim is to develop arrays of neural networks in hardware, a flexible architecture, in which it is possible to add or remove neurons, and mainly, modify the network topology, in order to enable a modular network of fixed-point arithmetic in a FPGA. Five synthesis of VHDL descriptions were produced: two for the neuron with one or two entrances, and three different architectures of ANN. The descriptions of the used architectures became very modular, easily allowing the increase or decrease of the number of neurons. As a result, some complete neural networks were implemented in FPGA, in fixed-point arithmetic, with a high-capacity parallel processing
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The last years have presented an increase in the acceptance and adoption of the parallel processing, as much for scientific computation of high performance as for applications of general intention. This acceptance has been favored mainly for the development of environments with massive parallel processing (MPP - Massively Parallel Processing) and of the distributed computation. A common point between distributed systems and MPPs architectures is the notion of message exchange, that allows the communication between processes. An environment of message exchange consists basically of a communication library that, acting as an extension of the programming languages that allow to the elaboration of applications parallel, such as C, C++ and Fortran. In the development of applications parallel, a basic aspect is on to the analysis of performance of the same ones. Several can be the metric ones used in this analysis: time of execution, efficiency in the use of the processing elements, scalability of the application with respect to the increase in the number of processors or to the increase of the instance of the treat problem. The establishment of models or mechanisms that allow this analysis can be a task sufficiently complicated considering parameters and involved degrees of freedom in the implementation of the parallel application. An joined alternative has been the use of collection tools and visualization of performance data, that allow the user to identify to points of strangulation and sources of inefficiency in an application. For an efficient visualization one becomes necessary to identify and to collect given relative to the execution of the application, stage this called instrumentation. In this work it is presented, initially, a study of the main techniques used in the collection of the performance data, and after that a detailed analysis of the main available tools is made that can be used in architectures parallel of the type to cluster Beowulf with Linux on X86 platform being used libraries of communication based in applications MPI - Message Passing Interface, such as LAM and MPICH. This analysis is validated on applications parallel bars that deal with the problems of the training of neural nets of the type perceptrons using retro-propagation. The gotten conclusions show to the potentiality and easinesses of the analyzed tools.
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This paper analyzes the performance of a parallel implementation of Coupled Simulated Annealing (CSA) for the unconstrained optimization of continuous variables problems. Parallel processing is an efficient form of information processing with emphasis on exploration of simultaneous events in the execution of software. It arises primarily due to high computational performance demands, and the difficulty in increasing the speed of a single processing core. Despite multicore processors being easily found nowadays, several algorithms are not yet suitable for running on parallel architectures. The algorithm is characterized by a group of Simulated Annealing (SA) optimizers working together on refining the solution. Each SA optimizer runs on a single thread executed by different processors. In the analysis of parallel performance and scalability, these metrics were investigated: the execution time; the speedup of the algorithm with respect to increasing the number of processors; and the efficient use of processing elements with respect to the increasing size of the treated problem. Furthermore, the quality of the final solution was verified. For the study, this paper proposes a parallel version of CSA and its equivalent serial version. Both algorithms were analysed on 14 benchmark functions. For each of these functions, the CSA is evaluated using 2-24 optimizers. The results obtained are shown and discussed observing the analysis of the metrics. The conclusions of the paper characterize the CSA as a good parallel algorithm, both in the quality of the solutions and the parallel scalability and parallel efficiency
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This work presents the concept, design and implementation of a MP-SoC platform, named STORM (MP-SoC DirecTory-Based PlatfORM). Currently the platform is composed of the following modules: SPARC V8 processor, GPOP processor, Cache module, Memory module, Directory module and two different modles of Network-on-Chip, NoCX4 and Obese Tree. All modules were implemented using SystemC, simulated and validated, individually or in group. The modules description is presented in details. For programming the platform in C it was implemented a SPARC assembler, fully compatible with gcc s generated assembly code. For the parallel programming it was implemented a library for mutex managing, using the due assembler s support. A total of 10 simulations of increasing complexity are presented for the validation of the presented concepts. The simulations include real parallel applications, such as matrix multiplication, Mergesort, KMP, Motion Estimation and DCT 2D
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The increasing complexity of integrated circuits has boosted the development of communications architectures like Networks-on-Chip (NoCs), as an architecture; alternative for interconnection of Systems-on-Chip (SoC). Networks-on-Chip complain for component reuse, parallelism and scalability, enhancing reusability in projects of dedicated applications. In the literature, lots of proposals have been made, suggesting different configurations for networks-on-chip architectures. Among all networks-on-chip considered, the architecture of IPNoSys is a non conventional one, since it allows the execution of operations, while the communication process is performed. This study aims to evaluate the execution of data-flow based applications on IPNoSys, focusing on their adaptation against the design constraints. Data-flow based applications are characterized by the flowing of continuous stream of data, on which operations are executed. We expect that these type of applications can be improved when running on IPNoSys, because they have a programming model similar to the execution model of this network. By observing the behavior of these applications when running on IPNoSys, were performed changes in the execution model of the network IPNoSys, allowing the implementation of an instruction level parallelism. For these purposes, analysis of the implementations of dataflow applications were performed and compared
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The Compact Muon Solenoid (CMS) detector is described. The detector operates at the Large Hadron Collider (LHC) at CERN. It was conceived to study proton-proton (and lead-lead) collisions at a centre-of-mass energy of 14 TeV (5.5 TeV nucleon-nucleon) and at luminosities up to 10(34)cm(-2)s(-1) (10(27)cm(-2)s(-1)). At the core of the CMS detector sits a high-magnetic-field and large-bore superconducting solenoid surrounding an all-silicon pixel and strip tracker, a lead-tungstate scintillating-crystals electromagnetic calorimeter, and a brass-scintillator sampling hadron calorimeter. The iron yoke of the flux-return is instrumented with four stations of muon detectors covering most of the 4 pi solid angle. Forward sampling calorimeters extend the pseudo-rapidity coverage to high values (vertical bar eta vertical bar <= 5) assuring very good hermeticity. The overall dimensions of the CMS detector are a length of 21.6 m, a diameter of 14.6 m and a total weight of 12500 t.
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In some applications with case-based system, the attributes available for indexing are better described as linguistic variables instead of receiving numerical treatment. In these applications, the concept of fuzzy hypercube can be applied to give a geometrical interpretation of similarities among cases. This paper presents an approach that uses geometrical properties of fuzzy hypercube space to make indexing and retrieval processes of cases.
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A novel hybrid high power rectifier capable to achieve unity power factor is proposed in this paper. Single-phase SEPIC rectifiers are associated in parallel with each leg of three-phase 6-pulse diode rectifier resulting in a programmable input current waveform structure. In this paper it is described the principles of operation of the proposed converter with detailed simulation and experimental results. For a total harmonic distortion of the input line current (THDI) less than 2% the rated power of the SEPIC rectifiers is 33%. Therefore, power rating of the SEPIC parallel converters is a fraction of the output power, on the range of 20% to 33% of the nominal output power, making the proposed solution economically viable for high power installations, with fast pay back of the investment. Moreover, retrofits to existing installations are also possible with this proposed topology, since the parallel path can be easily controlled by integration with the already existing de-link. Experimental results are presented for a 3 kW implemented prototype, in order to verify the developed analysis.