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共 3294 条记录，以下是1491-1500 订阅

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Bidirectional DC-DC Converter Using Modular Marx Power Switches and Series/parallel Inductor for High-Voltage Applications

引用

5th IFIP WG 5.5/SOCOLNET Doctoral conference on Computing, Electrical and Industrial Systems, DoCEIS 2014

作者： Luís, Ricardo Silva, J.Fernando A. Quadrado, José C. Pinto, Sónia Ferreira de Mesquita e Sousa, Duarte Instituto Superior de Engenharia de Lisboa R. Conselheiro Emídio Navarro 1959-007 Lisboa Portugal Instituto Superior Técnico Instituto Superior Técnico INESC-id DEEC AC Energia Av. Rovisco Pais 1049-001 Lisboa Portugal

ISBN: (纸本)9783642547331

this paper presents the modelling and the numerical simulation results of a bidirectional DC-DC converter using modular Marx power electronic switches to be applicable in high-voltage converters. To achieve ample voltage ratio between high-voltage and low-voltage sides, the proposed DC-DC converter uses also a power electronic circuit, in the low-voltage converter side, that changes the connection between three inductors, as a series or parallel connection, to aid the energy transfer to the inductors. © IFIP international Federation for Information processing 2014.

关键词： DC-DC converters

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An improved simulated annealing heuristic for static partitioning of task graphs onto heterogeneous architectures

An improved simulated annealing heuristic for static partiti...

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international conference on parallel and Distributed Systems (ICPADS)

作者： Aravind Vasudevan Avinash Malik David Gregg Trinity College School of Computer Science and Statistics Dublin University of Auckland

We present a simulated annealing based partitioning technique for mapping task graphs, onto heterogeneous processing architectures. Task partitioning onto homogeneous architectures to minimize the makespan of a task graph, is a known NP-hard problem. Heterogeneity greatly complicates the aforementioned partitioning problem, thus making heuristic solutions essential. A number of heuristic approaches have been proposed, some using simulated annealing. We propose a simulated annealing method with a novel NEXT STATE function to enable exploration of different regions of the global search space when the annealing temperature is high and making the search more local as the temperature drops. the novelty of our approach is two fold: (1) we go a step further than the existing scientific literature, considering heterogeneity at levels of task parallelism, data parallelism and communication. (2) We present a novel algorithm that uses simulated annealing to find better partitions in the presence of heterogeneous architectures, data parallel execution units, and significant data communication costs. We conduct a statistical analysis of the performance of the proposed method, which shows that our approach clearly outperforms the existing simulated annealing method.

关键词： Simulated annealing parallel processing Computer architecture Linear programming Temperature distribution Heuristic algorithms Standards

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Fast ICA on Modern GPU architectures

Fast ICA on Modern GPU Architectures

引用

IEEE international conference on parallel and Distributed Computing, Applications and Technologies (PDCAT)

作者： Max Plauth Frank Feinbube Peter Tröger Andreas Polze Hasso Plattner Institute University of Potsdam Potsdam Germany

Blind Signal Separation is an algorithmic problem class that deals with the restoration of original signal data from a signal mixture. Implementations, such as Fast ICA, are optimized for parallelization on CPU or first-generation GPU hardware. With the advent of modern, compute centered GPU hardware with powerful features such as dynamic parallelism support, these solutions no longer leverage the available hardware performance in the best-possible way. We present an optimized implementation of the FastICA algorithm, which is specifically tailored for next-generation GPU architectures such as Nvidia Kepler. Our proposal achieves a two digit factor of speedup in the prototype implementation, compared to a multithreaded CPU implementation. Our custom matrix multiplication kernels, tailored specifically for the use case, contribute to the speedup by delivering better performance than the state-of-the-art CUBLAS library.

关键词： Graphics processing units Kernel Hardware Signal processing algorithms Matrix decomposition Covariance matrices Computer architecture

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HadoopM: A Message-Enabled Data processing System on Large Clusters

HadoopM: A Message-Enabled Data Processing System on Large C...

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19th international conference on Database Systems for Advanced Applications (DASFAA)

作者： Pan, Wei Li, Zhanhuai Suo, Bo Wang, Zhuo Northwestern Polytech Univ Sch Comp Sci & Technol Xian 710072 Peoples R China

ISBN: (纸本)9783662439845;9783662439838

MapReduce as a popular platform for solving embarrassingly parallel problems has been extensively used on large commodity clusters. However constrained by embarrassingly parallel assumption, some computation patterns are not easy to express in MapReduce, and in some cases performance and efficiency can not be achieved without communication between tasks, such as iteration and map phase filtration from a holistic perspective. this paper presents HadoopM, a message-enhanced version of Hadoop MapReduce architecture that it breaks the key embarrassingly parallel assumption and can execute the MR jobs in a more efficient and elegant way. HadoopM allows user-defined message to be passed between mappers or reducers by two message passing mechanisms: lightweight and heavyweight, and asynchronous and synchronous message passing are both supported by system. HadoopM retains the scalability and fault-tolerance of Hadoop and is binary compatible with Hadoop Mapreduce. Our experimental results demonstrate the superiority of modified version over original Hadoop MapReduce on a range of algorithms. In some cases, such as PageRank and Skyline, HadoopM significantly boosts the job performance up to 50%.

关键词： MapReduce

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Agent-based mood spread diffusion model for GPU

Agent-based mood spread diffusion model for GPU

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IEEE international conference on Software Engineering and Service Sciences (ICSESS)

作者： First Xiaotong Wang Second Zhen Liu third Su Deng College of Information System and Management National University of Defence Technology Changsha Hunan China

ISBN: (纸本)9781479932801

By the analysis of problems of mood spread diffusion, combining the theory of Agent, Agent-Based mood diffusion model was established, using CUDA programming tool, which is suitable for parallel computing of the part to carry on the design implementation, thus proving the GPU computing can improve the efficiency of the model calculation.

关键词： Graphics processing units Mood Computational modeling Analytical models Mathematical model Kernel parallel processing

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7th international conference on Similarity Search and Applications (SISAP)

作者： Krulis, Martin Bednarek, David Yaghob, Jakub Zavoral, Filip Charles Univ Prague Fac Math & Phys Parallel Architectures Algorithms Applicat Res Gr Prague Czech Republic

ISBN: (纸本)9783319119885;9783319119878

In the past few years, we have observed a trend of increasing cooperation between computer science and other empirical sciences such as physics, biology, or medical fields. this e-science synergy opens new challenges for the computer science and triggers important advances in other areas of research. In our particular case, we are facing an astroinformatics challenge of analysing stellar spectra in order to establish automated classification methods for recognizing different types of Be stars. We have chosen similarity search methods, which are effectively utilized in other domains like multimedia content-based retrieval for instance. this paper presents our analysis of the problematics and proposed a solution based on Signature Quadratic Form Distance and feature signatures. We have also conducted intensive empirical evaluation which allowed us to determine appropriate configuration for our similarity model.

关键词： similarity SQFD stellar spectra feature signatures astroinformatics classification

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parallel algorithms for Hard Combinatorial Optimisation Problems in Multi-Agent Systems 14

Parallel Algorithms for Hard Combinatorial Optimisation Prob...

引用

international conference on Autonomous Agents and Multiagent Systems

作者： Filippo Bistaffa University of Verona

ISBN: (纸本)9781634391313

Multi-agent systems represent a powerful tool to model several interesting real-world problems. Unfortunately, the limited scalability of many state-of-the-art algorithms hinders their applicability in practical situations: in fact, complex dynamics and interactions among a large number of agents often make the search for an optimal solution an unfeasible task. Against this background, the study and design of new highly parallel computational models could greatly improve solution techniques in the above mentioned fields. In particular, I will introduce two parallel approaches to the coalition formation problem in the context of multi-agent systems, detailing how their performances can benefit from the use of modern parallel architectures.

关键词： Multi-Core GPGPU Coalition Formation Multi-agent systems parallel algorithms Computational modeling parallel architectures

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Document clustering using Multi-Objective Genetic algorithms with parallel programming based on CUDA

Document clustering using Multi-Objective Genetic Algorithms...

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international conference on Informatics in Control, Automation and Robotics (ICINCO)

作者： Jung Song Lee Soon Cheol Park Jong Joo Lee Han Heeh Ham Division of Electronics and Information Engineering Chonbuk National University Jeonju-si Republic of Korea Department of Korean Language and Literature Chonbuk National University Jeonju-si Republic of Korea Department of Archeology and Cultural Anthropology Chonbuk National University Jeonju-si Republic of Korea

In this paper, we propose a method of enhancing Multi-Objective Genetic algorithms (MOGAs) for document clustering with parallel programming. the document clustering using MOGAs shows better performance than other clustering algorithms. However, the overall computation time of the MOGAs is considerably long as the number of documents increases. To effectively avoid this problem, we implement the MOGAs with General-Purpose computing on Graphics processing Units (GPGPU) to compute the document similarities for the clustering. Furthermore, we introduce two thread architectures (Term-threads and Document-threads) in the CUDA (Compute Unified Device Architecture) language. the experimental results show that the parallel MOGAs with CUDA are tremendously faster than the general MOGAs.

关键词： Graphics processing units Genetic algorithms Instruction sets Vectors Linear programming Computer architecture Sociology

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Performance and energy characterization of high-performance low-cost cornerness detection on GPUs and multicores

Performance and energy characterization of high-performance ...

引用

international conference on Information, Intelligence, Systems and Applications (IISA)

作者： Apostolos Glenis Sergios Petridis Institute of Computer Science FORTH Heraclion Greece Institute of Informatics and Telecommunications NCSR “Demokritos” Agia Paraskevi Greece

Feature detection and tracking is an important problem in Computer Vision. Corners in an image are a good indication of features to track. Original algorithms may be expensive even on multicore architectures because they require full convolutions to be performed. Although these can be performed in real time in modern GPUs and multicore CPUs, faster solutions are needed for embedded systems and complex algorithms, given that corner detections is just a step of the analysis process. In this paper we evaluate the performance and energy efficiency of the Harris corner detection algorithm as well as an approximation of it, in both desktop and mobile platforms. the purpose of this paper is three-fold: evaluate the performance gains of GPUs vs. CPUs for several mobile and desktop systems, evaluate whether the Harris approximation provides adequate performance gains to justify its use in mobile and desktop system configurations and, finally, determine which configurations provide real-time performance. According to our evaluation (a) the best GPU solution is 16.3 times faster than the best CPU solution for the desktop case while being 2.6 times more energy efficient and (b) the best GPU solution for the mobile case is 1.2 times faster while being 3.6 times more energy efficient than the respective CPU.

关键词： Graphics processing units Approximation algorithms Mobile communication Real-time systems Detectors Approximation methods Feature extraction

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Fast GPU parallel N-Body tree traversal with Simulated Wide-Warp

Fast GPU parallel N-Body tree traversal with Simulated Wide-...

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international conference on parallel and Distributed Systems (ICPADS)

作者： Wagner M. Nunan Zola Luis C. E. Bona Fabiano Silva Federal University of Paraná Curitiba PR Brazil

ISBN: (纸本)9781479976164

the Barnes-Hut algorithm is a widely used approximation method for the N-Body simulation problem. the irregular nature of this tree walking code presents interesting challenges for its computation on parallel systems. Additional problems arise in effectively exploiting the processing capacity of GPU architectures. We propose and investigate the applicability of software Simulated Wide-Warps (SWW) in this context. To this extent, we explicitly deal with dynamic irregular patterns in data accesses with data remapping and data transformation, by controlling execution flow divergence of threads. We present a new compact data-structure for the tree layout, GPU parallel algorithms for tree transformation and parallel walking using SWW. Benefits of our techniques are in transposing the tree algorithm to execute regular patterns to match the GPU model. Our experiments show significant performance improvement over the best known GPU solutions to this algorithm.

关键词： Instruction sets Kernel Layout Graphics processing units Octrees Registers Indexes

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