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检索条件"主题词=Parallel and distributed computing"

共 271 条记录，以下是201-210 订阅

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Dependable parallel Multi-population Different Evolutionary Particle Swarm Optimization for Voltage and Reactive Power Control in Electric Power Systems 10

Dependable Parallel Multi-population Different Evolutionary ...

引用

10th IEEE International Workshop on Computational Intelligence and Applications (IWCIA)

作者： Yoshida, Hotaka Fukuyama, Yoshikazu Meiji Univ Sch Interdisciplinary Math Sci Tokyo Japan

ISBN: (纸本)9781538604694

This paper presents dependable parallel multipopulation differential evolutionary particle swam optimization (DEEPSO) for voltage and reactive power control (VRPC) in electric power systems. Considering large penetration of renewable energies and deregulated environment of power systems, VRPC requires fast computation even for larger-scale problems. One solutions to increase the computation speed is to use parallel and distributed computing. Since power system is one of the infrastructures of social community, not only fast computation, but also sustainable control (dependability) is strongly required for VRPC. A multi-population model is known to be one of the techniques to improve solution quality. The simulation results with IEEE 118 bus systems indicate that dependable parallel multi-population DEEPSO is superior to parallel DEEPSO using a master-slave model especially for dependability on VRPC.

关键词： Voltage and reactive power control parallel and distributed computing Multi-population Dependability Different Evolutionary Particle Swarm Optimization

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NNB: An Efficient Nearest Neighbor Search Method for Hierarchical Clustering on Large Datasets 9

NNB: An Efficient Nearest Neighbor Search Method for Hierarc...

引用

IEEE 9th International Conference on Semantic computing

作者： Zhang, Wei Zhang, Gongxuan Wang, Yongli Zhu, Zhaomeng Li, Tao Nanjing Univ Sci & Technol Sch Comp Sci & Engn Nanjing 210094 Jiangsu Peoples R China Huaiyin Normal Univ Sch Comp Sci & Technol Huaian 223300 Peoples R China

ISBN: (纸本)9781479979356

Nearest neighbor search is a key technique used in hierarchical clustering. The time complexity of standard agglomerative hierarchical clustering is O(n(3)), while the time complexity of more advanced hierarchical clustering algorithms (such as nearest neighbor chain) is O(n(2)). This paper presents a new nearest neighbor search method called nearest neighbor boundary(NNB), which first divides a large dataset into independent subsets and then finds nearest neighbor of each point in the subsets. When NNB is used, the time complexity of hierarchical clustering can be reduced to O(n log(2) n). Based on NNB, we propose a fast hierarchical clustering algorithm called nearest-neighbor boundary clustering(NBC), and the proposed algorithm can also be adapted to the parallel and distributed computing frameworks. The experimental results demonstrate that our proposal algorithm is practical for large datasets.

关键词： Hierarchical clustering nearest neighbor boundary parallel and distributed computing MapReduce

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A Mobile Agent Team Works Model for HPC Big Data Analysis: Fuzzy Logic Application 5

A Mobile Agent Team Works Model for HPC Big Data Analysis: F...

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5th International Conference on Information and Communication Technology and Accessbility (ICTA)

作者： Benchara, Fatema Zahra Youssfi, Mohamed Bouattane, Omar Ouajji, Hassan Hassan II Univ Casablanca ENSET Mohammedia Lab SSDIA Mohammadia Morocco

ISBN: (纸本)9781467387491

The aim of this paper is to present a distributed implementation of the Type-2 Fuzzy Logic (T2FL) algorithm in a mobile agent based distributed computing platform. The proposed algorithm is assigned to be implemented on an SPMD (Single Program Multiple Data) architecture which is based on a cooperative mobile agent model. It is constituted by a set of mobile agents as AVPEs (Agent Virtual Processing Elements) in order to improve the processing resources needed for performing the big data image segmentation. In this work we focused on the application of this algorithm to process the big data MRI (Magnetic Resonance Images) image. The input image is splitted into elementary images by the Mobile Team leader Agent and encapsulated one per AVPE. Each AVPE perform and exchange the segmentation results and maintain asynchronous communication with their Team leader agent until the convergence of this algorithm. The obtained experimental results in terms of accuracy and efficiency analysis of the proposed distributed implementation are achieved thanks to the mobile agents several interesting skills introduced in this distributed computational model.

关键词： distributed Type-2 Fuzzy algorithm Image Processing Mobile Agents parallel and distributed computing

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Trying to do it all in a single course: a surprisingly good idea

Trying to do it all in a single course: a surprisingly good ...

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Workshop on Education for High Performance computing (EduHPC)

作者： Newhall, Tia Swarthmore Coll Comp Sci Dept Swarthmore PA 19081 USA

ISBN: (纸本)9780738143057

We present the curricular design and learning goals of an upper-level undergraduate course that covers a wide breadth of topics in parallel and distributed computing (PDC), while also providing students with depth of experience and development of problem solving, programming, and analysis skills. We discuss lessons learned from our experiences teaching this course over the past 10 years, and discuss changes and improvements we have made in its offerings, as well as choices and trade-offs we made to achieve a balance, in a single course, between breadth and depth of topic across these two huge fields. Evaluations from students support that our approach works well meeting the goals of exposing students to a broad range of PDC topics, building important PDC thinking and programming skills, and meeting other pedagogical goals of an advance upper-level undergraduate CS course. Although our single course design was created due to constraints common to smaller schools that have fewer faculty resources, smaller curricula, and often fewer required courses for their majors, our experiences with this course lead us to conclude that it is a good approach for an advanced undergraduate course on PDC at any institution.

关键词： parallel and distributed computing CS Education curriculum design

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parallel Multi-population Improved Brain Storm Optimization with Differential Evolution strategies for State Estimation in Distribution Systems using Just In Time Modeling and Correntropy

Parallel Multi-population Improved Brain Storm Optimization ...

引用

IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Azuma, Daichi Fukuyama, Yoshikazu Oi, Akihiro Jintsugawa, Toru Fujimoto, Hisashi Meiji Univ Grad Sch Adv Math Sci Tokyo Japan Fuji Elect Co Ltd Corp R&D Headquarters Tokyo Japan

ISBN: (纸本)9781728124858

This paper proposes parallel multi-population improved brain storm optimization with differential evolution strategies (PMP-IBSODE) for state estimation in distribution systems (SEDS) using just in time (JIT) modeling and correntropy. SEDS is a function which estimates system conditions such as voltage and current everywhere in the distribution system using limited measurement data. When outliers, which are not true values, are measured at the measurement points, JIT modeling and correntropy can be effective. Moreover, application of evolutionary computation techniques is necessary for the SEDS considering of a nonlinear characteristic of an objective function caused by equipment in distribution systems. Various evolutionary computation techniques including IBSODE have been applied to the SEDS. However, speed-up of calculation and high quality estimation results are required because of penetration of renewable energies. An evolutionary computation technique using multi-population and parallel distributed computing is one of solutions for the challenges. The proposed method is verified to speed up computation time and obtain higher quality estimation results than conventional methods.

关键词： multi population improved brain storm optimization with differential evolution strategies parallel and distributed computing state estimation in distribution systems just in time modeling correntropy

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A Low-Cost, High-Performance Implementation of RSA Algorithm Using GPGPU

A Low-Cost, High-Performance Implementation of RSA Algorithm...

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Springer International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS)

作者： Srivatsa, P. S. Sasaank Rao, P. V. R. R. Bhogendra Keshav Mem Inst Technol Hyderabad India Def Res & Dev Lab Hyderabad Kanchanbagh India

ISBN: (纸本)9789811319518;9789811319501

Information security has been of great use in various civilian and defence domains. However, the arduous procedures involved in securely establishing a common key lead to asymmetric-key encryption. The high computational needs of asymmetric-key encryption process made them impractical to be used for real-world applications. The proliferation of low-cost, high-performance computing through GPGPUs made many applications with high-performance requirements feasible to implement and use in real-world applications. A successful attempt has been made to implement RSA algorithm using GPGPU and the results are presented in this paper.

关键词： parallel and distributed computing Heterogeneous computing GPGPU computing OpenCL Asymmetric-key encryption

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Benchmarking Different MapReduce Implementations for Computer-Aided Hardware Development

Benchmarking Different MapReduce Implementations for Compute...

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International Conference on Mathematics and Computers in Sciences and in Industry (MCSI)

作者： Schoemig, Milan Neuhaeuser, David Seidler, Ralf Buecker, H. Martin Univ Jena Dept Comp Sci & Math D-07737 Jena Germany

ISBN: (纸本)9781479943241

In the design of fast arithmetic circuits, the two's complement number representation can be alternatively replaced by a signed digit number representation. Compared to standard full adders used in two's complement arithmetic, signed digit adder cells offer the potential for improved performance. Designing an efficient signed digit adder cell leads to the problem of analyzing 2 to the power of 44 truth tables originating from different signed digit encodings. Since different digit encodings can produce identical truth tables, it is favorable to reduce this large number of truth tables by identifying identical ones. We introduce a novel approach for the solution of this problem using the MapReduce programming model. We take a step towards solving this problem using three different implementations of MapReduce (Hadoop, Disco, and MR-MPI) and compare their performance on an Opteron-based cluster using up to 64 physical cores.

关键词： MapReduce Hadoop Disco MR-MPI Big Data parallel and distributed computing Signed Digit

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A Near Real-Time, parallel and distributed Adaptive Object Detection and Retraining Framework based on AdaBoost Algorithm

A Near Real-Time, Parallel and Distributed Adaptive Object D...

引用

IEEE High Performance Extreme computing Conference (HPEC)

作者： Abualkibash, Munther Mahmood, Ausif Moslehpour, Saeid Univ Bridgeport Comp Sci & Engn Bridgeport CT 06604 USA Univ Bridgeport Elect & Comp Engn Bridgeport CT USA

ISBN: (纸本)9781467392860

Object detection (e.g., face detection) using supervised learning often requires extensive training, resulting in long execution times. If the system requires retraining to accommodate a missed detection, waiting several hours or even days in some cases before the system is ready, may not be acceptable in practical implementations. This paper presents a generalized object detection framework such that the system can efficiently adapt to misclassified data and be retrained within a few minutes. The methodology developed here is based on the popular AdaBoost algorithm for object detection. To reduce the learning time in object detection, we develop a highly efficient, parallel, and distributed AdaBoost algorithm that is able to achieve a training execution time of only 1.4 seconds per feature on 25 workstations. Further, we incorporate this parallel object detection algorithm into an adaptive framework such that a much smaller, optimized training subset is used to yield high detection rates while further reducing the retraining execution time. We demonstrate the usefulness of our adaptive framework on face and car detection.

关键词： parallel and distributed computing object detection face detection car detection AdaBoost master-slave architecture web services

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Introduction to parallel and distributed Programming using N-Body Simulations

Introduction to Parallel and Distributed Programming using N...

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2024 Workshops of the International Conference for High Performance computing, Networking, Storage and Analysis, SC Workshops 2024

作者： Van Craen, Alexander Breyer, Marcel Pfluger, Dirk University of Stuttgart IPVS SC Stuttgart Germany

ISBN: (纸本)9798350355543

This paper describes how we use n-body simulations as an interesting and visually compelling way to teach efficient, parallel, and distributed programming. Our first course focuses on bachelor students introducing them to algorithmic complexities and their implications in real-world problems and state-of-the-art tools like Git, remote development, or C++, by simulating the collision of two galaxies. This project teaches the mapping of mathematical functions into code, efficient implementations, and the pitfalls around complexity and scaling. Our second course targets master students introducing them to intra- and inter-node parallelization. Here, the students simulate our solar system using OpenMP and MPI. The master students further deepen their knowledge of parallelization and scientific computing by choosing custom projects like simulating water molecules or implementing an interactive live visualization using *** courses are structured such that they can easily be adapted by other instructors. All our material is publicly available at https://***/orgs/SCTeaching-NBody. © 2024 IEEE.

关键词： education n-body simulations parallel and distributed computing solar system teaching

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Synthesis of systolic arrays from single assignment algorithm

Synthesis of systolic arrays from single assignment algorith...

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IEEE 1st International Conference on Algorithms and Architectures for parallel Processing (ICA3PP 95)

作者： AlKhalili, AJ CONCORDIA UNIV MONTREALPQCANADA

ISBN: (纸本)0780320182

A systematic method of mapping algorithms from single assignment algorithms into systolic arrays is presented. The method is based on a space-time mapping technique of the index sets. We present a method of generation and selection of a valid transform dependency matrix that will yield an optimal or near optimal systolic array once it is mapped. The proposed method increases the visibility of the architecture in terms of processor delay and communication between processors at the algorithmic level, so that the designer is able to select a desired array at early stages of the design. An example of the proposed method is given.

关键词： parallel and distributed computing parallel algorithms VLSI systolic arrays time-space mapping

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