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检索条件"任意字段=International Conference on Parallel Distributed and Grid Computing"

共 34218 条记录，以下是4811-4820 订阅

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Fog Robotics Algorithms for distributed Motion Planning Using Lambda Serverless computing

Fog Robotics Algorithms for Distributed Motion Planning Usin...

引用

IEEE international conference on Robotics and Automation (ICRA)

作者： Ichnowski, Jeffrey Lee, William Murta, Victor Paradis, Samuel Alterovitz, Ron Gonzalez, Joseph E. Stoica, Ion Goldberg, Ken Univ Calif Berkeley Berkeley CA 94720 USA Univ N Carolina Chapel Hill NC 27599 USA

ISBN: (纸本)9781728173955

For robots using motion planning algorithms such as RRT and RRT*, the computational load can vary by orders of magnitude as the complexity of the local environment changes. To adaptively provide such computation, we propose Fog Robotics algorithms in which cloud-based serverless lambda computing provides parallel computation on demand. To use this parallelism, we propose novel motion planning algorithms that scale effectively with an increasing number of serverless computers. However, given that the allocation of computing is typically bounded by both monetary and time constraints, we show how prior learning can be used to efficiently allocate resources at runtime. We demonstrate the algorithms and application of learned parallel allocation in both simulation and with the Fetch commercial mobile manipulator using Amazon Lambda to complete a sequence of sporadically computationally intensive motion planning tasks.

关键词： Motion planning

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Simple yet Efficient Deployment of Scientific Applications in the Cloud

Simple yet Efficient Deployment of Scientific Applications i...

引用

international conference on parallel and distributed Systems (ICPADS)

作者： Leyi Sun Yifan Zhuo Olivier Marin New York University Shanghai Shanghai China

ISBN: (纸本)9781665408790

Scientific applications can benefit greatly from getting deployed on a cloud computing platform, but such deployments require skills and expertise that are beyond the reach of many scientists. We address this issue with a framework that simplifies the process of writing cloud-ready scientific applications, and that automates their deployment and execution on top of cloud infrastructures. This paper presents (1) our domain-specific language whose syntax is simple to learn and use, and (2) our compiler that exploits potential data parallelism opportunities and handles load balancing automatically for the users. Our framework prototype demonstrates the feasibility of our approach, and our scalability analysis looks promising.

关键词： Cloud computing Fault tolerance Runtime Scalability Fault tolerant systems Prototypes Writing

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Uncertainty-aware Forecasting of Renewable Energy Sources

Uncertainty-aware Forecasting of Renewable Energy Sources

引用

IEEE international conference on Big Data and Smart computing (BigComp)

作者： Pekaslan, Direnc Wagner, Christian Garibaldi, Jonathan M. Marin, Luis G. Saez, Doris Univ Nottingham Sch Comp Sci Intelligent Modelling & Anal IMA Grp Nottingham England Univ Nottingham Sch Comp Sci Lab Uncertainty Data & Decis Making LUCID Nottingham England Univ Chile Dept Elect Engn Santiago Chile

ISBN: (纸本)9781728160344

Smart grid systems are designed to enable the efficient capture and intelligent distribution of electricity across a distributed set of utilities. They are an essential component of increasingly important renewable energy sources, where it is vital to forecast the levels of energy being fed into and drawn from the grid. However, because of the high levels of uncertainty affecting real-world environments, accurate forecasting for example of wind power generation - being directly dependent on meteorological parameters and climatic conditions - is extremely challenging. Fuzzy Logic systems are frequently used in control systems to leverage their capacity for handling varying levels of uncertainty. In most cases, while uncertainty affecting the systems is captured in fuzzy sets (FSs), the final output of such systems is reduced to a crisp number (e.g. a control output). The latter process, while providing an efficient pathway to generating a specific control output, at the same time implies substantial information loss, as the uncertainty information captured in the FS outputs of these systems is effectively discarded. In this paper, we explore the potential of Mamdani fuzzy logic system based forecasting in order to generate not only a numeric forecast of the energy generated, but to also generate uncertainty intervals around said forecast indicating the level of uncertainty associated with the prediction. The proposed model is explored using both synthetic and smart-grid specific real-world (wind power) time series datasets. The results of the study indicate that utilising the `complete' FS output can provide valuable additional information in terms of the reliability of the forecast without any extra computational cost. At a general level, the approach indicates strong potential for leveraging the uncertainty information in fuzzy system outputs - which is commonly discarded - in real world applications.

关键词： Forecasting Uncertainty Intervals Smart-grid Renewable Energy

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Improving Efficiency in Large-Scale Decentralized distributed Training

Improving Efficiency in Large-Scale Decentralized Distribute...

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IEEE international conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Mang, Wei Cui, Xiaodong Kayi, Abdullah Liu, Mingrui Finkler, Ulrich Kingsbury, Brian Saon, George Mroueh, Youssef Buyuktosunoglu, Alper Das, Payel Kung, David Picheny, Michael IBM Res Yorktown Hts NY 10598 USA Univ Iowa Iowa City IA USA

ISBN: (纸本)9781509066315

Decentralized parallel SGD (D-PSGD) and its asynchronous variant Asynchronous parallel SGD (AD-PSGD) is a family of distributed learning algorithms that have been demonstrated to perform well for large-scale deep learning tasks. One drawback of (A)D-PSGD is that the spectral gap of the mixing matrix decreases when the number of learners in the system increases, which hampers convergence. In this paper, we investigate techniques to accelerate (A)D-PSGD based training by improving the spectral gap while minimizing the communication cost. We demonstrate the effectiveness of our proposed techniques by running experiments on the 2000-hour Switch-board speech recognition task and the ImageNet computer vision task. On an IBM P9 supercomputer, our system is able to train an LSTM acoustic model in 2.28 hours with 7.5% WER on the Hub5-2000 Switchboard (SWB) test set and 13.3% WER on the CallHome (CH) test set using 64 V100 GPUs and in 1.98 hours with 7.7% WER on SWB and 13.3% WER on CH using 128 V100 GPUs, the fastest training time reported to date.

关键词： distributed training decentralized SGD parallel computing automatic speech recognition image recognition

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distributed Energy Storage Aggregator for Power System Frequency Control

Distributed Energy Storage Aggregator for Power System Frequ...

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2020 international conference on Intelligent computing, Automation and Systems, ICICAS 2020

作者： Sun, Feng Li, Ping Liu, Siqi Hao, Jiancheng Yang, Hongyu Wang, Shiyuan Ye, Peng State Grid Liaoning Electric Power Co. Ltd. Electric Power Research Institue Shenyang110006 China Shenyang Institute of Engineering Shenyang110136 China

ISBN: (纸本)9781728191461

With the large amount configuration of distributed energy storage (DES), the randomness of its output and access point will challenge the traditional operation mode of power grid. If DES is connected to the power system in disorder as a random disturbance power source, it will have a negative impact on the power quality, and will cause the unreasonable utilization of energy storage resources. However, the economy of power system operation can be improved by regulating the idle DESs to provide auxiliary services for the demand of power system. In this paper, a control strategy of distributed energy storage aggregator (DESA) to participate in the power system frequency control is proposed. The aggregation of DESs is based on the analytic hierarchy process structure. By integrating the DES Aggregator into the power system load frequency control, the frequency regulation ability is improved. Case studies verify the effectiveness of the proposed control strategy. © 2020 IEEE.

关键词： Electric power transmission networks

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Bidirectional Smart grid Communication Platform with Network Devices: A Case Study

Bidirectional Smart Grid Communication Platform with Network...

引用

Advancements in Electrical, Electronics, Communication, computing and Automation (ICAECA), international conference on

作者： V Shanmugasundaram T Anuradha. Sakinala Govardhan Vishal Moyal V Raja Kumar Bandukula Tirupathi Kumar Sona College of Technology Salem Tamilnadu India KCG College of Technology Chennai Tamilnadu India Chaitanya Deemed to be University Warangal Telangana India SVKMs Institute of Technology Dhule Maharashtra India GITAM Deemed to be University Visakhapatnam India Koneru Lakshmaiah Education Foundation Hyderabad Telangana India

ISBN: (纸本)9781665428309

There are two-way streams of electricity and information utilized to build a distributed, automated network of energy distribution in the intelligent grid known as the next-generation grid. In this study, the various strategies and technologies for communicating with the smart grid are described. One of the primary goals of the project was to create a communication platform that handles network devices with bidirectional connection, plus real-time management of the energy data, along with new services to govern the quality of electric signals.

关键词： Renewable energy sources Automation Systems architecture Computer architecture Real-time systems Smart grids Telecommunication computing

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HeAT - a distributed and GPU-accelerated Tensor Framework for Data Analytics 8

HeAT - a Distributed and GPU-accelerated Tensor Framework fo...

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8th IEEE international conference on Big Data (Big Data)

作者： Goetz, Markus Debus, Charlotte Coquelin, Daniel Krajsek, Kai Comito, Claudia Knechtges, Philipp Hagemeier, Bjorn Tarnawa, Michael Hanselmann, Simon Siggel, Martin Basermann, Achim Streit, Achim German Aerosp Ctr Inst Software Technol SC Cologne Germany Forschungszentrum Julich Inst Rio & Geosci Agrosphere IBG 3 Julich Germany Forschungszentrum Julich FZJ Julich Supercomp Ctr JSC Julich Germany Karlsruhe Inst Technol KIT Steinbuch Ctr Comp SCC Karlsruhe Germany

ISBN: (纸本)9781728162515

To cope with the rapid growth in available data, the efficiency of data analysis and machine learning libraries has recently received increased attention. Although great advancements have been made in traditional array-based computations, most are limited by the resources available on a single computation node. Consequently, novel approaches must be made to exploit distributed resources, e.g. distributed memory architectures. To this end, we introduce IleAT, an array-based numerical programming framework for large-scale parallel processing with an easy-to-use NumPy-like API. HeAT utilizes PyTorch as a node-local eager execution engine and distributes the workload on arbitrarily large high-performance computing systems via MPI. It provides both low-level array computations, as well as assorted higher-level algorithms. With HeAT, it is possible for a NumPy user to take full advantage of their available resources, significantly I owering the bartier to distributed data analysis. When compared to similar frameworks, HeAT achieves speedups of up to two orders of magnitude.

关键词： IleAT Tensor Framework High-performance computing PyTorch NumPy Message Passing Interface CPU Rig Data Analytics Machine Learning Dask Model parallelism parallel Application Frameworks

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An efficient bi-objective optimization workflow using the distributed quasi-Newton method and its application to field development optimization

An efficient bi-objective optimization workflow using the di...

引用

SPE Reservoir Simulation conference 2021, RSC 2021

作者： Wang, Yixuan Alpak, Faruk Gao, Guohua Chen, Chaohui Vink, Jeroen Wells, Terence Saaf, Fredrik Shell Exploration and Production Company Shell International Exploration and Production Co. Shell Global Solution US Inc. Shell Global Solutions International BV

ISBN: (纸本)9781613997475

Although it is possible to apply traditional optimization algorithms to determine the Pareto front of a multiobjective optimization problem, the computational cost is extremely high, when the objective function evaluation requires solving a complex reservoir simulation problem and optimization cannot benefit from adjoint-based gradients. This paper proposes a novel workflow to solve bi-objective optimization problems using the distributed quasi-Newton (DQN) method, which is a well-parallelized and derivative-free optimization (DFO) method. Numerical tests confirm that the DQN method performs efficiently and robustly. The efficiency of the DQN optimizer stems from a distributed computing mechanism which effectively shares the available information discovered in prior iterations. Rather than performing multiple quasi-Newton optimization tasks in isolation, simulation results are shared among distinct DQN optimization tasks or threads. In this paper, the DQN method is applied to the optimization of a weighted average of two objectives, using different weighting factors for different optimization threads. In each iteration, the DQN optimizer generates an ensemble of search points (or simulation cases) in parallel and a set of non-dominated points is updated accordingly. Different DQN optimization threads, which use the same set of simulation results but different weighting factors in their objective functions, converge to different optima of the weighted average objective function. The non-dominated points found in the last iteration form a set of Pareto optimal solutions. Robustness as well as efficiency of the DQN optimizer originates from reliance on a large, shared set of intermediate search points. On the one hand, this set of searching points is (much) smaller than the combined sets needed if all optimizations with different weighting factors would be executed separately;on the other hand, the size of this set produces a high fault tolerance. Even if some simulati

关键词： Efficiency

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Data-Adapted parallel Merge Sort 25th

Data-Adapted Parallel Merge Sort

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25th international conference on parallel and distributed computing (Euro-Par)

作者： Holke, Johannes Ruettgers, Alexander Klitz, Margrit Basermann, Achim German Aerosp Ctr DLR Dept High Performance Comp Inst Software Technol D-51147 Cologne Germany

ISBN: (纸本)9783030483401;9783030483395

In the aerospace sciences we produce huge amounts of data. This data must be arranged in a meaningful order, so that we can analyze or visualize it. In this paper we focus on data that is distributed among computer processes and then needs to be sorted by a single root process for further analysis. We assume that the memory on the root process is too small to hold all sorted data at once, so that we have to perform the sorting and processing of data chunk-wise. We prove the efficiency of our approach in weak scaling tests, where we achieve a near constant bandwidth. Additionally, we obtain a considerable speed up compared to the standard parallel external sort. We also demonstrate the usefulness of our algorithm in a real-life aviation application.

关键词： parallel sorting High-performance computing Merge sort Data analysis Aerospace sciences

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Research and Design of Virtual Terminal for New Generation Electricity Information Collection System

Research and Design of Virtual Terminal for New Generation E...

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Electronics and Devices, Computational Science (ICEDCS), international conference on

作者： Yukun Xu Feng Huang Chao Jiang Shuang Xiao State Grid Shanghai Electric Power Shanghai China

ISBN: (数字)9781665455411

ISBN: (纸本)9781665455428

Design a power consumption information acquisition system simulation electric energy meter, use communication technology, computer technology and automatic control technology to monitor and manage the power load comprehensive system, collect, process and real-time monitor the power consumption information of power users, realize the use of Automatic collection of electrical information, monitoring of abnormal metering, power quality monitoring, power consumption analysis and management, related information release, distributed energy monitoring, information exchange of intelligent electrical equipment and other functions. The system user interface integrates application logic through services, improves the data coordination ability of the system, effectively reduces the data access load, and improves the system expansion ability through load balancing.

关键词： Meters Power demand Scientific computing User interfaces Planning Systems simulation Resource management

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