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IEEE Transactions on Sustainable computing 2024年

作者： Xiang, Zhengzhe Xue, Xizi Chen, Yuanyi Dustdar, Schahram Guo, Minyi Hangzhou City University Hangzhou China Zhejiang University Hangzhou China Austria and part-time ICREA Research Professor at UPF Distributed Systems Group of TU Wien Barcelona Spain Shanghai Jiao Tong University Emerging Parallel Computing Center Shanghai China

Modularized plant factories, characterized by machines executing intelligent control requests to automatically take care of crops, have emerged as a sustainable agricultural paradigm, garnering the attention of Internet-of-Things and agricultural researchers for their production stability and energy efficiency. However, the diversity and pluralism of the plant factory components make it difficult to cooperate and produce crops with better qualities. Therefore, appropriate resource allocation and task scheduling strategies become the key points to optimize the quality of production in the factories by immediately telling which component is more suitable to do what in taking care of the crops. To address this challenge, this paper investigates how the machines of the factory can use their unique services and resource to help improve the crops' quality and model the machine cooperation as an online decision-making problem. An α-competitive approach called OnATS is designed based on the transformation of the original problem, and the experiments show that the proposed algorithm is superior to the baselines. Additionally, this paper explores the impact of different system configurations on the proposed method and shows that the proposed approach has broad applicability. © 2016 IEEE.

关键词： Plant Factory Resource Allocation Service Deployment Task Assignment

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research on the weighted reconstruction of metabolic networks

Research on the weighted reconstruction of metabolic network...

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第五届中国蛋白质组学大会暨首届粤港蛋白质组学学术交流会

作者： Zhou Tingting Wang Zhenghua Chan, K.C.C. Beijing Proteome Research Center BeijingP.R.China102206 National Laboratory for Parallel & Distributed ProcessingNational University of Deference and TechnologyChangshaP.R.China 410073 Department of computingthe HongKong Polytechnic UniversityHonghumHongkong Department of computing the HongKong Polytechnic UniversityHonghumHongkong National Laboratory for Parallel & Distributed Processing National University of Deference and TechnologyChangshaP.R.China 410073

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WADE: a Web-based automated parallel CAD environment

WADE: a Web-based automated parallel CAD environment

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International Conference on High Performance computing

作者： D.R. Chakrabarti P.G. Joisha J.A. Chandy D. Krishnaswamy V. Krishnaswamy P. Banerjee Center for Parallel and Distributed Computing Electrical and Computer Engineering Department Northwestern University Evanston IL USA Sierra Vista Research Inc. Los Gatos CA USA Intel Corporation Folsom CA USA Intel Corporation OR USA

We present a novel framework of a Web-based automated parallel CAD environment. The goal of this project is to make available to the CAD community a growing number of design and test applications that support standard interfaces and execute efficiently in a parallel environment. The design files of a user working on a remote machine are transparently shipped to the local Compute center, the relevant computation is performed in a parallel environment and then the results are returned back to the user. A job submission and scheduling tool ensures proper load balance and maximal usage of the various parallel machines. The whole process is done efficiently and transparently without the user having to bother about any low-level details. At present, a number of parallel CAD tools including a placement tool, a fault simulator and a VHDL simulator are supported. Results from a preliminary implementation are impressive and show the feasibility of the approach.

关键词： Design automation Concurrent computing Contracts Electrical capacitance tomography Software tools Pricing Computer networks Circuits Cities and towns Testing

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MANIPULATIONS OF OCTREES AND QUADTREES ON MULTIPROCESSORS

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International Journal of Pattern Recognition and Artificial Intelligence 1994年第2期8卷 439-455页

作者： VIPIN CHAUDHARY K. KUMARI P. ARUNACHALAM J.K. AGGARWAL Parallel and Distributed Computing Laboratory Department of Electrical and Computer Engineering Wayne State University Detroit MI 48202 USA Sun Microsystems 2820 Orchard Parkway San Jose CA 95134 USA Computer and Vision Research Center Department of Electrical and Computer Engineering University of Texas at Austin Austin Texas 78712–1084 USA

Octrees offer a powerful means for representing and manipulating 3-D objects. This paper presents an implementation of octree manipulations using a new approach on a shared memory architecture. Octrees are hierarchical data structures used to model 3-D objects. The manipulation of these data structures involves performing independent computations on each node of the octree. Octrees are much easier to deal with than other forms of representations used to model 3-D objects especially where extensive manipulations are involved. When these operations are distributed among multiple processing elements (PEs) and executed simultaneously, a significant speedup may be achieved. Manipulations such as a complement, a union, an intersection and other operations such as finding the volume and centroid which this paper describes are implemented on the Sequent Balance multiprocessor. In this approach the PEs are allocated dynamically, resulting in a uniform load balancing among them. The experimental results presented illustrate the feasibility of the approach. Although this evaluation has been originally done for shared memory machines, it will provide insight for the evaluation of other architectures.

关键词： Shared memory architecture dynamic allocation union intersection orthogonal views

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An efficient algorithm for managing a parallel heap

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parallel Algorithms and Applications 1994年第3-4期4卷 281-299页

作者： Das, Sajal K. Horng, Wen-Bing Moon, Gyo S. Center for Research in Parallel and Distributed Computing Department of Computer Science University of North Texas Denton TX 76203-6886 United States Dept. of Computer Science and Information Engineering Tamkang Univ Tamsui Taipei Taiwan

We design a cost-optimal algorithm for managing a parallel heap on an exclusive-read exclusive-write (EREW), parallel random access machine (PRAM) model. We also analyze the time and space complexities of our algorithm, which efficiently employs p processors in the range 1 ≤ p ≤ n, where n is the maximum number of items in the parallel heap. It is assumed that a delete-think-insert cycle is repeatedly performed, and each processor requires an arbitrary but the same amount of time (called the think time) for processing an item which in turn generates at most two new items. The use of a global data structure for each level of the heap helps reduce the working memory space required. The time complexity for deleting p items of the highest priority from the parallel heap is O(log p), while that for inserting at most 2p new items is O(log n). With or without incorporating the think time, the speedup of our algorithm is shown to be linear, i.e. O(p). Hence this algorithm is an improvement in time over the one proposed by Deo and Prasad [5, 6]. © 1994, Taylor & Francis Group, LLC. All rights reserved.

关键词： Data structure EREW PRAM Heap Linear speedup parallel algorithm Priority queue

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MTD: Multi-Timestep Detector for Delayed Streaming Perception

arXiv

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arXiv 2023年

作者： Huang, Yihui Chen, Ningjiang School of Computer and Electronic Information Guangxi University Nanning China Guangxi Intelligent Digital Services Research Center of Engineering Technology Nanning China Key Laboratory of Parallel Distributed and Intelligent Computing Guangxi University Education Department of Guangxi Zhuang Autonomous Region Nanning China

Autonomous driving systems require real-time environmental perception to ensure user safety and experience. Streaming perception is a task of reporting the current state of the world, which is used to evaluate the delay and accuracy of autonomous driving systems. In real-world applications, factors such as hardware limitations and high temperatures inevitably cause delays in autonomous driving systems, resulting in the offset between the model output and the world state. In order to solve this problem, this paper propose the Multi-Timestep Detector (MTD), an end-to-end detector which uses dynamic routing for multi-branch future prediction, giving model the ability to resist delay fluctuations. A Delay Analysis Module (DAM) is proposed to optimize the existing delay sensing method, continuously monitoring the model inference stack and calculating the delay trend. Moreover, a novel Timestep Branch Module (TBM) is constructed, which includes static flow and adaptive flow to adaptively predict specific timesteps according to the delay trend. The proposed method has been evaluated on the Argoverse-HD dataset, and the experimental results show that it has achieved state-of-the-art performance across various delay settings. Copyright © 2023, The Authors. All rights reserved.

关键词： Autonomous vehicles

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Knowledge Distillation with Source-free Unsupervised Domain Adaptation for BERT Model Compression

Knowledge Distillation with Source-free Unsupervised Domain ...

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International Conference on Computer Supported Cooperative Work in Design

作者： Jing Tian Juan Chen Ning Jiang Chen Lin Bai Suqun Huang School of Computer and Electronic Information Guangxi University Nanning China Guangxi Intelligent Digital Services Research Center of Engineering Technology Nanning China Education Department of Guangxi Zhuang Autonomous Region Key Laboratory of Parallel Distributed and Intelligent Computing (Guangxi University) Nanning China

The pre-training language model BERT has brought significant performance improvements to a series of natural language processing tasks, but due to the large scale of the model, it is difficult to be applied in many practical application scenarios. With the continuous development of edge computing, deploying the models on resource-constrained edge devices has become a trend. Considering the distributed edge environment, how to take into account issues such as data distribution differences, labeling costs, and privacy while the model is shrinking is a critical task. The paper proposes a new BERT distillation method with source-free unsupervised domain adaptation. By combining source-free unsupervised domain adaptation and knowledge distillation for optimization and improvement, the performance of the BERT model is improved in the case of cross-domain data. Compared with other methods, our method can improve the average prediction accuracy by up to around 4% through the experimental evaluation of the cross-domain sentiment analysis task.

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distributed Simulation and the Grid: Position Statements

Distributed Simulation and the Grid: Position Statements

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International Workshop/Symposium on distributed Simulation and Real-Time Applications (DS-RT)

作者： S.J.E. Taylor G.V. Popescu J.M. Pullen S.J. Turner Centre for Applied Simulation Modeling Brunei University Uxbridge Middlesex UK IBM Thomas J. Watson Research Center Yorktown Heights NY USA C3I Center George Mason University Fairfax VA USA Parallel & Distributed Computing Centre Nanyang Technological University Singapore

The Grid provides a new and unrivaled technology for large scale distributed simulation as it enables collaboration and the use of distributed computing resources. This panel paper presents the views of four researchers in the area of distributed Simulation and the Grid. Together we try to identify the main research issues involved in applying Grid technology to distributed simulation and the key future challenges that need to be solved to achieve this goal. Such challenges include not only technical challenges, but also political ones such as management methodology for the Grid and the development of standards. The benefits of the Grid to end-user simulation modelers also are discussed.

关键词： Grid computing Resource management Delay Government Web and internet services Computer aided manufacturing parallel processing Feedback Industrial economics Investments

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MMDSSE: Multi-client and Multi-keyword Dynamic Searchable Symmetric Encryption for Cloud Storage

MMDSSE: Multi-client and Multi-keyword Dynamic Searchable Sy...

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Annual Conference on Privacy, Security and Trust, PST

作者： Panyu Wu Zhenfu Cao Jiachen Shen Xiaolei Dong Yihao Yang Jun Zhou Liming Fang Zhe Liu Chunpeng Ge Chunhua Su Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai China Research Center for Basic Theories of Intelligent Computing Research Institute of Basic Theories Zhejiang Lab Hangzhou China College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China Science and Technology on Parallel and Distributed Processing Laboratory (PDL) Changsha China Shandong University Jinan China University of Aizu Fukushima Japan

Since data outsourcing poses privacy concerns with data leakage, searchable symmetric encryption (SSE) has emerged as a powerful solution that enables clients to perform query operations on encrypted data while preserving their privacy. Dynamic SSE schemes have been proposed to handle update operations. However, it is shown that updates might increase the risk of information leakage. Meanwhile, to meet the requirement of real-world applications, it is desirable to have the searchable encryption scheme which supports both multiple clients and multi-keyword queries. To address these issues, this paper proposes MMDSSE, a multi-client forward secure dynamic SSE scheme that supports multi-keyword queries. MMDSSE allows the clients narrow down the results by providing an arbitrary subset of the entire archive, and thus suitable for cloud storage environment. Security analysis and experimental evaluations show that MMDSSE is secure and efficient.

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A Fault Classification Prediction Model Based on Loose-Type Wavelet Neural Network for Server Health Management

A Fault Classification Prediction Model Based on Loose-Type ...

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Cloud computing, Big Data Applications and Software Engineering (CBASE), International Conference on

作者： Yi Wei Yingxiong Nong Zhe Li Jian Pan Zhenyu Yang Xiaoqi Lu Ningjiang Chen China Tobacco Guangxi Industrial Co. Ltd Nanning China School of Computer Electronics and Information Guangxi University Nanning China School of Computer Electronics and Information Guangxi University Guangxi Intelligent Digital Services Research Center of Engineering Technology Key Laboratory of Parallel Distributed and Intelligent Computing (Guangxi University) Nanning China

To prevent the serious impact on production efficiency caused by service interruption, data loss, and other issues resulting from server faults, this paper proposes a server fault prediction model named Wavelet Packet Transform Probabilistic Neural Network(WPT-PNN). WPT-PNN loosely mixes wavelet packet transform and probabilistic neural network to achieve quick fault localization and signal denoising effects. The proposed model is validated using server operational data gathered. The experimental results suggest that the WPT-PNN model can effectively manage the challenges of complicated, non-stationary, and noisy signals in the feature extraction stage and extract signal features reliably. In the fault classification prediction stage, our method improves fault prediction accuracy to 81%, and limits the error range within [-2, 4], better matching the requirements for precise and low false-positive fault prediction in servers.

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