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20th IEEE International parallel and distributed processing Symposium, IPDPS 2006

作者： Chu, Rui Xiao, Nong Zhuang, Yongzhen Liu, Yunhao Lu, Xicheng National Key Laboratory for Parallel and Distributed Processing ChangSha HuNan China Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong

ISBN: (纸本)1424400546

Memory-intensive applications often suffer from the poor performance of disk swapping when memory is inadequate. Remote memory sharing schemes, which provide a remote memory that is faster than the local hard disk, are able to improve the performance of such applications. Due to the limitation of being applicable within single clusters only, however, most of the previous remote memory mechanisms, such as the network memory scheme, fail to be extendable into a large scale, distributed, heterogeneous, and dynamic environment. In this work, we propose a service-oriented grid memory sharing scheme, distributed Paging RAM Grid (DPRG). We study the properties and criteria of large scale memory sharing, and then design major operations and optimizations to fit the usage of grid systems. We collect trace from our grid environment, and evaluate DPRG through comprehensive trace-driven simulations. Results show that DPRG significantly outperforms existing remote memory sharing schemes and supports grid computing applications effectively. © 2006 IEEE.

关键词： Storage allocation (computer)

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Contrastive Learning with Diverse Samples 26

Contrastive Learning with Diverse Samples

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26th European Conference on Artificial Intelligence, ECAI 2023

作者： Wu, Lilei Liu, Jie Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha410073 China Laboratory of Digitizing Software for Frontier Equipment National University of Defense Technology Changsha410073 China

ISBN: (纸本)9781643684369

Unsupervised visual representation learning has gained much attention from the computer vision community because of the recent contrastive learning achievements. Current work mainly adopts instance discrimination as the pretext task, which treats every single instance as a different class (negative) and uses a collection of data augmentation techniques to generate more examples (positive) for each class. The idea is straightforward and efficient but will generally cause similar instances to be classified into different classes. Such problem has been defined as 'class collision' in some previous works and is shown to hurt the representation ability. Motivated by this observation, we present a solution to address this issue by filtering similar negative examples from each mini-batch. Concretely, we model the problem as a Determinantal Point Process (DPP) so that similar instances can be filtered stochastically, and diverse samples are expected to be sampled for contrastive training. Besides, we further introduce a priority term for each instance, which indicates the hardness of its positives, so that instances with more hard positives are more likely to be sampled for contributing to the optimization. Our sampling can be efficiently implemented in a feed-forward manner and further accelerated by our encouraged complement DPP. Extensive experimental results demonstrate our priority over the standard setup of contrastive learning. © 2023 The Authors.

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A distributed Approach to Consistent Order Delivery of Concurrent Events in Asynchronous DVEs

A Distributed Approach to Consistent Order Delivery of Concu...

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2010 2nd International Conference on Education technology and Computer(第二届IEEE教育技术与计算机国际会议 ICETC 2010)

作者： Hangjun Zhou Wei Zhang Yuxing Peng Sikun Li Key Laboratory of Science and Technology for National Defence of Parallel and Distributed Processing Key Laboratory of Science and Technology for National Defence of Parallel and Distributed Processing

ISBN: (纸本)9781424463671;9781424463688;9781424463701

In large-scale asynchronous distributed virtual environments(DVEs), one of the difficult problems is to deliver the concurrent events in a consistent order at each node. Generally, the previous consistency control approaches can be classified into two categories: causal order and time stamped order. However, causal order approaches can merely preserve the cause-effect relation of events and time stamped order approaches seem intrinsically complex to be used in serverless large-scale asynchronous DVEs. In this paper, we proposed a novel distributed algorithm to identify the concurrent events and preserve the consistent order delivery of them at different nodes. Simulation studies are also carried out to compare the performance of this algorithm with that of the previous ones. The results show that the new algorithm can effectively deliver the concurrent events in consistent order at each node and is more efficient than the previous algorithms in large-scale asynchronous DVEs.

关键词： distributed virtual environments concurrent events distributed consistency algorithm

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Word-level BERT-CNN-RNN Model for Chinese Punctuation Restoration 6

Word-level BERT-CNN-RNN Model for Chinese Punctuation Restor...

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6th IEEE International Conference on Computer and Communications, ICCC 2020

作者： Zhang, Zhe Liu, Jie Chi, Lihua Chen, Xinhai Science and Technology on Parallel and Distributed Processing Laboratory Laboratory of Software Engineering for Complex Systems National University of Defense Technology Changsha China College of Computer Science and Electronic Engineering Hunan University Changsha China

ISBN: (纸本)9781728186351

Punctuation restoration in speech recognition has a wide range of application scenarios. Despite the widespread success of neural networks methods at performing punctuation restoration for English, there have been only limited attempts for Chinese punctuation restoration. Due to the differences between Chinese and English in terms of grammar and basic semantic units, existing methods for English is not suitable for Chinese punctuation restoration. To tackle this problem, we propose a hybrid model combining the kernel of Bidirectional Encoder Representations from Transformers (BERT), Convolution Neural Network (CNN) and Recurrent Neural Network (RNN). This model employs a flexible structure and special CNN design which can extract word-level features for Chinese language. We compared the performance of the hybrid model with five widely-used punctuation restoration models on the public dataset. Experimental results demonstrate that our hybrid model is simple and efficient. It outperforms other models and achieves an accuracy of 69.1%. © 2020 IEEE.

关键词： Recurrent neural networks

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Modeling complex relationship paths for knowledge graph completion

Modeling complex relationship paths for knowledge graph comp...

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作者： Zeng, Ping Tan, Qingping Meng, Xiankai Zhang, Haoyu Xu, Jianjun College of Computer National University of Defense Technology Changsha China National Key Laboratory for Parallel and Distributed Processing Changsha China

Determining the validity of knowledge triples and filling in the missing entities or relationships in the knowledge graph are the crucial tasks for large-scale knowledge graph completion. So far, the main solutions use machine learning methods to learn the low-dimensional distributed representations of entities and relationships to complete the knowledge graph. Among them, translationmodels obtain excellent performance. However, the proposed translation models do not adequately consider the indirect relationships among entities, affecting the precision of the representation. Based on the long short-term memory neural network and existing translation models, we propose a multiple-module hybrid neural network model called TransP. By modeling the entity paths and their relationship paths, TransP can effectively excavate the indirect relationships among the entities, and thus, improve the quality of knowledge graph completion tasks. Experimental results show that TransP outperforms state-of-the-art models in the entity prediction task, and achieves the comparable performance with previous models in the relationship prediction task. © 2018 The Institute of Electronics, Information and Communication Engineers.

关键词： Knowledge graph

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RETRACTED ARTICLE: parallel block multigrid preconditioner for 3D navier-stokes equations on unstructured grids

RETRACTED ARTICLE: Parallel block multigrid preconditioner f...

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作者： Li, Zongzhe Lu, Yao Cao, Wei Wang, Yongxian Wang, Zhenghua Parallel and Distributed Processing for National Laboratory School of Computer Science National University of Defence Lechnology Changsha Hunan 410073 China

ISBN: (纸本)9781424472369

In this paper, we explore a parallel block multigrid preconditioner based on factorization of the coefficient matrix generated in three-dimensional unstructured grids system. This preconditioner is robust with respect to the magnitude of the mesh size and the coefficient complexity, apply smoothed aggregation algebraic multigrid which using block lower-upper symmetric Gauss-Seidel(BLU-SGS) as smoother to accelerate convergent rate. We focus on this method to three-dimensional, unstructured, large-scale, parallel and NS equations' steady-state simulations. The numerical results which conducted on NACA0012 airfoil indicate that nearly optimal convergence rates and computational complexity for parallel solutions, this method also provide high speedup and efficiency for a series of processors. © 2010 IEEE.

关键词： Navier Stokes equations

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A semantic-based meteorology grid service registry, discovery and composition framework

A semantic-based meteorology grid service registry, discover...

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2006 2nd International Conference on Semantics Knowledge and Grid, SKG

作者： Kaijun, Ren Nong, Xiao Junqiang, Song Weimin, Zhang Tao, Chen National Laboratory for Parallel and Distributed Processing NUDT Changsha Hunan 410073 China College of Science National University of Defense Technology Changsha Hunan 410073 China

ISBN: (纸本)0769532055

Meteorology Grid Computing aims to provide scientist with seamless, reliable, secure and inexpensive access to meteorological resources. In this paper, we presented a semantic-based meteorology grid service registry, discovery and composition framework by combining grid technologies and the advantages of semantic web techniques. The main objective of the framework is to support automating the discovery, selection, and workflow composition of semantically described heterogeneous meteorological grid services, which offers the possibility of facilitating geographically distributed meteorological scientists to resolve complex scientific problems cooperately. With this framework, the key technologies such as semantic registry, semantic matchmaking, QoS ranking and composition model, will be discussed. © 2006 IEEE.

关键词： Grid computing

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A Data-Centric Approach for Efficient and Scalable CFD Implementation on Multi-GPUs Clusters 24th

A Data-Centric Approach for Efficient and Scalable CFD Imple...

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24th International Conference on parallel and distributed Computing, Applications and Technologies, PDCAT 2023

作者： Li, Ruitian Deng, Liang Dai, Zhe Zhang, Jian Liu, Jie Liu, Gang China Aerodynamic Research and Development Center Computational Aerodynamic Institute Mianyang China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha China

ISBN: (纸本)9789819982103

Scalability is a crucial factor determining the performance of massive heterogeneous parallel CFD applications on the multi-GPUs platforms, particularly after the single-GPU implementations have achieved optimal performance through numerous optimizations. A novel Data-Centric hybrid MPI-CUDA CFD model is proposed in this paper to enable efficient scalability of CFD applications on large-scale heterogeneous platforms. Based on the Data-Centric approach, Minimum-cost MPI transfer strategy and the code refactoring technique are realized for a better balance between data transfer and floating-point computation performance, which could significantly improve the scalability and reduce the time-to-solution. Subsequently, those approaches are integrated into the industrial unstructured CFD software, FlowStar, to evaluate their effectiveness. Numerical results demonstrate that Minimum-cost MPI strategy achieves more than 2.0 times performance improvement compared to the traditional Model-Centric implementation, and the code refactoring technique boosts performance by 40% to 50% over the minimum-cost MPI version. Moreover, the Data-Centric implementation on 64 A100 GPUs platform show a speedup ratio of over 120 when compared to the original MPI implementation with 64 ranks. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Scalability

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A load balancing-supported constant degree DHT ID assignment method

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Tien Tzu Hsueh Pao/Acta Electronica Sinica 2010年第11期38卷 2649-2654页

作者： Wang, Xiao-Hai Peng, Yu-Xing Li, Dong-Sheng Key Laboratory of Science and Technology for Parallel and Distributed Processing National University of Defense Technology Changsha Hunan 410073 China

A Load Balancing-Supported ID assignment method is the foundation to implement and maintain DHT overlays, realized constant degree DHTs usually use simple pure centralized or distributed ID management strategies, which cannot resolve the contradiction between cost of maintaining topologies' information and topologies' balance. Analyzing the universal tree structures in the topologies, an ID Assignment method RFIDAM based on the internal structure Routing Forest is proposed, which regularly aggregates local balancing information to guide new nodes' joining for overall balance. The experimental results show, with low maintenance and routing message overhead, the system's loading balance is efficiently ensured with the length of IDs differ by at most 2.

关键词： Topology

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A clustering-based approach for mining dockerfile evolutionary trajectories

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science China(Information sciences) 2019年第1期62卷 211-213页

作者： Yang ZHANG Huaimin WANG Vladimir FILKOV Key Laboratory of Parallel and Distributed Computing National University of Defense Technology College of Computer National University of Defense Technology DECAL Lab University of California Computer Science Department University of California

Dear editor,Docker1), as a de-facto industry standard [1], enables the packaging of an application with all its dependencies and execution environment in a light-weight, self-contained unit, i.e., *** launching the container from Docker image, developers can easily share the same operating system, libraries, and binaries [2]. As the configuration file, the dockerfile plays an important role,

关键词： A clustering-based approach for mining dockerfile evolutionary trajectories

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