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检索条件"机构=The Distributed and Parallel Software Laboratory"
93 条 记 录,以下是21-30 订阅
排序:
TeeSwap: Private Data Exchange using Smart Contract and Trusted Execution Environment  23
TeeSwap: Private Data Exchange using Smart Contract and Trus...
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23rd IEEE International Conference on High Performance Computing and Communications, 7th IEEE International Conference on Data Science and Systems, 19th IEEE International Conference on Smart City and 7th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021
作者: Chen, Peng Shi, Peichang Xu, Jie Fu, Xiang Li, Linhui Zhong, Tao Xiang, Liangliang Kong, Jinzhu College of Computer National University of Defense Technology National Key Laboratory of Parallel and Distributed Processing Changsha410073 China Zhejiang Lab Hangzhou311100 China Kylin Software Co. Ltd Changsha410073 China
With importance of data value is approved, data-sharing will create more and greater value has become consensus. However, data exchange has to use a trusted third party(TTP) as an intermediary in an untrusted network ... 详细信息
来源: 评论
GNNRL-Smoothing: A Prior-Free Reinforcement Learning Model for Mesh Smoothing
arXiv
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arXiv 2024年
作者: Wang, Zhichao C. Chen, Xinhai C. Gong, Chunye Y. Yang, Bo Deng, Liang Sun, Yufei F. Pang, Yufei F. Liu, Jie National University of Defense Technology Science and Technology on Parallel and Distributed Processing Laboratory China National University of Defense Technology Laboratory of Digitizing Software for Frontier Equipment China China Aerodynamics Research and Development Center China Nankai University College of Software China
Mesh smoothing methods can enhance mesh quality by eliminating distorted elements, leading to improved convergence in simulations. To balance the efficiency and robustness of traditional mesh smoothing process, previo... 详细信息
来源: 评论
ST-PINN: A Self-Training Physics-Informed Neural Network for Partial Differential Equations
ST-PINN: A Self-Training Physics-Informed Neural Network for...
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International Joint Conference on Neural Networks (IJCNN)
作者: Junjun Yan Xinhai Chen Zhichao Wang Enqiang Zhoui Jie Liu Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha China Laboratory of Digitizing Software for Frontier Equipment National University of Defense Technology Changsha China
Partial differential equations (PDEs) are an essential computational kernel in physics and engineering. With the advance of deep learning, physics-informed neural networks (PINNs), as a mesh-free method, have shown gr...
来源: 评论
Fast and scalable in-network lock management using lock fission  24
Fast and scalable in-network lock management using lock fiss...
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Proceedings of the 18th USENIX Conference on Operating Systems Design and Implementation
作者: Hanze Zhang Ke Cheng Rong Chen Haibo Chen Institute of Parallel and Distributed Systems SEIEE Shanghai Jiao Tong University and Shanghai AI Laboratory and MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University Institute of Parallel and Distributed Systems SEIEE Shanghai Jiao Tong University and Engineering Research Center for Domain-specific Operating Systems Ministry of Education China Institute of Parallel and Distributed Systems SEIEE Shanghai Jiao Tong University and Shanghai AI Laboratory and Engineering Research Center for Domain-specific Operating Systems Ministry of Education China Institute of Parallel and Distributed Systems SEIEE Shanghai Jiao Tong University and Engineering Research Center for Domain-specific Operating Systems Ministry of Education China and Key Laboratory of System Software (Chinese Academy of Sciences)
distributed lock services are extensively utilized in distributed systems to serialize concurrent accesses to shared resources. The need for fast and scalable lock services has become more pronounced with decreasing t...
来源: 评论
Sparse Matrix Reordering Method Selection with parallel Computing and Deep Learning
Sparse Matrix Reordering Method Selection with Parallel Comp...
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International Joint Conference on Neural Networks (IJCNN)
作者: Rui Xia Jihu Guo Huajian Zhang Shun Yang Qinglin Wang Jie Liu College of Computer Science and Techonology National University of Defense Technology Changsha China Laboratory of Digitizing Software for Frontier Equipment National University of Defense Technology Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology
Sparse matrix reordering is an important step in Cholesky decomposition. By reordering the rows and columns of the matrix, the time of computation and storage cost can be greatly reduced. With the proposal of various ... 详细信息
来源: 评论
Feature and Performance Comparison of FaaS Platforms  14
Feature and Performance Comparison of FaaS Platforms
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14th IEEE International Conference on software Engineering and Service Science, ICSESS 2023
作者: Ma, Penghui Shi, Peichang Yi, Guodong College of Computer Science National University of Defense Technology National Key Laboratory of Parallel and Distributed Processing Changsha410073 China College of Computer Science National University of Defense Technology Key Laboratory of Software Engineering for Complex Systems Changsha410073 China Xiangjiang Lab Changsha410073 China School of Advanced Interdisciplinary Studies Hunan University of Technology and Business Changsha410073 China
With serverless computing offering more efficient and cost-effective application deployment, the diversity of serverless platforms presents challenges to users, including platform lock-in and costly migration. Moreove... 详细信息
来源: 评论
AUXILIARY-TASKS LEARNING FOR PHYSICS-INFORMED NEURAL NETWORK-BASED PARTIAL DIFFERENTIAL EQUATIONS SOLVING
arXiv
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arXiv 2023年
作者: Yan, Junjun Chen, Xinhai Wang, Zhichao Zhou, Enqiang 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
Physics-informed neural networks (PINNs) have emerged as promising surrogate modes for solving partial differential equations (PDEs). Their effectiveness lies in the ability to capture solution-related features throug... 详细信息
来源: 评论
Bi-Objective Scheduling Algorithm for Hybrid Workflow in JointCloud
Bi-Objective Scheduling Algorithm for Hybrid Workflow in Joi...
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IEEE International Conference on Joint Cloud Computing (JCC)
作者: Rui Li Huaimin Wang Peichang Shi National Key Laboratory of Parallel and Distributed Processing College of Computer Science National University of Defense Technology Changsha China State Key Laboratory of Complex & Critica Software Environment College of Computer Science National University of Defense Technology Changsha China
Big data workflows are widely used in IoT, recommended systems, and real-time vision applications, and they continue to grow in complexity. These hybrid workflows consist of both resource-intensive batch jobs and late... 详细信息
来源: 评论
ST-PINN: A Self-Training Physics-Informed Neural Network for Partial Differential Equations
arXiv
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arXiv 2023年
作者: Yan, Junjun Chen, Xinhai Wang, Zhichao Zhoui, Enqiang 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
Partial differential equations (PDEs) are an essential computational kernel in physics and engineering. With the advance of deep learning, physics-informed neural networks (PINNs), as a mesh-free method, have shown gr... 详细信息
来源: 评论
Proposing an intelligent mesh smoothing method with graph neural networks
arXiv
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arXiv 2023年
作者: Wang, Zhichao Chen, Xinhai Yan, Junjun 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 National University of Defense Technology Changsha410073 China
In CFD, mesh smoothing methods are commonly utilized to refine the mesh quality to achieve high-precision numerical simulations. Specifically, optimization-based smoothing is used for high-quality mesh smoothing, but ... 详细信息
来源: 评论