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检索条件"机构=Cluster and Grid Computing Lab"
555 条 记 录,以下是91-100 订阅
排序:
Duo: Improving Data Sharing of Stateful Serverless Applications by Efficiently Caching Multi-Read Data
Duo: Improving Data Sharing of Stateful Serverless Applicati...
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International Symposium on Parallel and Distributed Processing (IPDPS)
作者: Zhuo Huang Hao Fan Chaoyi Cheng Song Wu Hai Jin National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology China
A growing number of applications are moving to serverless architectures for high elasticity and fine-grained billing. For stateful applications, however, the use of serverless architectures is likely to lead to signif...
来源: 评论
Scalable Optimal Margin Distribution Machine
arXiv
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arXiv 2023年
作者: Wang, Yilin Cao, Nan Zhang, Teng Shi, Xuanhua Jin, Hai National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology China
Optimal margin Distribution Machine (ODM) is a newly proposed statistical learning framework rooting in the latest margin theory, which demonstrates better generalization performance than the traditional large margin ... 详细信息
来源: 评论
Enabling Efficient Large Recommendation Model Training with Near CXL Memory Processing
Enabling Efficient Large Recommendation Model Training with ...
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Annual International Symposium on Computer Architecture, ISCA
作者: Haifeng Liu Long Zheng Yu Huang Jingyi Zhou Chaoqiang Liu Runze Wang Xiaofei Liaot Hai Jinf Jingling Xue National Engineering Research Center for Big Data Technology and System/Services Computing Technology and System Lab/Cluster and Grid Computing Lab Huazhong University of Science and Technology China School of Computer Science and Engineering University of New South Wales Australia Zhejiang Lab Hangzhou China
Personalized recommendation systems have become one of the most important Internet services nowadays. A critical challenge of training and deploying the recommendation models is their high memory capacity and bandwidt... 详细信息
来源: 评论
MeG2: In-Memory Acceleration for Genome Graphs Analysis
MeG2: In-Memory Acceleration for Genome Graphs Analysis
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Design Automation Conference
作者: Yu Huang Long Zheng Haifeng Liu Zhuoran Zhou Dan Chen Pengcheng Yao Qinggang Wang Xiaofei Liao Hai Jin National Engineering Research Center for Big Data Technology and System/Services Computing Technology and System Lab/Cluster and Grid Computing Laboratory Huazhong University of Science and Technology Wuhan China Zhejiang Lab Hangzhou China
Genome graphs analysis has emerged as an effective means to enable mapping DNA fragments (known as reads) to the reference genome. It replaces the traditional linear reference with a graph-based representation to augm...
来源: 评论
Container lifecycle-aware scheduling for serverless computing
Container lifecycle-aware scheduling for serverless computin...
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作者: Wu, Song Tao, Zhiheng Fan, Hao Huang, Zhuo Zhang, Xinmin Jin, Hai Yu, Chen Cao, Chun National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China State Key Laboratory for Novel Software Technology Department of Computer Science and Technology Nanjing University Nanjing China
Elastic scaling in response to changes on demand is a main benefit of serverless computing. When bursty workloads arrive, a serverless platform launches many new containers and initializes function environments (known... 详细信息
来源: 评论
It Takes Two to Tango: Serverless Workflow Serving via Bilaterally Engaged Resource Adaptation
arXiv
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arXiv 2025年
作者: Wu, Jing Wang, Lin Deng, Quanfeng Yu, Chen Zhang, Dong Yan, Bingheng Liu, Fangming National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab Huazhong University of Science and Technology China Paderborn University Germany Inspur Data Co. Ltd. China Peng Cheng Laboratory China
Serverless platforms typically adopt an early-binding approach for function sizing, requiring developers to specify an immutable size for each function within a workflow beforehand. Accounting for potential runtime va... 详细信息
来源: 评论
Efficient FPGA-based graph processing with hybrid pull-push computational model
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Frontiers of Computer Science 2020年 第4期14卷 13-28页
作者: Chengbo YANG Long ZHENG Chuangyi GUI Hai JIN National Engineering Research Center for Big Data Technology and System/Service Computing Technology and System Lab/Cluster and Grid Computing Lab School of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan430074China
Hybrid pull-push computational model can provide compelling results over either of single one for processing real-world *** and pipeline parallelism of FPGAs make it potential to process different stages of graph ***,... 详细信息
来源: 评论
FIRE: combining multi-stage filtering with taint analysis for scalable recurring vulnerability detection  24
FIRE: combining multi-stage filtering with taint analysis fo...
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Proceedings of the 33rd USENIX Conference on Security Symposium
作者: Siyue Feng Yueming Wu Wenjie Xue Sikui Pan Deqing Zou Yang Liu Hai Jin National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security Cluster and Grid Computing Lab and School of Cyber Science and Engineering Huazhong University of Science and Technology China Nanyang Technological University Singapore National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security Cluster and Grid Computing Lab and School of Cyber Science and Engineering Huazhong University of Science and Technology China and Jinyinhu Laboratory China National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security Cluster and Grid Computing Lab and School of Computer Science and Technology Huazhong University of Science and Technology China
With the continuous development of software open-sourcing, the reuse of open-source software has led to a significant increase in the occurrence of recurring vulnerabilities. These vulnerabilities often arise through ...
来源: 评论
Fast Parallel Recovery for Transactional Stream Processing on Multicores
Fast Parallel Recovery for Transactional Stream Processing o...
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International Conference on Data Engineering
作者: Jianjun Zhao Haikun Liu Shuhao Zhang Zhuohui Duan Xiaofei Liao Hai Jin Yu Zhang National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China School of Computer Science and Engineering Nanyang Technological University Singapore
Transactional stream processing engines (TSPEs) have gained increasing attention due to their capability of processing real-time stream applications with transactional semantics. However, TSPEs remain susceptible to s... 详细信息
来源: 评论
FedMHO: Heterogeneous One-Shot Federated Learning Towards Resource-Constrained Edge Devices
arXiv
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arXiv 2025年
作者: Yao, Dezhong Shi, Yuexin Liu, Tongtong Xu, Zhiqiang National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China Mohamed bin Zayed University of Artificial Intelligence United Arab Emirates
Federated Learning (FL) is increasingly adopted in edge computing scenarios, where a large number of heterogeneous clients operate under constrained or sufficient resources. The iterative training process in conventio... 详细信息
来源: 评论