检索结果-内蒙古大学图书馆

30th ACM Symposium on Operating Systems Principles, SOSP 2024

作者： Luo, Xuchuan Shen, Jiacheng Zuo, Pengfei Wang, Xin Lyu, Michael R. Zhou, Yangfan National Key Laboratory of Parallel and Distributed Computing Changsha China School of Computer Science Fudan University Shanghai China Duke Kunshan University Kunshan China Huawei Cloud Shenzhen China Shanghai Key Laboratory of Intelligent Information Processing Shanghai China The Chinese University of Hong Kong Hong Kong Hong Kong

ISBN: (纸本)9798400712517

Disaggregated memory (DM) is a widely discussed datacenter architecture in academia and industry. It decouples computing and memory resources from monolithic servers into two network-connected resource pools. Range indexes are widely adopted by storage systems on DM to efficiently locate and query remote data. However, existing range indexes on DM suffer from either high computing-side cache consumption or high memory-side read amplifications. In this paper, we propose CHIME, a hybrid index combining B+ trees with hopscotch hashing, to achieve low cache consumption and low read amplifications simultaneously. There are three challenges in constructing CHIME on DM, i.e., the complicated optimistic synchronization, the extra metadata access, and the read amplifications introduced by hopscotch hashing. CHIME leverages 1) a three-level optimistic synchronization scheme to synchronize read and write operations with various granularities, 2) an access-aggregated metadata management technique to eliminate extra metadata accesses by piggybacking and replicating metadata, and 3) an effective hotness-aware speculative read mechanism to mitigate the read amplifications of hopscotch hashing. Experimental results show that CHIME outperforms the state-of-the-art range indexes on DM by up to 5.1× with the same cache size and achieves similar performance with up to 8.7× lower cache consumption. © 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.

关键词： Memory architecture

来源：评论

学校读者我要写书评

暂无评论

Using redundant threads for fault tolerance of OpenMP programs

Using redundant threads for fault tolerance of OpenMP progra...

引用

2010 International Conference in Information Science and Applications, ICISA 2010

作者： Fu, Hongyi Ding, Yan Key Laboratory of Science and Technology for National Defence of Parallel and Distributed Processing National University of Defence Tech. Changsha Hunan 410073 China School of Computer National University of Defence Tech. Changsha Hunan 410073 China

ISBN: (纸本)9781424459438

As the wide application of multi-core processor architecture in the domain of high performance computing, fault tolerance for shared memory parallel programs becomes a hot spot of research. For years, checkpointing has been the dominant fault tolerance technology in this field, and recently, many research works have been engaged with it. However, to those programs which deal with large amount of data, checkpointing may induce massive I/O transfer, which will adversely affect scalability. To deal with such a problem, this paper proposes a fault tolerance approach, making use of redundancy, for shared memory parallel programs. Our scheme avoids saving and restoring computational state during the program's execution, hence does not involve I/O operations, so presents explicit advantage over checkpointing in scalability. In this paper, we introduce our approach and the related compiler tool in detail, and give the experimental evaluation result. ©2010 IEEE.

关键词： Fault tolerance

来源：评论

学校读者我要写书评

暂无评论

A Multi-Dimensional Assessment Model and Its Application in E-learning Courses of Computer Science 20

A Multi-Dimensional Assessment Model and Its Application in ...

引用

21st Annual Conference of the Special Interest Group in Information Technology Education, SIGITE 2020

作者： Luo, Jiwen Lu, Feng Wang, Tao Key Lab. of Parallel and Distributed Computing College of Computer National University of Defense Technology Changsha China 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

ISBN: (纸本)9781450370455

Computer science is a practical discipline. It is always a great challenge to evaluate students' computer practice using computer-aided means for large scale students. We always need to address problems such as suspected plagiarism and deviation of the overall difficulty factor. In this paper, a multi-dimensional assessment model is designed for CS courses based on the detailed practice processing data in an E-learning system. The model comprehensively evaluates the students' learning process and results in three aspects of correctness, originality, and quality detection. Besides, the teacher can easily participate in the assessment according to their needs. The correctness is an essential requirement, and the originality is based on the clustering results of students' behaviors after clone detection to curb homework plagiarism. SonarQube is used to detect code quality and put forward higher requirements for codes. Manual participation intelligence has improved the flexibility and applicability of the model to a certain extent. We applied this model on the EduCoder online education platform and carried out a comprehensive analysis of 485 students in the parallel Programming Principles and Practice Class of Huazhong University of Science and Technology. Experiment results confirm the distinction, rationality, and fairness of the model in assessing student performance. It not only gives students a credible, comprehensive score in large-scale online practical programming courses but also gives teachers and students corresponding suggestions based on the evaluation results. Furthermore, the model can be extended to other online education platforms. © 2020 ACM.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Detecting faults by tracing companion states in cloud computing systems

引用

Jisuanji Xuebao/Chinese Journal of Computers 2012年第5期35卷 856-870页

作者： Rao, Xiang Wang, Huai-Min Chen, Zhen-Bang Zhou, Yang-Fan Cai, Hua Zhou, Qi Sun, Ting-Tao National Key Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha 410073 China Shenzhen Research Institute The Chinese University of Hong Kong Shenzhen China Department of Computing Platform Alibaba Cloud Computing Company Hangzhou 310011 China

A common way to construct a fault model is injecting the fault into the system and observing the subsequent symptoms, e. g. event logs. However, fault features would vary during the propagation period, and present different symptoms at different stage of the fault propagation process. The exiting detection window based feature extraction methods can only identify the early symptoms of a fault, but fail to detect the latter symptoms and cause false alarms. To solve the problem, we present a fault feature extraction method, called Companion State Tracer (CSTracer), which consists of 3 integrated steps: (1) pre-process logs to remove the unrelated logs;(2) construct a general identifier for the early symptoms of a fault;(3) construct a finite state machine model for the fault to trace the latter symptoms. CSTracer can persistently monitor a fault after the fault has been identified. We have justified the effectiveness of CSTracer in an enterprise cloud system. Compared with the existing, the results show that CSTracer has a better detection accuracy.

关键词： Fault detection

来源：评论

学校读者我要写书评

暂无评论

CoCache: Multi-layer Multi-path Cooperative Cache Accelerating the Deployment of Large Scale Virtual Machines

CoCache: Multi-layer Multi-path Cooperative Cache Accelerati...

引用

2014 IEEE 8th International Symposium on Service Oriented System Engineering

作者： Ziyang Li Zhaoning Zhang Huiba Li Yuxing Peng National Key Laboratory for Parallel and Distributed Processing National University of Defense Technology China

By analyzing the problems and challenges of virtual machine image store system in cloud computing environment, we present a cooperative persistent cache (CoCache) for virtual disks. CoCache takes advantage of the service ability of the cached nodes by providing virtual image data service for other nodes. CoCache can transfer data between nodes in a P2P pattern, for extending data service ability of the system. CoCache is realized in the kernel space of Linux, can support any kind of VMM. Experiments show that CoCache can effectively reduce the cost during virtual machines read data, and promote the service ability of virtual machine storage system. Layer-aware cache policy is proposed specially for improving cache hit rate in the multi-layer and multipath environment.

关键词： Virtual machining Servers Image storage Cloud computing Computer architecture System performance Cache storage

来源：评论

学校读者我要写书评

暂无评论

Large-scale network topology generation for emulation environment

Large-scale network topology generation for emulation enviro...

引用

1st International Conference on Networking and distributed computing, ICNDC 2010

作者： Kuang, Xiao-Hui Huang, Min-Huan Che, Yong-Gang Jin, Li Fei, Xu National Key Laboratory of Science and Technology on Information System Security Beijing Institute of System and Engineering Beijing China Department of Computer Science and Technology Tsinghua University Beijing China National Laboratory for Parallel and Distributed Process National University of Defense Technology Changsha China

ISBN: (纸本)9780769542072

Network emulation environment is great importance to the research of network protocols, applications and security mechanism. Large-scale network topology generation is one of key technologies to construct network emulation environment. In this paper, a new large-scale network topology generation framework called LSNTGF is proposed, which divides the network topology into three hierarchies: AS, router and terminal node. It contains the assignment mechanism to bandwidth of each link and IP address of each node. The framework is evaluate by implementation, and the result illustrate it is efficient to network emulation environment for network protocols and security research. © 2010 IEEE.

关键词： Network topology

来源：评论

学校读者我要写书评

暂无评论

XGrad: Boosting Gradient-Based Optimizers With Weight Prediction

arXiv

引用

arXiv 2023年

作者： Guan, Lei Li, Dongsheng Shi, Yanqi Meng, Jian The Department of Mathematics National University of Defense Technology Changsha China The National Key Laboratory of Parallel and Distributed Computing National University of Defense Technology China

In this paper, we propose a general deep learning training framework XGrad which introduces weight prediction into the popular gradient-based optimizers to boost their convergence and generalization when training the deep neural network (DNN) models. In particular, ahead of each mini-batch training, the future weights are predicted according to the update rule of the used optimizer and are then applied to both the forward pass and backward propagation. In this way, during the whole training period, the optimizer always utilizes the gradients w.r.t. the future weights to update the DNN parameters, making the gradient-based optimizer achieve better convergence and generalization compared to the original optimizer without weight prediction. XGrad is rather straightforward to implement yet pretty effective in boosting the convergence of gradient-based optimizers and the accuracy of DNN models. Empirical results concerning five popular optimizers including SGD with momentum, Adam, AdamW, AdaBelief, and AdaM3 demonstrate the effectiveness of our proposal. The experimental results validate that XGrad can attain higher model accuracy than the baseline optimizers when training the DNN models. The code of XGrad will be available at: https://***/guanleics/XGrad. Copyright © 2023, The Authors. All rights reserved.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

TeeSwap: Private Data Exchange using Smart Contract and Trusted Execution Environment 23

TeeSwap: Private Data Exchange using Smart Contract and Trus...

引用

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

ISBN: (纸本)9781665494571

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 environment, which may lead to leakage of data privacy. In this paper, we design a system named TeeSwap, which uses smart contract to complete data exchange, and at the same time uses cryptographic algorithms and trusted execution environment (TEE) to ensure privacy in process of data transmission, verification and contract execution. Meanwhile, TeeSwap can ensure the credibility, fairness, integrity and privacy while data are shared in our system. In the end, we implement contracts about data market and data exchange. When confirming the data transaction, data market contract can automatically generate and deploy exchange contract, which can complete the data exchange authoritatively. © 2021 IEEE.

关键词： Data privacy Smart contracts Data communication Cryptography

来源：评论

学校读者我要写书评

暂无评论

Meta-Tsallis-Entropy Minimization: A New Self-Training Approach for Domain Adaptation on Text Classification

arXiv

引用

arXiv 2023年

作者： Lu, Menglong Huang, Zhen Tian, Zhiliang Zhao, Yunxiang Fei, Xuanyu Li, Dongsheng National Key Laboratory of Parallel and Distributed Computing National University of Defense Technology China Beijing Institute of Biotechnology China Suiren Information China

Text classification is a fundamental task for natural language processing, and adapting text classification models across domains has broad applications. Self-training generates pseudo-examples from the model’s predictions and iteratively train on the pseudo-examples, i.e., mininizes the loss on the source domain and the Gibbs entropy on the target domain. However, Gibbs entropy is sensitive to prediction errors, and thus, self-training tends to fail when the domain shift is large. In this paper, we propose Meta-Tsallis Entropy minimization (MTEM), which applies meta-learning algorithm to optimize the instance adaptive Tsallis entropy on the target domain. To reduce the computation cost of MTEM, we propose an approximation technique to approximate the Second-order derivation involved in the meta-learning. To efficiently generate pseudo labels, we propose an annealing sampling mechanism for exploring the model’s prediction probability. Theoretically, we prove the convergence of the meta-learning algorithm in MTEM and analyze the effectiveness of MTEM in achieving domain adaptation. Experimentally, MTEM improves the adaptation performance of BERT with an average of 4 percent on the benchmark dataset. © 2023, CC BY-NC-SA.

关键词： Learning algorithms

来源：评论

学校读者我要写书评

暂无评论

Cooperative Air-Ground Instant Delivery by UAVs and Crowdsourced Taxis 40

Cooperative Air-Ground Instant Delivery by UAVs and Crowdsou...

引用

40th IEEE International Conference on Data Engineering, ICDE 2024

作者： Gao, Junhui Wang, Qianru Zhang, Xin Shi, Juan Zhao, Xiang Han, Qingye Pan, Yan School of Computer Science Northwestern Polytechnical University China School of Computer Science and Technology Xidian University China Air Force Engineering University China National University of Defense Technology Laboratory for Big Data and Decision China School of Management Science and Real Estate Chongqing University China National University of Defense Technology National Key Laboratory of Information Systems Engineering China National University of Defense Technology National Key Laboratory of Parallel and Distributed Computing China

ISBN: (纸本)9798350317152

Instant delivery has become a fundamental service in people's daily lives. Different from the traditional express service, the instant delivery has a strict shipping time constraint after being ordered. However, the labor shortage makes it challenging to realize efficient instant delivery. To tackle the problem, researchers have studied to introduce vehicles (i.e., taxis) or Unmanned Aerial Vehicles (UAVs or drones) into instant delivery tasks. Unfortunately, the delivery detour of taxis and the limited battery of UAVs make it hard to meet the rapidly increasing instant delivery demands. Under this circumstance, this paper proposes an air-ground cooperative instant delivery paradigm to maximize the delivery performance and meanwhile minimize the negative effects on the taxi passengers. Specifically, a data-driven delivery potential-demands-aware cooperative strategy is designed to improve the overall delivery performance of both UAVs and taxis as well as the taxi passengers' experience. The experimental results show that the proposed method improves the delivery number by 30.1% and 114.5% compared to the taxi-based and UAV-based instant delivery respectively, and shortens the delivery time by 35.7% compared to the taxi-based instant delivery. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：