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Grid and Cooperative computing - GCC 2004 Workshops 1

引用

丛书名： Lecture Notes in Computer Science

1000年

作者： Hai Jin Yi Pan Nong Xiao Jianhua Sun

ISBN: (数字)9783540302070

ISBN: (纸本)9783540235781

Welcome to the proceedings of GCC2004 and the city of Wuhan. Grid computing has become a mainstream research area in computer science and the GCC conference has become one of the premier forums for presentation of new and exciting research in all aspectsofgridandcooperativecomputing. Theprogramcommitteeispleasedtopresent the proceedings of the 3rd International Conference on Grid and Cooperative Comp- ing (GCC2004), which comprises a collection of excellent technical papers, posters, workshops, and keynote speeches. The papers accepted cover a wide range of exciting topics, including resource grid and service grid, information grid and knowledge grid, grid monitoring,managementand organizationtools, grid portal, grid service, Web s- vices and their QoS, service orchestration, grid middleware and toolkits, software glue technologies, grid security, innovative grid applications, advanced resource reservation andscheduling,performanceevaluationandmodeling,computer-supportedcooperative work, P2P computing, automatic computing, and meta-information management. The conference continues to grow and this year a record total of 581 manuscripts (including workshop submissions) were submitted for consideration. Expecting this growth, the size of the program committee was increased from 50 members for GCC 2003 for 70 in GCC 2004. Relevant differences from previous editions of the conf- ence: it is worth mentioning a signi?cant increase in the number of papers submitted by authors from outside China; and the acceptance rate was much lower than for p- vious GCC conferences. From the 427 papers submitted to the main conference, the program committee selected only 96 regular papers for oral presentation and 62 short papers for poster presentation in the program.

关键词： Theory of Computation Computer Communication Networks Operating systems Information systems Applications (incl. Internet) Information Storage and Retrieval User Interfaces and Human Computer Interaction

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Optimization of Sparse Matrix-Vector Multiplication with Variant CSR on GPUs

Optimization of Sparse Matrix-Vector Multiplication with Var...

引用

International Conference on Parallel and Distributed systems (ICPADS)

作者： Xiaowen Feng Hai Jin Ran Zheng Kan Hu Jingxiang Zeng Zhiyuan Shao Services Computing Technology and System Laboratory Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

Sparse Matrix-Vector multiplication (SpMV) is one of the most significant yet challenging issues in computational science area. It is a memory-bound application whose performance mostly depends on the input matrix and the underlying architecture. Many researchers have paid more attentions on exploring a variety of optimization techniques to SpMV. One of the most promising respects is how to adapt the storage format to satisfy the underlying architecture. Alterative storage formats can largely lessen memory pressure, however, the computational resources are often underutilized. Therefore, a new storage format, which is called Compressed Sparse Row with Segmented Interleave Combination (SIC), is proposed. Stemming from Compressed Sparse Row format (CSR), SIC format employs an interleave combination pattern that combines certain amount of CSR rows to form a new SIC row. In order to further improve performance, segmented processing is also brought in. According to the empirical data, we also develop an automatic SIC-based SpMV suitable for all the matrices. Experimental results show that our approach outperforms the NVIDIA CSR vector kernel, achieving up to 12.6 × speedup. It also demonstrates a comparable performance with the Hybrid format, even with the highest 2.89 × speedup.

关键词： Graphics processing unit Kernel Sparse matrices Silicon carbide Vectors Instruction sets Computer architecture

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DarkSAM: Fooling Segment Anything Model to Segment Nothing 38

DarkSAM: Fooling Segment Anything Model to Segment Nothing

引用

38th Conference on Neural Information Processing systems, NeurIPS 2024

作者： Zhou, Ziqi Song, Yufei Li, Minghui Hu, Shengshan Wang, Xianlong Zhang, Leo Yu Yao, Dezhong Jin, Hai National Engineering Research Center for Big Data Technology and System China Services Computing Technology and System Lab China Cluster and Grid Computing Lab China Hubei Engineering Research Center on Big Data Security China Hubei Key Laboratory of Distributed System Security China School of Computer Science and Technology Huazhong University of Science and Technology China School of Cyber Science and Engineering Huazhong University of Science and Technology China School of Software Engineering Huazhong University of Science and Technology China School of Information and Communication Technology Griffith University Australia

Segment Anything Model (SAM) has recently gained much attention for its outstanding generalization to unseen data and tasks. Despite its promising prospect, the vulnerabilities of SAM, especially to universal adversarial perturbation (UAP) have not been thoroughly investigated yet. In this paper, we propose DarkSAM, the first prompt-free universal attack framework against SAM, including a semantic decoupling-based spatial attack and a texture distortion-based frequency attack. We first divide the output of SAM into foreground and background. Then, we design a shadow target strategy to obtain the semantic blueprint of the image as the attack target. DarkSAM is dedicated to fooling SAM by extracting and destroying crucial object features from images in both spatial and frequency domains. In the spatial domain, we disrupt the semantics of both the foreground and background in the image to confuse SAM. In the frequency domain, we further enhance the attack effectiveness by distorting the high-frequency components (i.e., texture information) of the image. Consequently, with a single UAP, DarkSAM renders SAM incapable of segmenting objects across diverse images with varying prompts. Experimental results on four datasets for SAM and its two variant models demonstrate the powerful attack capability and transferability of DarkSAM. Our codes are available at: https://***/CGCL-codes/DarkSAM. © 2024 Neural information processing systems foundation. All rights reserved.

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Dynamic Acceleration of Parallel Applications in Cloud Platforms by Adaptive Time-Slice Control

Dynamic Acceleration of Parallel Applications in Cloud Platf...

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International Symposium on Parallel and Distributed Processing (IPDPS)

作者： Song Wu Zhenjiang Xie Haibao Chen Sheng Di Xinyu Zhao Hai Jin Services Computing Technology and System Lab Huazhong University of Science and Technology Wuhan China Argonne National Laboratory USA

ISBN: (纸本)9781509021413

Tightly-coupled parallel applications in cloud systems may suffer from significant performance degradation because of the resource over-commitment issue. In this paper, we propose a dynamic approach based on the adaptive control over time-slice for virtual clusters, in order to mitigate the performance degradation for parallel applications in cloud and avoid the negative impact effectively on other non-parallel applications meanwhile. The key idea is to reduce the synchronization overhead inside and across virtual machines (VMs) in cloud systems, by dynamically adjusting the time-slices of VMs in terms of the spinlock latency at runtime. Such a design is motivated by our experimental finding that VM's time slice is a key factor determining the synchronization overhead as well as the parallel execution performance. We perform the evaluation on a real cluster environment deployed with XEN, using five well-known benchmarks with 10+ applications. Experiments show that our approach obtains 1.5-10× performance gain for running parallel applications, than other state-of-the-art solutions (including Credit Scheduling of Xen and the well-known methods like Co-Scheduling and Balance Scheduling), with nearly unaffected impact on the performance of non-parallel applications.

关键词： Synchronization Cloud computing Degradation Benchmark testing Dynamic scheduling Virtual machining Runtime

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Pulmonary Disease Census Aiding system Based on Medical Image Grid

Pulmonary Disease Census Aiding System Based on Medical Imag...

引用

Asian Conference on Intelligent Information and Database systems, ACIIDS

作者： Hai Jin Aobing Sun Qin Zhang Ran Zheng Ruhan He Services Computing Technology and System Laboratory Cluster and Grid Computing Laboratorie school of Computer Science and Technology Huazhong University of Science and Technology HUST Wuhan China

The large population exerts high burdens to Chinese health census works. In this paper, we propose our PDCAS (pulmonary disease census aiding system) based on medical image grid, which aims to utilize the superiorities of grid technology to improve the efficiency of high-incidence and occupational pulmonary disease census. PDCAS integrates the individual medical information distributed in different hospitalspsila information systems into Medical Information Centre of one area. The census records are classified through one risk rate based cross clustering model to direct the medical diagnosis and review. The main processing algorithms of PDCAS are subdivided and encapsulated as detachable Web services with adapted granularity to support the grid workflow composition corresponding to different pulmonary diseases or aiding aims. The prototype of PDCAS proves the possible improvement of grid technology to diseases census and other data intensive medical applications.

关键词： Diseases Biomedical imaging Medical diagnostic imaging Information systems Medical diagnosis Clustering algorithms Web services Prototypes Medical services Biomedical equipment

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Grid and Cooperative computing - GCC 2004 1

引用

丛书名： Lecture Notes in Computer Science

1000年

作者： Hai Jin Yi Pan Nong Xiao Jianhua Sun

ISBN: (数字)9783540302087

ISBN: (纸本)9783540235644

关键词： Theory of Computation Computer Communication Networks Operating systems Software Engineering Information systems Applications (incl. Internet) Information Storage and Retrieval

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X-Stream: A Flexible, Adaptive Video Transformer for Privacy-Preserving Video Stream Analytics

X-Stream: A Flexible, Adaptive Video Transformer for Privacy...

引用

IEEE Annual Joint Conference: INFOCOM, IEEE Computer and Communications Societies

作者： Dou Feng Lin Wang Shutong Chen Lingching Tung Fangming Liu 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 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 Paderborn University Germany 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 Guangxi University 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 Peng Cheng Laboratory China

ISBN: (数字)9798350383508

ISBN: (纸本)9798350383515

Video stream analytics (VSA) systems fuel many exciting applications that facilitate people’s lives, but also raise critical concerns about exposing too much individuals’ privacy. To alleviate these concerns, various frameworks have been presented to enhance the privacy of VSA systems. Yet, existing solutions suffer two limitations: (1) being scenario-customized, thus limiting the generality of adapting to multifarious scenarios, (2) requiring complex, imperative programming, and tedious process, thus largely reducing the usability of such systems. In this paper, we present X-Stream, a privacy-preserving video transformer that achieves flexibility and efficiency for a large variety of VSA tasks. X-Stream features three major novel designs: (1) a declarative query interface that provides a simple yet expressive interface for users to describe both their privacy protection and content exposure requirements, (2) an adaptation mechanism that dynamically selects the most suitable privacy-preserving techniques and their parameters based on the current video context, and (3) an efficient execution engine that incorporates optimizations for multi-task deduplication and inter-frame inference. We implement X-Stream and evaluate it with representative VSA tasks and public video datasets. The results show that X-Stream achieves significantly improved privacy protection quality and performance over the state-of-the-art, while being simple to use.

关键词： Privacy Transforms Streaming media Transformers Multitasking Real-time systems Task analysis

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Towards Pay-As-You-Consume Cloud computing

Towards Pay-As-You-Consume Cloud Computing

引用

IEEE International Conference on services computing (SCC)

作者： Shadi Ibrahim Bingsheng He Hai Jin Cluster and Grid Computing Laboratory Services Computing Technology and System Laboratory Huazhong University of Science and Technology Wuhan China School of Computer Engineering Nanyang Technological University Singapore

Cloud computing enables users to perform their computation tasks in the public virtualized cloud using a pay-as-you-go style. Current pay-as-you-go pricing schemes typically charge on the incurred virtual machine hours. Our case studies demonstrate significant variations in the user costs, indicating significant unfairness among different users from the micro-economic perspective. Further studies reveal the reason for such variations is interference among concurrent virtual machines. The amount of interference cost depends on various factors, including workload characteristics, the number of concurrent VMs, and scheduling in the cloud. In this paper, we adopt the concept of pricing fairness from micro economics, and quantitatively analyze the impact of interference on the pricing fairness. To solve the unfairness caused by interference, we propose a pay-as-you-consume pricing scheme, which charges users according to their effective resource consumption excluding interference. The key idea behind the pay-as-you-consume pricing scheme is a machine learning based prediction model of the relative cost of interference. Our preliminary results with Xen demonstrate the accuracy of the prediction model, and the fairness of the pay-as-you-consume pricing scheme.

关键词： Interference Pricing Virtual machining Throughput Hardware Benchmark testing Predictive models

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PKTown: A Peer-to-Peer Middleware to Support Multiplayer Online Games

PKTown: A Peer-to-Peer Middleware to Support Multiplayer Onl...

引用

International Conference on Multimedia and Ubiquitous Engineering (MUE)

作者： Hai Jin Hong Yao Xiaofei Liao Sirui Yang Wei Liu Yong Jia Services Computing Technology and System Laboratory Cluster and Grid Computing Laboratory Huazhong University of Science and Technology Wuhan China School of Computer Science and Technology China University of Geoscience Wuhan China

Peer-to-peer (P2P) system can support service for lots of end users with little hardware investment, which suits for the efforts to lower down the service cost for multiplayer online games (MOG). In this paper, we introduce PKTown, a P2P middleware inserted into Star Craft and the network layer. PKTown captures all packets generated by Star Craft. We apply application layer multicast (ALM) to transmit the broadcast packets through overlay network. PKTown extends the LAN game experiences to players belong to different LAN. We design a k-regular random overlay network based on game specific requirements analysis. No change is made on binary code of Star Craft. Preliminary test results show that PKTown works well and supports other MOG in the same way. Our contribution is to provide a new game experience method with little hardware investment.

关键词： Peer to peer computing Middleware Local area networks Hardware Investments Web server Costs Broadcasting Binary codes Testing

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Desktop Virtualization: Techniques and Applications

Desktop Virtualization: Techniques and Applications

引用

International Conference on Pervasive computing and Applications (ICPCA)

作者： Hai Jin Services Computing Technology and System Laboratory School of Computer Science and Technology Huazhong University of Science슠and슠Technology Wuhan China

In this talk, the author discusses some recent advances in desktop virtualization field. Especially, the author talks about desktop virtualization research work in the National 973 Basic Research Program, The Research on Fundamental Theory and Approach of computing system Virtualization. These works include multi-platform supported virtual desktop (MSVD) and HVM supported virtual laptop environment. The design objectives and considerations are discussed in this talk, as well as the system design, performance evaluation compared with other techniques, and some system demonstrations.

关键词： Application virtualization Pervasive computing Grid computing Computers system software Application software Platform virtualization Resource virtualization Costs Investments

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