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XGCN:a library for large-scale graph neural network recommendations

Frontiers of Computer Science 2024年第3期18卷 247-249页

作者： Xiran SONG Hong HUANG Jianxun LIAN Hai JIN National Engineering Research Center for Big Data Technology and System Services Computing Technology and System LabCluster and Grid Computing LabSchool of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China Microsoft Research Asia Beijing 100080China

1 Introduction Graph Neural Networks(GNNs)have gained widespread adoption in recommendation systems,and nowadays there is a pressing need to effectively manage large-scale graph data[1].When it comes to large graphs,GNNs may encounter the scalability issue stemming from their multi-layer messagepassing ***,scaling GNNs has emerged as a crucial research area in recent years,with numerous scaling strategies being proposed.

关键词： scaling gained operations

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Svega: Answering natural language questions over knowledge base with semantic matching 30

Svega: Answering natural language questions over knowledge b...

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30th International Conference on Software Engineering and Knowledge Engineering, SEKE 2018

作者： Li, Gaofeng Yuan, Pingpeng Jin, Hai Services Computing Technology and System Lab Cluster and Grid Computing Lab Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)1891706446

Nowadays, more and more large scale knowledge bases are available for public access. Although these knowledge bases have their inherent access interfaces, such as SPARQL, they are generally unfriendly to end users. An intuitive way to bridge the gap between users and knowledge bases is to enable users to ask questions with natural language interface and return desired answers directly. Here the challenge is how to discover the query intention of users. Another challenge is how to obtain accurate answers from knowledge bases. In this paper, we model the query intention with a graph based on an entity-driven method. Consequently, the core problem of natural language question answering can be treated as subgraph matching over knowledge bases. For a query graph, there is a huge number of candidate mappings in a knowledge base, including ambiguities. Thus, a semantic vector is proposed to address disambiguation by evaluating the semantic similarity between edges in a query graph and paths in a knowledge base. By this way, our system can extract accurate answers directly without any offline work. Extensive experiments over the series of QALD challenges show the effectiveness of our system Svega in terms of recall and precision against other state-of-The-Art systems. © 2018 Universitat zu Koln. All rights reserved.

关键词： Semantics

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Container-Based Customization Approach for Mobile Environments on Clouds 13th

Container-Based Customization Approach for Mobile Environmen...

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13th International Conference on Green, Pervasive, and Cloud computing, GPC 2018

作者： Hu, Jiahuan Wu, Song Jin, Hai Chen, Hanhua Services Computing Technology and System Lab Cluster and Grid Computing Lab Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9783030150921

Recently, mobile cloud which utilizes the elastic resources of clouds to provide services for mobile applications, is becoming more and more popular. When building a mobile cloud platform (MCP), one of the most important things is to provide an execution environment for mobile applications, e.g., the Android mobile operating system (OS). Many efforts have been made to build Android environments on clouds, such as Android virtual machines (VMs) and Android containers. However, the need of customizable Android execution environments for MCP has been ignored for many years, since the existing OS customization solutions are only designed for hardware-specific platforms or driver-specific applications, and taking little account of frequently-changing scenarios on clouds. Moreover, they lack a unified method of customization, as well as an effective upgrade and maintenance mechanism. As a result, they are not suitable for varied and large-scale scenarios on clouds. Therefore, in this paper, we propose a unified and effective approach for customizing Android environments on clouds. The approach provides a container-based solution to custom-tailor Android OS components, as well as a way to run Android applications for different scenarios. Under the guidance of this approach, we develop an automatic customization toolkit named AndroidKit for generating specific Android OS components. Through this toolkit, we are able to boot new Android VM instances called AndroidXs. These AndroidXs are composed of OS images generated by AndroidKit, which can be easily customized and combined for varied demands on clouds. © 2019, Springer Nature Switzerland AG.

关键词： Android (operating system)

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Reference metadata extraction from scientific papers

Reference metadata extraction from scientific papers

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2011 12th International Conference on Parallel and Distributed computing, Applications and Technologies, PDCAT 2011

作者： Guo, Zhixin Jin, Hai Cluster and Grid Computing Lab Services Computing Technology and System Lab Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780769545646

Bibliographical information of scientific papers is of great value since the Science Citation Index is introduced to measure research impact. Most scientific documents available on the web are unstructured or semi-structured, and the automatic reference metadata extraction process becomes an important task. This paper describes a framework for automatic reference metadata extraction from scientific papers. Our system can extract title, author, journal, volume, year, and page from scientific papers in PDF. We utilize a document metadata knowledge base to guide the reference metadata extraction process. The experiment results show that our system achieves a high accuracy. © 2011 IEEE.

关键词： Metadata

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VAIL: A victim-aware cache policy for improving lifetime of hybrid memory 9

VAIL: A victim-aware cache policy for improving lifetime of ...

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9th International Workshop on Programming Models and Applications for Multicores and Manycores, PMAM 2018

作者： Jia, Youchuang Zhou, Fang Gao, Xiang Wu, Song Jin, Hai Liao, Xiaofei Yuan, Pingpeng Services Computing Technology and System Lab Cluster and Grid Computing Lab Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781450356459

Nowadays emerging Non-Volatile Memory (NVM) technologies are introduced to remedy the shortages of the current DRAM-based memory system. However, NVM has limited write endurance, which would severely restrict the performance of memory system. In order to relieve above limitation, we proposed a victim-aware cache policy (VAIL), based on DRAM and NVM hybrid memory system. VAIL took the eviction locality of victims from the DRAM cache into consideration, to reduce writebacks to NVM and improve DRAM hit ratio at the same time. Our evaluation shows that VAIL could reduce 17.2% writebacks to NVM with single-core workloads, 22% writebacks to NVM with multi-core workloads and improve the DRAM hit ratio of the hybrid memory system. © 2018 Association for computing Machinery.

关键词： Dynamic random access storage

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grid workflow scheduling based on reliability cost 2

Grid workflow scheduling based on reliability cost

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2nd International Conference on Scalable Information systems, InfoScale 2007

作者： Tao, Yongcai Jin, Hai Shi, Xuanhua Cluster and Grid Computing Lab Services Computing Technology and System Lab Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781595937575

grid workflow is a complex and typical grid application, but owing to the highly dynamic feature of grid environments, resource unavailability is increasingly becoming severe and poses great challenges to grid workflow scheduling. Though fault recovery mechanism adopted in grid system guarantee the completion of jobs to some extent, but wasting system resources. To overcome the shortcoming, this paper proposes a Markov Chain based grid node availability prediction model which can efficiently predict grid nodes' availability in the future without adding significant overhead. Based on this model, the paper presents a grid workflow scheduling based on reliability cost (RCGS). The performance evaluation results demonstrate that RCGS improves the dependability of workflow execution and success ratio of tasks with low reliability cost.

关键词： grid computing

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Dev store: Distributed storage system for desktop virtualization

Dev store: Distributed storage system for desktop virtualiza...

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8th International Conference on Computer Science and Education, ICCSE 2013

作者： Jiang, Yue Jin, Hai Liao, Xiaofei Services Computing Technology and System Lab Cluster and Grid Computing Lab Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9781467344623

With the development of desktop virtualization technology, more and more companies begins to deploy virtual desktop. Traditional NAS and SAN storages can only support small-scale users due to network bandwidth limit and poor scalability. Another disadvantage is that NAS and SAN storages are very expensive. The distributed file systems such as GFS, PVFS, and Lustre are with low cost, high scalability and mass storage, but they are only designed for specific scenarios and can not meet the need of desktop virtualization storage. The characteristics of virtual desktop I/O are small random I/O, high IOPS, snapshot needed and frequent access of the root image. Based on these I/O characteristics, DevStore is designed for desktop virtualization, and aims to be low cost, good scalability and performance. Experiments show that DevStore image's write performance is 70MB/s and read performance is 60MB/s in gigabit Ethernet. The snapshot time of DevStore is less than 1ms. DevStore is also easy to expand. Experiments also show that DevStore is better than QCOW in NFS environment and meets the desktop virtualization storage need. © 2013 IEEE.

关键词： Virtual machine

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VMckpt:lightweight and live virtual machine checkpointing

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Science china(Information Sciences) 2012年第12期55卷 2865-2880页

作者： LIU HaiKun 1,JIN Hai 1,LIAO XiaoFei 1,MA Bo 1 & XU ChengZhong 2 1 services computing technology and system lab,cluster and grid computing lab,School of Computer Science and technology,Huazhong University of Science and technology,Wuhan 430074,china 2 Department of Electrical and Computer Engineering,Wayne State University,Detroit,MI 48202,USA 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 Department of Electrical and Computer Engineering Wayne State University Detroit USA

Recent advance of virtualization technology provides a new approach to check-point/restart at the virtual machine(VM) *** contrast to traditional process-level checkpointing,checkpointing at the virtualization layer brings up several advantages,such as compatibility,transparence,flexibility and ***,because the virtualization layer has little semantic knowledge about the operation system and the applications running atop,VM-layer checkpointing requires saving the entire operating system state rather than a single *** overhead may render the approach *** reduce the size of VM checkpoint,in this paper we propose a page eviction scheme and an incremental checkpointing mechanism to avoid saving unnecessary VM pages in the *** keep the system online transparently,we propose a live checkpointing mechanism by saving the memory image in a copy-on-write(COW) *** implement the performance optimization mechanisms in a prototype system,called *** results with a group of representative applications show that our page eviction scheme and incremental checkpointing can significantly reduce the checkpoint file size by up to 87% and shorten the total checkpointing/restart time by a factor of up to 71%,in comparison with the Xens default checkpointing *** observed application downtimes due to checkpointing can be reduced to as small as 300 ms.

关键词： checkpoint/restart copy-on-write page eviction virtual machine

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MalScan: Android Malware Detection Based on Social-Network Centrality Analysis

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IEEE Transactions on Dependable and Secure computing 2025年

作者： Wu, Yueming Suo, Wenqi Feng, Siyue Zou, Deqing Yang, Wei Liu, Yang Jin, Hai Huazhong University of Science and Technology National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Wuhan430074 China Jinyinhu Laboratory Wuhan430074 China University of Texas at Dallas United States Nanyang Technological University Singapore Huazhong University of Science and Technology 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 Wuhan430074 China

Malware scanning of an app market is expected to be scalable and effective. However, existing approaches use syntax-based features that can be evaded by transformation attacks or semantic-based features which are usually extracted by expensive program analysis. Therefore, to address the scalability challenges of traditional heavyweight static analysis, we propose a graph-based lightweight approach MalScan for Android malware detection. MalScan considers the function call graph as a complex social network and employs centrality analysis on sensitive application program interfaces (APIs) to express the semantic characteristics of the graph. On this basis, machine learning algorithms and ensemble learning algorithms are applied to classify the extracted features. We evaluate MalScan on datasets of 104,892 benign apps and 108,640 malwares, and the results of experiments indicate that MalScan outperforms six state-of-the-art detectors and can quickly detect Android malware with an f-value as high as 99%. In addition, there are also significant improvements in the robustness of Android app evolution and robustness to obfuscation. Finally, we conduct an exhaustive statistical study of over one million applications in the Google-Play app market and successfully identify 498 zero-day malware, which further validates the feasibility of MalScan on market-wide malware scanning. © 2004-2012 IEEE.

关键词： Android malware

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ARCHER:a ReRAM-based accelerator for compressed recommendation systems

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Frontiers of Computer Science 2024年第5期18卷 147-160页

作者： Xinyang SHEN Xiaofei LIAO Long ZHENG Yu HUANG Dan CHEN Hai JIN National Engineering Research Center for Big Data Technology and System Services Computing Technology and System LabClusters and Grid Computing LabSchool of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China

Modern recommendation systems are widely used in modern data *** random and sparse embedding lookup operations are the main performance bottleneck for processing recommendation systems on traditional platforms as they induce abundant data movements between computing units and ***-based processing-in-memory(PIM)can resolve this problem by processing embedding vectors where they are ***,the embedding table can easily exceed the capacity limit of a monolithic ReRAM-based PIM chip,which induces off-chip accesses that may offset the PIM ***,we deploy the decomposed model on-chip and leverage the high computing efficiency of ReRAM to compensate for the decompression performance *** this paper,we propose ARCHER,a ReRAM-based PIM architecture that implements fully yon-chip recommendations under resource ***,we make a full analysis of the computation pattern and access pattern on the decomposed *** on the computation pattern,we unify the operations of each layer of the decomposed model in multiply-and-accumulate *** on the access observation,we propose a hierarchical mapping schema and a specialized hardware design to maximize resource *** the unified computation and mapping strategy,we can coordinatethe inter-processing elements *** evaluation shows that ARCHER outperforms the state-of-the-art GPU-based DLRM system,the state-of-the-art near-memory processing recommendation system RecNMP,and the ReRAM-based recommendation accelerator REREC by 15.79×,2.21×,and 1.21× in terms of performance and 56.06×,6.45×,and 1.71× in terms of energy savings,respectively.

关键词： recommendation system ReRAM processing-in-memory embedding layer

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