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Semantic Reasoning technology on Temporal Knowledge Graph 19th

Semantic Reasoning Technology on Temporal Knowledge Graph

引用

19th International Conference on Web Information systems and Applications, WISA 2022

作者： Li, Jianuo Zhao, Feng 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 Wuhan China

ISBN: (纸本)9783031203084

Semantic reasoning techniques based on knowledge graphs have been widely studied since they were proposed. Previous studies are mostly based on closed-world assumptions, which cannot reason about unknown facts. To this end, we propose the Two-Stage Temporal Reasoning Model (TSTR) for reasoning about future facts. In the first stage, probability of future facts occurring is reasoned using repeated information in history. In the second stage, the semantics of the neighborhood nodes are aggregated using the structural encoder and the temporal information is captured using the temporal encoder. The predicted probabilities are obtained by the decoder. Finally, the candidate entity probabilities of the two-stage reasoning are weighted to achieve the prediction of the two-stage fusion. We tested the performance of the TSTR on public datasets and the results demonstrated the effectiveness of the TSTR. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Recurrent neural networks

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A multi-dimensional index for privacy-preserving queries in cloud computing

A multi-dimensional index for privacy-preserving queries in ...

引用

作者： Xu, Hui Ding, Xiaofeng Jin, Hai Yu, Qing 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

Although cloud computing saves the cost of enterprises and individuals to manage data in various applications on public cloud servers, it also causes the problem of the leakage of critical personal information and sensitive data. Therefore, the issues about data privacy of the published personal information have become a challenging problem. Most of the existing methods focus on cryptography-based techniques by encrypting the sensitive data before publishing. However, these techniques are either too computation expensive or only some authorized users can get access to the encrypted cloud data. The consequence is that the search response time is not satisfactory and the sharing extent of the cloud data is becoming limited. Motivated by this, we propose a perturbation-based method to preserve the privacy of data in cloud. To accelerate the query processing without privacy breaches, a high-efficiency multi-dimensional index is built for answering range counting queries under differential privacy, which embeds privacy-preserving R-tree index in Content Addressable Network. Experimental results demonstrate that our methods not only protect data privacy in different degree, but also accelerate the query speed efficiently. Compared with the existing method Quad-opt, our method provides about 20% better data utility under the same differential privacy principles. © 2019 John Wiley & Sons, Ltd.

关键词： Sensitive data

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VMFence: A customized intrusion prevention system in distributed virtual computing environment 09

VMFence: A customized intrusion prevention system in distrib...

引用

3rd International Conference on Ubiquitous Information Management and Communication, ICUIMC'09

作者： Jin, Hai Xiang, Guofu Zhao, Feng Zou, Deqing Li, Min Shi, Lei Cluster and Grid Computing Lab. School of Computer Science and Technology Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9781605584058

Intrusion Prevention system (IPS) has been an effective tool to detect and prevent unwanted attempts, which are mainly through network and system vulnerabilities, at accessing and manipulating computer systems. Intrusion detection and prevention are two main functions of IPS. As attacks are becoming massive and complex, the traditional centralized IPSes are incapable of detecting all those attempts. The existing distributed IPSes, mainly based on mobile agent, have some serious problems, such as weak security of mobile agents, response latency, large code size. In this paper, we propose a customized intrusion prevention system, VMFence, in distributed virtual computing environment to simplify the complexity of the management. In VMFence, the states of detection processes vary with those of Virtual Machines (VMs), which are described by Deterministic Finite Automata (DFA). The detection processes, each of which detects one virtual machine, reside in a privileged virtual machine. The processes run synchronously and outside of VMs in order to achieve high performance and security. The experimental results also show VMFence has higher detection efficiency than traditional intrusion detection systems and little impact on the performance of the monitored VMs. Copyright 2009 ACM.

关键词： Intrusion detection

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Fine-grained Scheduling in FPGA-Based Convolutional Neural Networks 5

Fine-grained Scheduling in FPGA-Based Convolutional Neural N...

引用

5th IEEE International Conference on Cloud computing and Big Data Analytics, ICCCBDA 2020

作者： Zhang, Wei Liao, Xiaofei Jin, Hai 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 Wuhan China

ISBN: (纸本)9781728160245

FPGA has been considered as a promising solution to accelerate Convolutional Neural Networks (CNNs) for its excellent performance in energy efficiency and programmability. However, prior designs are usually designed for inference only as designers can map pre-trained models to the hardware in a very efficient way. However, those approaches may not be suitable for training CNN models. In this paper, we propose FConv, in which the CPU and FPGA work together in a fine-grained manner. The FPGA accelerator in FConv uses one Winograd-based convolver, which reduces the design complexity and improves performance. We apply double-buffer for output routine to effectively overlap computation and data transfer. We also integrate multiple PEs to improve data parallelism. We propose our analytical model for prediction and use it as a guide in task scheduling. We find the upper limit of performance under the current design based on the analytical model. We evaluate our design on VGG-16 and Densnet-40 on ImageNet and CIFAR-10. We achieve 262.43 GOP/s on the VGG-16 model, which is 2.13 times of the performance compared to FFT-based implementation on the same platform. We also achieve at most 4 times+ performance improvement compared MKL with 20 threads running on 10 core Intel processors. © 2020 IEEE.

关键词： Field programmable gate arrays (FPGA)

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A control mechanism about quality of service for resource management in simulation grid

A control mechanism about quality of service for resource ma...

引用

4th International Conference on Computational and Information Sciences, ICCIS 2012

作者： Kuang, Ping Jin, Hai Cluster and Grid Computing Lab. School of Computer Science and Technology Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780769547893

The simulation grid has become a very important research topic. In order to ensure the QoS of resource management, we present a control mechanism in simulation grid, which is based on the prediction methods. In the control mechanism, we first introduce our resource management module in simulation grid. Then, we propose a resource allocation algorithm. In order to justify the feasibility and the availab.lity of this control mechanism, a series of experiments have been done. The results show that it is feasible to schedule the system resources and control the QoS of system resources for tasks in simulation grid. © 2012 IEEE.

关键词： Quality of service

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The Entry-Extensible Cuckoo Filter 17th

The Entry-Extensible Cuckoo Filter

引用

17th IFIP WG 10.3 International Conference on Network and Parallel computing, NPC 2020

作者： Yu, Shuiying Wu, Sijie Chen, Hanhua 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 Wuhan China

ISBN: (纸本)9783030794774

The emergence of large-scale dynamic sets in real applications brings severe challenges in approximate set representation structures. A dynamic set with changing cardinality requires an elastic capacity of the approximate set representation structure, while traditional static structures, e.g., bloom filter, cuckoo filter, and their variants cannot satisfy the requirements. Existing dynamic approximate set representation structures only provide filter-level extensions, which require a single membership query to probe all discrete filters one by one. The large number of small discrete memory accesses takes up the vast majority of query time and results in unsatisfied query performance. To address the problem, in this work we propose the entry-extensible cuckoo filter (E2CF) to reduce memory access overhead for dynamic set representation and accelerate the membership query. E2CF utilizes adjacent buckets with continuous physical addresses in a cuckoo filter to extend bucket entries, which avoids many discrete memory accesses in a query. To further make E2CF space and time efficient, we adopt asynchronous extension and fine-grained splitting methods. Experiment results show that compared to state-of-the-art designs, E2CF reduces the query and insertion time by 82% and 28%, respectively. © 2021, IFIP International Federation for Information Processing.

关键词： Data structures

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DPLM: A novel application-layer routing scheme for low delay VoIP 08

DPLM: A novel application-layer routing scheme for low delay...

引用

4th Asian Internet Engineering Conference, AINTEC 2008

作者： Liao, Xiaofei Jin, Hai Zhu, Lili Cluster and Grid Computing Lab. School of Computer Science and Technology Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9781605581279

In order to achieve low delay services in VoIP, we can use application-layer routing scheme, which is to find proper relay nodes to intermediate voice packets from the source peer to the destination peer. The difficulty of the scheme is how to find the proper relay nodes, which we call relay problem. This paper presents a new application-layer routing scheme, called DPLM, to resolve relay problem. We introduced the mechanism in detail, and evaluated our mechanism in NS2 network simulation environment and got a high relay node hit ratio result, which confirms the feasibility of a real system. Also we make a comparison with traditional schemes, and the results show that DPLM scheme has good performances. Copyright 2008 ACM.

关键词： Routing protocols

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Image segmentation for silicosis diagnosis in grid environment 09

Image segmentation for silicosis diagnosis in grid environme...

引用

1st International Conference on Internet Multimedia computing and Service, ICIMCS 2009

作者： Zheng, Ran Jin, Hai Zhang, Qin Zhang, Liang Cluster and Grid Computing Lab. School of Computer Science and Technology Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9781605588407

Silicosis is one of the most serious occupational diseases in China. Radiologist information comes from chest radiographs, in which the most important parts are lung fields and ribs. It is necessary to distinguish lung fields and ribs from other organs. The anatomical knowledge-based lung segmentation can improve the accuracy of segmentation and solve the problems of opened region and lost clavicle region. The curve model-based rib segmentation can acquire more accurate rib location information, and provide more efficient orientation for latter diagnosis. These two methods are also deployed in grid environment to get higher efficiency when processing massive and distributed medical data for silicosis diagnosis. Experiments show that the two proposed algorithms can meet the latter medical requirements for chest radiograph with higher accuracy. Copyright 2009 ACM.

关键词： Computer aided diagnosis

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An efficient distributed transactional memory system

An efficient distributed transactional memory system

引用

11th IEEE International Conference on Trust, Security and Privacy in computing and Communications, TrustCom-2012

作者： Peng, Xin Liao, Xiaofei Jin, Hai Fan, Xuepeng Tu, Xuping Yu, Linchen Cluster and Grid Computing Lab. School of Computer Science and Technology Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780769547459

Transactional memory (TM) is a parallel programming concept which reduces challenges in parallel programming. Existing distributed transactional memory system consumes too much bandwidth and brings high latency. In this work, we present Transactional Memory system for cluster (Clustm), a generalized and scalab.e distributed transactional memory system. Our system addresses several open issues posed by this domain, including transactional memory consistency protocol, cache consistency protocol, and the distribution strategy of the metadata of shared data across the cluster. Then, we evaluate our design with several workloads, and the results demonstrate outstanding performance. © 2012 IEEE.

关键词： Parallel programming

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SpaHet: A Software/Hardware Co-design for Accelerating Heterogeneous-Sparsity based Sparse Matrix Multiplication 24

SpaHet: A Software/Hardware Co-design for Accelerating Heter...

引用

61st ACM/IEEE Design Automation Conference, DAC 2024

作者： Huang, Haoqin Yao, Pengcheng An, Zhaozeng Sun, Yufei Hu, Ao Xu, Peng Zheng, Long Liao, Xiaofei Jin, Hai 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 Wuhan430074 China Zhejiang Lab Hangzhou311121 China

ISBN: (纸本)9798400706011

Sparse general matrix-matrix multiplication is widely used in data mining applications. Its irregular memory access patterns limit the performance of general-purpose processors, thus motivating many FPGA-based hardware innovations in recent years. Nevertheless, existing accelerators fail to efficiently support heterogeneous input matrix sparsity, which is universal in various real-world applications. With in-depth experimental analysis, we observe that their performance is bottlenecked by their fixed tiling mechanisms, which only alleviate the irregularity of one input matrix. Based on the observation, we propose SpaHet, a software/hardware co-design to accelerate heterogeneous-sparsity based sparse matrix multiplication. SpaHet adopts a dual-adaptive sliding window mechanism to cover the reuse characteristics of both input matrices simultaneously. With a specialized exploration algorithm, the window-based mechanism can automatically find the optimal tiling strategy instead of applying a fixed one based on empirical experience. A sparsity-aware merge tree is also proposed to maximize the output matrix reuse via accumulating intermediate results thoroughly. Our results on a Xilinx Alveo U280 accelerator card show that SpaHet outperforms state-of-the-art CPU-, GPU- and FPGA-based solutions by 7.71×, 1.1×, and 2.74× in performance, respectively. © 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.

关键词： Program processors

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