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20th International Conference on parallel and distributed computing, Applications and Technologies, PDCAT 2019

作者： Peng, Xiangjun Wang, Qingfeng Sun, Xu Gong, Chunye Wang, Yaohua User-Centric Computing Group University of Nottingham Ningbo China China Department of Computer Science and Technology National University of Defense Technology China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology China

ISBN: (纸本)9781728126166

User-Item (U-I) matrix has been used as the dominant data infrastructure of Collaborative Filtering (CF). To reduce space consumption in runtime and storage, caused by data sparsity and growing need to accommodate side information in CF design, one needs to go beyond the U-I Matrix. In this paper, we took a case study of Succinct Representations in Collaborative Filtering, rather than using a U-I Matrix. Our key insight is to introduce Succinct Data Structures as a new infrastructure of CF. Towards this, we implemented a User-based K-Nearest-Neighbor CF prototype via Wavelet Tree, by first designing a Accessible Compressed Documents (ACD) to compress U-I data in Wavelet Tree, which is efficient in both storage and runtime. Then, we showed that ACD can be applied to develop an efficient intersection algorithm without decompression, by taking advantage of ACD's characteristics. We evaluated our design on 1,000 cores of Tianhe-II supercomputer, with one of the largest public data set ml-20m. The results showed that our prototype could achieve 3.7 minutes on average to deliver the results. © 2019 IEEE.

关键词： Collaborative filtering

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PUF-based secure checker protocol for Networked RFID Systems

PUF-based secure checker protocol for Networked RFID Systems

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IEEE Conference on Open Systems (ICOS)

作者： Biplob Ray Morshed Chowdhury Jemal Abawaiy Parallel and Distributed Computing Laboratory Deakin University Melbourne Australia Deakin University Burwood VIC AU

Radio Frequency Identification (RFID) system is an emerging technology for automating object identification. The Networked RFID System (NRS) is a component of a distributed object identification network which facilitates automated supply chain management. It also makes the Internet of Things (IoT) concept a reality. To increase the business feasibility of NRS implementation, the system should be able to ensure the visibility and traceability of the object throughout the chain using a checker protocol. By doing so, the protocol will check the genuineness of the object and the genuineness of the object's previous travel path on-site. While doing so, the protocol needs to ensure the security requirement of the system. To this end, we propose a secure checker protocol for NRS which will use a PUF (Physically Unclonable Function) and simple cryptographic primitives. The protocol provides security (protect privacy of the partners, injection of fake objects, non-repudiation, and unclonability), visibility and traceability for NRS. It is also suitable for passive tags.

关键词： Protocols Radiofrequency identification Security Privacy Supply chains Equations

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Simultaneously Learning Syntactic Dependency and Semantics Reasonability for Relation Extraction

Simultaneously Learning Syntactic Dependency and Semantics R...

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International Conference on Image, Vision and Intelligent Systems, ICIVIS 2021

作者： Wang, Xin Yin, Nan Zhang, Xiang Bai, Xinyi Luo, Zhigang College of Computer National University of Defense Technology Changsha China Institute for Quantum and State Key Laboratory of High Performance Computing National University of Defense Technology Changsha China Science and Technology on Parallel and Distributed Laboratory National University of Defense Technology Changsha China

ISBN: (纸本)9789811669620

Relation extraction as an important Natural Language Processing (NLP) task is to identify relations between named entities in text. Recently, graph convolutional networks over dependency trees have been widely used to capture syntactic features and achieved attractive performance. However, most existing dependency-based approaches ignore the positive influence of the words outside the dependency trees, sometimes conveying rich and useful information on relation extraction. In this paper, we propose a novel model, Entity-aware Self-attention Contextualized GCN (ESC-GCN), which efficiently incorporates syntactic structure of input sentences and semantic context of sequences. To be specific, relative position self-attention obtains the overall semantic pairwise correlation related to word position, and contextualized graph convolutional networks capture rich intra-sentence dependencies between words by adequately pruning operations. In this way, our proposed model not only reduces the noisy impact from dependency trees but also obtains easily-ignored entity-related semantic representation. Extensive experiments demonstrate that our model achieves encouraging performance. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Semantics

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parallel Accelerating Ultra-Long Read Alignment by Vertical Partitioning Data

Parallel Accelerating Ultra-Long Read Alignment by Vertical ...

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International Symposium on parallel Architectures, Algorithms and Programming (PAAP)

作者： Deng Pan Cheng Zhong Danyang Chen Jinxiong Zhang Feng Yang School of Computer Electronics and Information Key Laboratory of Parallel Distributed Computing Technology in Guangxi Universities Guangxi University Nanning Guangxi China School of Computer Electronics and Information Key Laboratory of Parallel Distributed Computing Guangxi University Nanning Guangxi China

ISBN: (纸本)9781665452199

The alignment between sequencing reads and genome is a basic work in biological big data analysis. Each read of the third generation sequencing data is getting longer, and the data size is getting larger. To effectively solve the ultra-long read alignment problem with high requirements for computing and memory capacity, a strategy for vertical partitioning ultra-long reads on hybrid CPU/GPU cluster is proposed, and a heap data structure is used to filter the local aligned results in all computing nodes of the parallel cluster system according to the alignment score to reduce the data transmission size. The methods for early termination and parallel merging-splicing are used to accelerate splicing local aligned results. The local aligned results among all computing nodes are collected and extended to obtain the final alignment results. The experimental results on datasets of simulated and real ultra-long reads show that the proposed parallel alignment algorithm can obtain high alignment accuracy, sensitivity and base-level sensitivity as a whole, and accelerate completing alignment between ultra-long reads and reference genome.

关键词： Sequential analysis Sensitivity Splicing Merging Memory management Genomics Programming

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Decision tree construction for data mining on grid computing environments

Decision tree construction for data mining on grid computing...

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19th International Conference on Advanced Information Networking and Applications, AINA 2005

作者： Yang, Chao-Tung Tsai, Shu-Tzu Li, Kuan-Ching High-Performance Computing Laboratory Department of Computer Science and Information Engineering Tunghai University Taichung City 40704 Taiwan Parallel and Distributed Processing Center Department of Computer Science and Information Management Providence University Taichung County 43301 Taiwan

ISBN: (纸本)0769522491

In this paper, we present our Grid-based decision tree architecture, with the intention of applying it to both parallel and sequential algorithms. Also, we show that, based on the scope and model of data mining applied in the Grid environment as well as user equivalent perspective, Grid roles can be categorized into three types. It is our goal, through these definitions, to help software developers define clear system processes and differentiate the application scope for software applications. To, fulfill our architecture, we first apply an existing parallel decision tree algorithm (the SPRINT algorithm) to the Grid environment. The performance and differences in many other areas are compared using datasets of different sizes. The experimental results will be used for future reference and further development. © 2005 IEEE.

关键词： Data mining

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The collaborative P-GRADE Grid Portal

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5th International Conference on Computational Science - ICCS 2005

作者： Lewis, Gareth J. Sipos, Gergely Urmetzer, Florian Alexandrov, Vassil N. Kacsuk, Peter Advanced Computing and Emerging Technologies Centre School of Systems Engineering University of Reading WhiteKnights Reading RG6 6AY United Kingdom MTA SZTAKI Laboratory of Parallel and Distributed Systems H-1518 Budapest Hungary

ISBN: (纸本)9783540260448

Grid portals are increasingly used to provide uniform access to the grid infrastructure. This paper describes how the P-GRADE Grid Portal could be used in a collaborative manner to facilitate group work and support the notion of Virtual Organisations. We describe the development issues involved in the construction of a collaborative portal, including ensuring a consistent view between participants of a collaborative workflow and management of proxy credentials to allow separate nodes of the workflow to be submitted to different grids. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Computational methods

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Efficient and available in-memory KV-store with hybrid erasure coding and replication 16

Efficient and available in-memory KV-store with hybrid erasu...

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Proceedings of the 14th Usenix Conference on File and Storage Technologies

作者： Heng Zhang Mingkai Dong Haibo Chen Shanghai Key Laboratory of Scalable Computing and Systems Institute of Parallel and Distributed Systems Shanghai Jiao Tong University

ISBN: (纸本)9781931971287

In-memory key/value store (KV-store) is a key building block for many systems like databases and large websites. Two key requirements for such systems are efficiency and availability, which demand a KV-store to continuously handle millions of requests per second. A common approach to availability is using replication such as primary-backup (PBR), which, however, requires M + 1 times memory to tolerate M failures. This renders scarce memory unable to handle useful user *** paper makes the first case of building highly available in-memory KV-store by integrating erasure coding to achieve memory efficiency, while not notably degrading performance. A main challenge is that an in-memory KV-store has much scattered metadata. A single KV put may cause excessive coding operations and parity updates due to numerous small updates to metadata. Our approach, namely Cocytus, addresses this challenge by using a hybrid scheme that leverages PBR for small-sized and scattered data (e.g., metadata and key), while only applying erasure coding to relatively large data (e.g., value). To mitigate well-known issues like lengthy recovery of erasure coding, Cocytus uses an online recovery scheme by leveraging the replicated metadata information to continuously serving KV requests. We have applied Cocytus to Memcached. Evaluation using YCSB with different KV configurations shows that Cocytus incurs low overhead for latency and throughput, can tolerate node failures with fast online recovery, yet saves 33% to 46% memory compared to PBR when tolerating two failures.

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Multi-level Shared Knowledge Guided Learning for Knowledge Graph Completion

arXiv

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arXiv 2024年

作者： Shan, Yongxue Zhou, Jie Peng, Jie Zhou, Xin Yin, Jiaqian Wang, Xiaodong National Key Laboratory of Parallel and Distributed Computing College of Computer National University of Denfense Technology Changsha China

In the task of Knowledge Graph Completion (KGC), the existing datasets and their inherent subtasks carry a wealth of shared knowledge that can be utilized to enhance the representation of knowledge triplets and overall performance. However, no current studies specifically address the shared knowledge within KGC. To bridge this gap, we introduce a multi-level Shared Knowledge Guided learning method (SKG) that operates at both the dataset and task levels. On the dataset level, SKG-KGC broadens the original dataset by identifying shared features within entity sets via text summarization. On the task level, for the three typical KGC subtasks – head entity prediction, relation prediction, and tail entity prediction – we present an innovative multi-task learning architecture with dynamically adjusted loss weights. This approach allows the model to focus on more challenging and underperforming tasks, effectively mitigating the imbalance of knowledge sharing among subtasks. Experimental results demonstrate that SKG-KGC outperforms existing text-based methods significantly on three well-known datasets, with the most notable improvement on WN18RR (MRR: 66.6%→72.2%, Hit@1: 58.7%→67.0%). Copyright © 2024, The Authors. All rights reserved.

关键词： Knowledge graph

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Direct method-green's theory: From PDE to BIE in the geometric transformation

Direct method-green's theory: From PDE to BIE in the geometr...

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2016 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR 2016

作者： Yang, Li-Na Li, Tao-Shen Tang, Yuan Yan Xu, Jia Pan, Jian-Jia Luo, Hui-Wu Zheng, Xian-Wei School of Computer Electronics and Information Guangxi University Nanning530004 China Department of Computer and Information Science Faculty of Science and Technology University of Macau China Guangxi Colleges Universities Key Laboratory of Parallel and Distributed Computing Nanning530004 China

ISBN: (纸本)9781509035885

In this research, we apply the Green's theory for converting the partial differential equation to the boundary integral equation for geometric transformation. Green's theory is designed specifically for integral equation. It is efficient in detecting the singularity point to the geometric transformation that has been verified. Experimental results show that the Green's theory has good performance. © 2016 IEEE.

关键词： Partial differential equations

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An enhanced parallel loop self-scheduling scheme for cluster environments

An enhanced parallel loop self-scheduling scheme for cluster...

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19th International Conference on Advanced Information Networking and Applications, AINA 2005

作者： Yang, Chao-Tung Cheng, Kuan-Wei Li, Kuan-Ching High-Performance Computing Laboratory Department of Computer Science and Information Engineering Tunghai University Taichung City 40704 Taiwan Parallel and Distributed Processing Center Department of Computer Science and Information Management Providence University Taichung County 43301 Taiwan

ISBN: (纸本)0769522491

In this paper, a parallel loop self-scheduling scheme for heterogeneous PC cluster systems is proposed. Though the proposed scheme does allow users to choose parameters before the execution initialization phase, there are still weaknesses that motivate us to go further with new improvements in that scheme. For instance, a decision on a fixed and monotonous parameter can easily lead to invalid schedule by using previous input information. Thus, it is proposed in this paper a new scheme, where the scheduling parameter can be adjusted dynamically and fit into most widely available computer systems, in order to provide higher overall performance. © 2005 IEEE.

关键词： Scheduling

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