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parallel EM-Clustering: Fast convergence by asynchronous model updates

Parallel EM-Clustering: Fast convergence by asynchronous mod...

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10th IEEE international conference on Data Mining Workshops, ICDMW 2010

作者： Plant, Claudia Böhm, Christian Florida State University Tallahassee FL United States University of Munich Munich Germany

ISBN: (纸本)9780769542577

The data explosion in many applications requires efficient data mining solutions. Fortunately, emerging technologies like grid and cloud computing, high-performance multi-core processors and graphics processing units provide the potential to keep pace with the data explosion and open up new opportunities for designing efficient algorithms. In this paper, we propose a parallel variant of the Expectation Maximization (EM) algorithm suitable for clustering large data sets in a distributed environment. The conventional EM algorithm sequentially iterates two phases: In the E-step, points are assigned to the clusters and in the M-step the cluster models are updated. The basic idea of our approach is allowing asynchronous model updates for faster convergence and best usage of the available resources. The frequency of the updates can be flexibly adjusted to the specific characteristics of the environment including communication costs and computing power of the single devices. An extensive experimental evaluation demonstrates the benefits of our approach. © 2010 IEEE.

关键词： Graphics processing unit

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A semantic-based meteorology grid service registry, discovery and composition framework

A semantic-based meteorology grid service registry, discover...

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2nd international conference on Semantics, Knowledge, and Grid, SKG 2006

作者： Ren, Kaijun Xiao, Nong Song, Junqiang Zhang, Weimin Chen, Tao National Laboratory for Parallel and Distributed Processing NUDT Changsha Hunan 410073 China College of Science National University of Defense Technology Changsha Hunan 410073 China

ISBN: (纸本)076952673X

Meteorology Grid Computing aims to provide scientist with seamless, reliable, secure and inexpensive access to meteorological resources. In this paper, we presented a semantic-based meteorology grid service registry, discovery and composition framework by combining grid technologies and the advantages of semantic web techniques. The main objective of the framework is to support automating the discovery, selection, and workflow composition of semantically described heterogeneous meteorological grid services, which offers the possibility of facilitating geographically distributed meteorological scientists to resolve complex scientific problems cooperately. With this framework, the key technologies such as semantic registry, semantic matchmaking, QoS ranking and composition model, will be discussed. © 2006 IEEE.

关键词： Grid computing

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In-memory distributed Matrix Computation processing and Optimization

In-memory Distributed Matrix Computation Processing and Opti...

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IEEE 33rd international conference on Data Engineering (ICDE)

作者： Yu, Yongyang Tang, Mingjie Aref, Walid G. Malluhi, Qutaibah M. Abbas, Mostafa M. Ouzzani, Mourad Purdue Univ W Lafayette IN 47907 USA Qatar Univ Doha Qatar HBKU Qatar Comp Res Inst Doha Qatar

ISBN: (纸本)9781509065431

The use of large-scale machine learning and data mining methods is becoming ubiquitous in many application domains ranging from business intelligence and bioinformatics to self-driving cars. These methods heavily rely on matrix computations, and it is hence critical to make these computations scalable and efficient. These matrix computations are often complex and involve multiple steps that need to be optimized and sequenced properly for efficient execution. This paper presents new efficient and scalable matrix processing and optimization techniques for in-memory distributed clusters. The proposed techniques estimate the sparsity of intermediate matrix-computation results and optimize communication costs. An evaluation plan generator for complex matrix computations is introduced as well as a distributed plan optimizer that exploits dynamic cost-based analysis and rule-based heuristics to optimize the cost of matrix computations in an in-memory distributed environment. The result of a matrix operation will often serve as an input to another matrix operation, thus defining the matrix data dependencies within a matrix program. The matrix query plan generator produces query execution plans that minimize memory usage and communication overhead by partitioning the matrix based on the data dependencies in the execution plan. We implemented the proposed matrix processing and optimization techniques in Spark, a distributed in-memory computing platform. Experiments on both real and synthetic data demonstrate that our proposed techniques achieve up to an order-of-magnitude performance improvement over state-of-the-art distributed matrix computation systems on a wide range of applications.

关键词： Matrix computation query optimization distributed computing

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Comparison of transaction restart techniques in a distributed database environment

Comparison of transaction restart techniques in a distribute...

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PARBASE-90: international conference on Databases, parallel Architectures, and Their applications

作者： Rusinkiewicz, Marek Leiss, Ernst L. Dubash, Rumi Dep of Comput Sci Univ of Houston Houston TX USA

The authors present the results of a simulation study carried out to compare the effects of different restart techniques on the overall throughput, number of restarts, average response time, and average communication delay in representative distributed database environments. The performances of the following transaction restart methods are compared: (1) restart with random increase of timestamp, (2) restart with random delay, (3) data-marking method, (4) data marking with random delay, and (5) restart with a substitute transaction. The substitute transaction method is shown to perform well under all loads, except for the case in which all transactions are update-only. In this case, restart with a random delay performs better. The data-marking method introduces a very high communication overhead owing to the fact that the transactions keep sending messages requesting operations when an item is not available. This results in high response times and in an erratic behavior of the system under higher loads.

关键词： Database Systems

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A Toolchain to Verify the parallelization of OmpSs-2 applications 26th

A Toolchain to Verify the Parallelization of OmpSs-2 Applica...

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26th international conference on parallel and distributed Computing (Euro-Par)

作者： Economo, Simone Royuela, Sara Ayguade, Eduard Beltran, Vicenc Barcelona Supercomp Ctr BSC Barcelona Spain Sapienza Univ Roma DIAG Antonio Ruberti Rome Italy

ISBN: (纸本)9783030576752;9783030576745

Programming models for task-based parallelization based on compile-time directives are very effective at uncovering the parallelism available in HPC applications. Despite that, the process of correctly annotating complex applications is error-prone and may hinder the general adoption of these models. In this paper, we target the OmpSs-2 programming model and present a novel toolchain able to detect parallelization errors coming from non-compliant OmpSs-2 applications. Our toolchain verifies the compliance with the OmpSs-2 programming model using local task analysis to deal with each task separately, and structural induction to extend the analysis to the whole program. To improve the effectiveness of our tools, we also introduce some ad-hoc verification annotations, which can be used manually or automatically to disable the analysis of specific code regions. Experiments run on a sample of representative kernels and applications show that our toolchain can be successfully used to verify the parallelization of complex real-world applications.

关键词： Synchronization Software testing and debugging parallel programming

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A Fast Large-size Production Data Transformation Scheme for Supporting Smart Manufacturing in Semiconductor Industry 13

A Fast Large-size Production Data Transformation Scheme for ...

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13th IEEE conference on Automation Science and Engineering (IEEE CASE)

作者： Suryajaya, Benny Chen, Chao-Chun Hung, Min-Hsiung Liu, Yu-Yang Liu, Jia-Xuan Lin, Yu-Chuan Natl Cheng Kung Univ Inst Mfg Informat & Syst Tainan Taiwan Chinese Culture Univ Dept Comp Sci & Informat Engn Taipei Taiwan

ISBN: (纸本)9781509067817

In this paper, we propose a novel data transformation scheme over a big data platform, aiming at injecting production data from the local database in the factory side and transforming them into the workpiece-centric form that many manufacturing analytics systems need. The key idea is to blend big data processing techniques, including table composition with external distributed files, columnar storage, partition, massively parallel processing into the data transformation scheme for minimizing the data processing time. Our proposed scheme brings two main impacts to the smart manufacturing. First, our scheme plays the key component to develop data-driven manufacturing decision systems, since large-volume production data sources can be efficiently transformed into the workpiece-centric form that other smart manufacturing services require. Second, our proposed scheme provides a development exemplar to assist a manufacturing factory toward the Industry-4.0 realm, since big data techniques are ingeniously blended in building data-intensive manufacturing services. We finally implement the prototype of the proposed scheme on the Hadoop platform and apply the prototype to a semiconductor factory for conducting integrated tests. Testing results of a case study physically applying the proposed scheme to a semiconductor factory demonstrate the success of our work.

关键词： cloud manufacturing big data processing industry 4.0 Hadoop databases

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Traceable Ring Signature Scheme in Internet of Vehicles Based on Lattice Cryptography 21

Traceable Ring Signature Scheme in Internet of Vehicles Base...

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21st IEEE international Symposium on parallel and distributed processing with applications, 13th IEEE international conference on Big Data and Cloud Computing, 16th IEEE international conference on Social Computing and Networking and 13th international conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Liao, Wei Han, Lansheng Chen, Peng Huazhong University of Science and Technology Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Wuhan China

ISBN: (纸本)9798350329223

Lattice cryptography, as a recognized Cryptosystem that can resist quantum computation, has great potential for development. Lattice based signature scheme is currently a research focus. In this paper, the traceable ring signature scheme based on lattice cryptography in the Internet of Vehicles (IoV) environment is studied. Firstly, users' public and private keys are generated on the lattice, which effectively reduces the key size and time cost. Secondly, the scheme also achieves traceability by adding additional information. The scheme satisfies strong unforgeability, traceability, and anonymity. In addition, the traceable ring signature scheme based on lattice cryptography is applied in the IoV environment to effectively protect user privacy. Model communication can not only protect user privacy, but also trace the signer when necessary, achieving a balance between security and privacy. The simulation results show that the average delay of IoV of our scheme is better than that of similar schemes. The research in this paper improves the security of data transmission in the IoV environment, enables it to adapt to the complex and changeable new network environment, and effectively guarantees the information security of vehicles and owners. © 2023 IEEE.

关键词： Cryptography

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Accelerating Computation of DNA Sequence Alignment in distributed Environment 4th

Accelerating Computation of DNA Sequence Alignment in Distri...

引用

4th international conference on Intelligent Computing

作者： Guo, Tao Li, Guiyang Deaton, Russel Sichuan Normal Univ Coll Comp Sci Chengdu 610066 Peoples R China Univ Arkansas Coll Comp Sci & Engn Fayetteville AR 72701 USA

ISBN: (纸本)9783540859291

Sequence similarity and alignment are most important operations in computational biology. However, analyzing large sets of DNA sequence seems to be impractical on a regular PC. Using multiple threads with JavaParty mechanism, this project has successfully implemented in extending the capabilities of regular Java to a distributed environment for simulation of DNA computation. With the aid of JavaParty and the design of multiple threads, the results of this study demonstrated that the modified regular Java program could perform parallel computing without using RMI or socket communication. In this paper, an efficient method for modeling and comparing DNA sequences with dynamic programming and JavaParty was firstly proposed. Additionally, results of this method in distributed environment have been discussed.

关键词： DNA sequences

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GISQF: An Efficient Spatial Query processing System 7

GISQF: An Efficient Spatial Query Processing System

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7th IEEE international conference on Cloud Computing (CLOUD)

作者： Al-Naami, Khaled Mohammed Seker, Sadi Khan, Latifur Univ Texas Dallas Dept Comp Sci Dallas TX 75083 USA Istanbul Medeniyet Univ Dept Business Istanbul Turkey

ISBN: (纸本)9781479950638

Collecting observations from all international news coverage and using TABARI software to code events, the Global Database of Event, Language, and Tone (GDELT) is the only global political georeferenced event dataset with 250+ million observations covering all countries in the world from January 1, 1979 to the present with daily updates. The purpose of this widely used dataset is to help understand and uncover spatial, temporal and perceptual trends and behaviors of the social and international system. To query such big geospatial data, traditional RDBMS can no longer be used and the need for parallel distributed solutions has become a necessity. MapReduce paradigm has proved to be a scalable platform to process and analyze Big Data in the cloud. Hadoop as an implementation of MapReduce is an open source application that has been widely used and accepted in academia and industry. However, when dealing with Spatial Data, Hadoop is not equipped well and falls short as it doesnt perform efficiently in terms of running time. SpatialHadoop is an extension of Hadoop with the support of spatial data. In this paper, we present Geographic Information System Querying Framework (GISQF) to process Massive Spatial Data. This framework has been built on top of the open source SpatialHadoop system which exploits two-layer spatial indexing techniques to speed up query processing. We show how this solution outperforms Hadoop query processing by orders of magnitude when applying queries on GDELT dataset with a size of 60 GB. We show the results for three types of queries, Longitude Latitude Point queries, Circle-Area queries, and Aggregation queries.

关键词： Query processing

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Fortifying NoC-based Manycores: distributed Monitoring to Detect Security Threats 31

Fortifying NoC-based Manycores: Distributed Monitoring to De...

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31st conference on Electronics Circuits and Systems

作者： Faccenda, Rafael Follmann Comaru, Gustavo Calazans, Ney Caimi, Luciano Lores Moraes, Fernando Gehm Pontificia Univ Catolica Rio Grande do Sul Sch Technol Porto Alegre Brazil Fed Univ Santa Catarina UFSC Comp Dept DEC Ararangua Brazil Fed Univ Fronteira Sul UFFS Chapeco Chapeco Brazil

ISBN: (纸本)9798350377217;9798350377200

As computing technology advances, manycore systems have become increasingly used due to their performance and parallel processing capabilities. However, these systems also present significant security risks, including threats from hardware Trojans, malicious applications, and peripherals capable of executing various attacks, such as denial-of-service, spoofing, and eavesdropping. Researchers have proposed several security enhancements to address these challenges, including establishing secure zones, authentication protocols, and security-aware routing algorithms. This paper introduces a distributed monitoring mechanism that can detect suspicious activities within NoC links, peripheral interfaces, and packet reception protocols, explicitly focusing on detecting DoS, spoofing, and eavesdropping attacks. We conducted a comprehensive attack campaign to evaluate the effectiveness of our monitoring mechanisms and test the platform's resilience. The results were promising, with the system successfully detecting all attacks and continuing to execute applications correctly. Although there was an average execution time penalty of 8.83%, which included the time taken to generate attack warnings from the monitoring mechanisms and apply countermeasures, this mechanism significantly enhanced the security of manycore systems.

关键词： Security NoC-based Manycores Security Threat Monitoring Security Evaluation

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