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检索条件"任意字段=International Conference on Parallel and Distributed Processing Techniques and Applications"

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New Developments in distributed applications and Interoperable Systems

引用

丛书名： IFIP Advances in Information and Communication Technology Ser.

2001年

作者： Zielinski Geihs, Kurt Springer

ISBN: (数字)9780306470059

ISBN: (纸本)9780792374817

distributed applications are a necessity in most central application sectors of the contemporary information society, including e-commerce, e-banking, e-learning, e-health, telecommunication and transportation. This results from a tremendous growth of the role that the Internet plays in business, administration and our everyday activities. This trend is going to be even further expanded in the context of advances in broadband wireless communication. New Developments in distributed applications and Interoperable Systems focuses on the techniques available or under development with the goal to ease the burden of constructing reliable and maintainable interoperable information systems providing services in the global communicating environment. The topics covered in this book include: Context-aware applications; Integration and interoperability of distributed systems; Software architectures and services for open distributed systems; Management, security and quality of service issues in distributed systems; Software agents and mobility; Internet and other related problem areas. The book contains the proceedings of the Third international Working conference on distributed applications and Interoperable Systems (DAIS'2001), which was held in September 2001 in Kraków, Poland, and sponsored by the international Federation on Information processing (IFIP). The conference program presents the state of the art in research concerning distributed and interoperable systems. This is a topical research area where much activity is currently in progress. Interesting new aspects and innovative contributions are still arising regularly. The DAIS series of conferences is one of the main international forums where these important findings are reported.

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An optimized parallel Failure-less Aho-Corasick algorithm for DNA sequence matching 8

An optimized Parallel Failure-less Aho-Corasick algorithm fo...

引用

8th IEEE international conference on Information and Automation for Sustainability, ICIAfS 2016

作者： Thambawita, D.R.V.L.B. Ragel, Roshan G. Elkaduwe, Dhammike Department of Computer Science and Technology Uva Wellassa University Badulla Sri Lanka Department of Computer Engineering University of Peradeniya Sri Lanka

ISBN: (纸本)9781509061327

The Aho-Corasick algorithm is a multiple patterns searching algorithm running sequentially in various applications like network intrusion detection and bioinformatics for finding several input strings within a given large input string. The parallel version of the Aho-Corasick algorithm is called as parallel Failure-less Aho-Corasick algorithm because it doesnt need failure links like in the original Aho-Corasick algorithm. In this research, we implemented an application specific parallel failureless Aho-Corasick algorithm on the general purpose graphic processing unit by applying several cache optimization techniques for matching DNA sequences. Our parallel Aho-Corasick algorithm shows better performance than the available parallel Aho-Corasick algorithm library due to its simplicity and optimized cache memory usage of graphic processing units for matching DNA sequences. © 2016 IEEE.

关键词： Graphics processing unit

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Towards Performance Optimization for Hadoop MapReduce applications 17

Towards Performance Optimization for Hadoop MapReduce Applic...

引用

17th international conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2020

作者： Htay, Than Than Phyu, Sabai University of Computer Studies Yangon Ministry of Education Yangon Myanmar

ISBN: (数字)9781728164861

ISBN: (纸本)9781728164861

Apache Hadoop is a widely used open-source distributed platform towards big data processing and provides YARN based distributed parallel processing framework on low cost commodity machines. However, YARN adopts static resource management (that is, the number of containers available per node and the size of each container are static in nature) depending on pre-configured default resource units called containers leading to poor performance to deal with various sort of MapReduce applications. In addition, during the last wave of a job, many available resources occur frequently being idle because YARN does not consider the wave behavior in tasks of MapReduce applications. To take advantage of idle resources resulting in performance improvement, the important parameter, the number of map tasks is needed to optimize based on the available resources and governed by split size. Therefore, this parameter is optimized through the split size tuning based on the available resources. To address the drawback of static resource management of yarn in Hadoop, the numbers of concurrent containers per machine are tuned to optimize the node performance for running each MapReduce application. As per experimental results, the proposed system that optimizes the selected parameter on optimized concurrent containers can achieve the performance gains of MapReduce applications while reducing the optimization overheads. © 2020 IEEE.

关键词： Containers

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OEIRM: An open distributed processing based interoperability reference model for e-Science

OEIRM: An open distributed processing based interoperability...

引用

9th IFIP international conference on Network and parallel Computing, NPC 2012

作者： Zhao, Zhiming Grosso, Paola De Laat, Cees System and Network Engineering Research Group Informatics Institute University of Amsterdam 1098XH Amsterdam Netherlands

ISBN: (纸本)9783642356056

E-Science applications are often interdisciplinary and require resources from different infrastructures;the interoperability between heterogeneous infrastructures is an important requirement for constructing large scale experiments. Analyzing interoperability issues by including both application and infrastructure aspects promotes a global view on interoperability of different layers, and we argue it can converge to an optimal reference model to guide the development of service layers in e-Science infrastructures. This paper proposes an Open distributed processing based interoperability reference model for e-Science. © IFIP international Federation for Information processing 2012.

关键词： Interoperability

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Demeter: Resource-Efficient distributed Stream processing under Dynamic Loads with Multi-Configuration Optimization 24

Demeter: Resource-Efficient Distributed Stream Processing un...

引用

15th ACM/SPEC international conference on Performance Engineering (ICPE)

作者： Geldenhuys, Morgan K. Scheinert, Dominik Kao, Odej Thamsen, Lauritz Tech Univ Berlin Berlin Germany Univ Glasgow Glasgow Lanark Scotland

ISBN: (纸本)9798400704444

distributed Stream processing (DSP) focuses on the near real-time processing of large streams of unbounded data. To increase processing capacities, DSP systems are able to dynamically scale across a cluster of commodity nodes, ensuring a good Quality of Service despite variable workloads. However, selecting scaleout configurations which maximize resource utilization remains a challenge. This is especially true in environments where workloads change over time and node failures are all but inevitable. Furthermore, configuration parameters such as memory allocation and check-pointing intervals impact performance and resource usage as well. Sub-optimal configurations easily lead to high operational costs, poor performance, or unacceptable loss of service. In this paper, we present Demeter, a method for dynamically optimizing key DSP system configuration parameters for resource efficiency. Demeter uses Time Series Forecasting to predict future workloads and Multi-Objective Bayesian Optimization to model runtime behaviors in relation to parameter settings and workload rates. Together, these techniques allow us to determine whether or not enough is known about the predicted workload rate to proactively initiate short-lived parallel profiling runs for data gathering. Once trained, the models guide the adjustment of multiple, potentially dependent system configuration parameters ensuring optimized performance and resource usage in response to changing workload rates. Our experiments on a commodity cluster using Apache Flink demonstrate that Demeter significantly improves the operational efficiency of long-running benchmark jobs.

关键词： distributed Stream processing Cluster Resource Management Performance Profiling Performance Modeling Runtime Optimization Time Series Forecasting Cloud Computing

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Software component technology for high performance parallel and grid computing 7

引用

7th European conference on parallel Computing, Euro-Par 2001

作者： Gannon, Dennis Department of Computer Science Indiana University United States

ISBN: (纸本)3540424954

A software component framework is one where an application designer programs by composing well understood and tested "components" rather than writing large volumes of not-very-reusable code. The software industry has been using component technology to build desktop applications for about ten years now. More recently this idea has been extended to application in distributed systems with frameworks like the Corba Component Model and Enterprise Java Beans. With the advent of Grid computing, high performance applications may be distributed over a wide area network of compute and data servers. Also "peerto-peer" applications exploit vast amounts of parallelism exploiting the resources of thousands of servers. In this talk we look at the problem of building a component technology for scientific applications. The common component architecture project seeks to build a framework that allows software components runing on a massively parallel computers to be linked together to form wide-area, high performance application services that may be accessed from desktop applications. This problem is far from being solved and the talk will describe progress to date and outline some of the difficult problems that remain to be solved. © Springer-Verlag Berlin Heidelberg 2001.

关键词： Grid computing

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Applying Data Mapping techniques to Vector DSPs

Applying Data Mapping Techniques to Vector DSPs

引用

7th SAMOS international Workshop

作者： Westermann, Peter Schwoerer, Ludwig Kaufmann, Andre Dortmund Univ Technol Circuits & Syst Lab D-44221 Dortmund Germany Bochum Univ Appl Sci Inst Commun & Elect D-44801 Bochum Germany Nokia GmbH D-44807 Bochum Germany

ISBN: (纸本)1424410584

Vector digital signal processors (DSPs) offer a good performance to power consumption ratio. Therefore, they are suitable for mobile devices in software defined radio applications. These vector DSPs require input algorithms with vector operations. The performance of vectorized algorithms to a great extent depends on the distribution of data on vector elements. Traditional algorithms for vectorization focus on the extraction of parallelism from a program;we propose an analysis tool that focuses on the selection of an efficient dynamic data mapping for vector DSPs. We transferred Garcia's communication parallelism graph (Garcia et al., IEEE Trans parallel Distrib Syst 12: 416-431, 2001) for distributed memory multiprocessor systems to vector DSPs. By alternating the representation of two-dimensional data distributions and the cost models, we are able to determine a dynamic mapping of data on vector elements on the Embedded Vector Processor (EVP) (van Berkel et al., Proceedings of the 2004 software-defined radio technical conference SDR'04, 2004). Additionally, we propose a new efficient algorithm for processing the graph representation that operates in two steps. We demonstrate the capabilities of our tool by describing the vectorization of some MIMO OFDM algorithms.

关键词： Vector DSPs Vectorizing compilers

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A literature review on sentiment analysis techniques involving social media platforms 6

A literature review on sentiment analysis techniques involvi...

引用

6th international conference on parallel, distributed and Grid Computing, PDGC 2020

作者： Garg, Samarth Panwar, Divyansh Singh Gupta, Aakansha Katarya, Rahul Delhi Technological University Department of Computer Science and Engineering Delhi India

ISBN: (纸本)9781728171326

Sentiment analysis refers to the active field of Natural language processing that extracts the attitude and emotion of a human being. With the growth of social media, more people are using online platforms such as Twitter, Facebook, Y ouTube, etc. to express their opinions. Twitter is considered to be the purest platform to express one's views. Mostly all personalities from diverse backgrounds use twitter. Therefore, it becomes a need of the hour to study public opinion. This provides us valuable information and helps organizations and governments to contemplate mass public opinion and take better decisions accordingly. In this review paper, an extensive and exhaustive guide to the subfield of Natural language processing (NLP), focusing precisely on sentiment analysis on twitter dataset, has been presented. It highlights three main approaches to analyze the sentiment. We have summarized and compared the approaches on different metrics opted by various researchers in the field of sentiment analysis using the twitter dataset. With so much active work in this field, this review paper would assist all future researchers. © 2020 IEEE.

关键词： Sentiment analysis

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Algorithms and Architectures for parallel processing 1

引用

丛书名： Lecture Notes in Computer Science

1000年

作者： Yang Xiang Wanlei Zhou Alfredo Cuzzocrea Michael Hobbs

ISBN: (数字)9783642246692

ISBN: (纸本)9783642246685

This two volume set LNCS 7016 and LNCS 7017 constitutes the refereed proceedings of the 11th international conference on Algorithms and Architectures for parallel processing, ICA3PP 2011, held in Melbourne, Australia, in October 2011. The second volume includes 37 papers from one symposium and three workshops held together with ICA3PP 2011 main conference. These are 16 papers from the 2011 international Symposium on Advances of distributed Computing and Networking (ADCN 2011), 10 papers of the 4th IEEE international Workshop on Internet and distributed Computing Systems (IDCS 2011), 7 papers belonging to the III international Workshop on Multicore and Multithreaded Architectures and Algorithms (M2A2 2011), as well as 4 papers of the 1st IEEE international Workshop on parallel Architectures for Bioinformatics Systems (HardBio 2011).

关键词： Algorithm Analysis and Problem Complexity Artificial Intelligence Software Engineering Information Systems applications (incl. Internet) Computer Communication Networks Management of Computing and Information Systems

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Evaluation of architecture-aware optimization techniques for Convolutional Neural Networks 31

Evaluation of architecture-aware optimization techniques for...

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31st Euromicro international conference on parallel, distributed and Network-Based processing, PDP 2023

作者： Marichal, Raul Toyos, Guillermo Dufrechou, Ernesto Ezzatti, Pablo Instituto de Computación Universidad de la República Facultad de Ingeniería Montevideo Uruguay

ISBN: (纸本)9798350337631

The growing need to perform Neural network inference with low latency is giving place to a broad spectrum of heterogeneous devices with deep learning capabilities. Therefore, obtaining the best performance from each device and choosing the most suitable platform for a given problem has become challenging. This paper evaluates multiple inference platforms using architecture-aware optimizations for convolutional neural networks. Specifically, we use TensorRT and OpenVINO frameworks for hardware optimizations on top of the platform-aware NetAdapt algorithm. The experimental evaluation shows that on MobileNet and AlexNet, using NetAdapt with TensorRT or Open-VINO can improve latency up to 10 x and 5.3 x, respectively. Moreover, a throughput test using different batch sizes showed variable performance improvement on the different devices. Discussing the experimental results can guide the selection of devices and optimizations for different AI solutions. © 2023 IEEE.

关键词： Edge computing

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