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检索条件"任意字段=IASTED International Conference on Parallel and Distributed Computing and Systems, PDCS 2010"

共 1020 条记录，以下是171-180 订阅

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Synthesizing generic experimental environments for simulation

Synthesizing generic experimental environments for simulatio...

引用

5th international conference on P2P, parallel, Grid, Cloud and Internet computing, 3PGCIC 2010

作者： Quinson, Martin Bobelin, Laurent Suter, Frederic Nancy University LORIA INRIA Nancy France IN2P3 Computing Center CNRS IN2P3 Lyon-Villeurbanne France

ISBN: (纸本)9780769542379

Experiments play an important role in parallel and distributed computing. Simulation is a common experimental technique that relies on abstractions of the tested application and execution environment but offers reproducibility of results and fast exploration of numerous scenarios. This article focuses on setting up the experimental environment of a simulation run. First we analyze the requirements expressed by different research communities. As the existing tools of the literature are too specific, we then propose a more generic experimental environment synthesizer called Simulacrum. This tool allows its users to select a model of a currently deployed computing grid or generate a random environment. Then the user can extract a subset of it that fulfills his/her requirements. Finally the user can export the corresponding XML representation. © 2010 IEEE.

关键词： distributed computer systems

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auto-AID: A Data Mining Framework for Autonomic Anomaly Identification in Networked Computer systems

auto-AID: A Data Mining Framework for Autonomic Anomaly Iden...

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IEEE 29th international Performance computing and Communications conference

作者： Guan, Qiang Fu, Song Univ N Texas Dept Comp Sci & Engn Denton TX 76203 USA

ISBN: (纸本)9781424493289

Networked computer systems continue to grow in scale and in the complexity of their components and interactions. Component failures become norms instead of exceptions in these environments. A failure will cause one or multiple computer(s) to be unavailable, which affects the resource utilization and system throughput. When a computer fails to function properly, health-related data are valuable for trouble shooting. However, it is challenging to effectively identify anomalies from the voluminous amount of noisy, high-dimensional data. In this paper, we present auto-AID, an autonomic mechanism for anomaly identification in networked computer systems. It is composed of a set of data mining techniques that facilitates automatic analysis of system health data. The identification results are very valuable for the system administrators to manage systems and schedule the available resources. We implement a prototype of auto-AID and evaluate it on a production institution wide compute grid. The results show that auto-AID can effectively identify anomalies with little human intervention.

关键词： Anomaly identification Data mining System dependability parallel and distributed systems

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Adaptive parallel computing for large-scale distributed and parallel applications 10

Adaptive parallel computing for large-scale distributed and ...

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Proceedings of the First international Workshop on Data Dissemination for Large Scale Complex Critical Infrastructures

作者： Balasubramanian, Jaiganesh Mintz, Alexander Kaplan, Andrew Vilkov, Grigory Gleyzer, Artem Kaplan, Antony Guida, Ron Varshneya, Pooja Schmidt, Douglas C. Zircon Computing LLC Wayne NJ United States Vanderbilt University Nashville TN United States

ISBN: (纸本)9781605589176

This paper presents the structure and functionality of zFunction, which is an adaptive distributed computing platform that supports a user-friendly programming model for developing parallel processing applications. It allows developers to design software as if they are programming for a single computer and then it automatically takes care of data distribution and task parallelization activities on different cluster nodes or multiple CPU cores. zFunction thus substantially improves the performance of complex distributed applications that process a large amount of data in real time, mission critical systems. This paper uses a representative case study from the financial services domain to show how these types of applications can benefit from zFunction. © 2010 ACM.

关键词： Real time systems

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MOBILE AGENT BASED AUTONOMIC DYNAMIC parallel computing

MOBILE AGENT BASED AUTONOMIC DYNAMIC PARALLEL COMPUTING

引用

20th Reliability, Stress Analysis, and Failure Prevention conference

作者： Chou, Yu-Cheng Ko, David Cheng, Harry H. Univ Calif Davis Dept Mech & Aeronaut Engn Integrat Engn Lab Davis CA 95616 USA

ISBN: (纸本)9780791849002

parallel computing is widely adotped in scientific and engineering applications to enhance the efficiency. Moreover, there are increasing research interests focusing on utilizing distributed networked computers for parallel computing. The Message Passing Interface (MPI) standard was designed to support portability and platform independence of a developed parallel program. However, the procedure to start an MPI-based parallel computation among distributed computers lacks autonomicity and flexibility. This article presents an autonomic dynamic parallel computing framework that provides autonomicity and flexibility that are important and necessary to some parallel computing applications involving resource constrained and heterogeneous platforms. In this framework, an MPI parallel computing environment consisting of multiple computing entities is dynamically established through inter-agent communications using the IEEE Foundation for Intelligent Physical Agents (FIPA) compliant Agent Communication Language (ACL) messages. For each computing entity in the MPI parallel computing environment, a load-balanced MPI program C source code along with the MPI environment configuration statements are dynamically composed as a mobile agent code. A mobile agent wrapping the mobile agent code is created and sent to the computing entity where the mobile agent code is retrieved and interpretively executed. An example of autonomic parallel matrix multiplication is given to demonstrate the self-configuration and self-optimization properties of the presented framework.

关键词： Engineering systems and industry applications Optimization Computation Computers Anterior cruciate ligament Stress

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distributed Data Mining Methodology for Clustering and Classification Model

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10th international conference on Artificial Intelligence and Soft computing (ICAISC 2010)

作者： Gorawski, Marcin Pluciennik-Psota, Ewa Silesian Tech Univ Inst Comp Sci PL-44100 Gliwice Poland

ISBN: (纸本)9783642132070

distributed computing and data mining are nowadays almost ubiquitous. Authors propose methodology of distributed data mining by combining local analytical models (built in parallel in nodes of a distributed computer system) into a. global one without necessity to construct distributed version of data mining algorithm. Different combining strategies for clustering and classification are proposed and their verification methods as well. Proposed solutions were tested with data sets coming from UCI Machine Learning Repository.

关键词： distributed computer systems

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Cooperative distributed problem solving through ad hoc agent coalitions

Cooperative distributed problem solving through ad hoc agent...

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2010 1st international conference on parallel, distributed and Grid computing, PDGC - 2010

作者： Singh, Vivek Kumar Singh, Akanksha Husaini, Subuhi Department of Computer Science Banaras Hindu University Varanasi India

ISBN: (纸本)9781424476725

Cooperative distributed Problem Solving refers to a loosely coupled network of problem solvers working together to solve problems that may be beyond the capabilities of individual agents. Individual nodes may not have sufficient expertise, resources or information to solve the entire problem but every node is capable of solving some part. A group of autonomous agents in a Multi-agent System often work in a cooperative manner and form coalitions to obtain higher payoff than they can get individually. The coalition formation framework of Multi-agent systems can be extended to a distributed Problem Solving formulation where agents strive to achieve higher group benefits. This paper tries to demonstrate how a group of autonomous agents can solve a package delivery domain problem with reasonably good parameters in a purely distributed manner. Unlike traditional distributed problem solving experiments, here the agents are distributed across the problem domain and all control decisions are decentralized with no agent acting as a central dispatcher/scheduler. © 2010 IEEE.

关键词： Multi agent systems

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Scalable link analysis algorithm for a distributed memory environment

Scalable link analysis algorithm for a distributed memory en...

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2010 1st international conference on parallel, distributed and Grid computing, PDGC - 2010

作者： Arulraj, Joy James Prabhu DCSE College of Engineering Anna University India

ISBN: (纸本)9781424476725

The convergence rate of iterative stationary methods for the PageRank linear system is significant for efficient computation of the relative rank of web pages based on the Web graph. This paper investigates this problem from the perspective of a message-passing framework on a distributed memory parallel programming model. A three-dimensional Web model is introduced to present a scalable link analysis algorithm that can compute the rank vector of a linear system with a high degree of convergence and accuracy. The algorithm derives its scalability by eliminating the need for any global information or page categorization. The details of the MPI-based parallel implementation and the experimental results obtained on a 8-node cluster of Intel Xeon 3.0 GHz, 1.5GB RAM machines over a 100MBit Ethernet LAN are provided. The variation in convergence behavior with residual probability is analyzed. For the WebBase crawl, a speedup of 12.45 is obtained by the scalable algorithm over the centralized algorithm. © 2010 IEEE.

关键词： Linear systems

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Proceedings - 11th ACIS international conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed computing, SNPD2010

Proceedings - 11th ACIS International Conference on Software...

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11th ACIS international conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed computing, SNPD2010

ISBN: (纸本)9780769540887

The proceedings contain 41 papers. The topics discussed include: Bayesian network inference with qualitative expert knowledge for decision support systems;semantic query validation in guided-based systems: assuring the construction of queries that make sense;user and item pattern matching in multi-criteria recommender systems;modeling of device collaboration process based on Petri net;CP-nets based methodology for integrating functional verification and performance analysis of network protocol;a novel security approach for critical information systems: preventing flooding in the non-authenticated client area using a new service from local network service providers;achieving flow-level controllability in network intrusion detection system;explaining classification by finding response-related subgroups in data;real-time implementation of synthetic aperture sonar imaging on high performance clusters;and recovering depth from a single image using dark channel prior.

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Accelerating spatial data processing with MapReduce

Accelerating spatial data processing with MapReduce

引用

16th IEEE international conference on parallel and distributed systems, ICPADS 2010

作者： Wang, Kai Han, Jizhong Tu, Bibo Dai, Jiao Zhou, Wei Song, Xuan High Performance Computer Research Center Institute of Computing Technology Chinese Academy of Sciences Beijing China Ministration Office Beijing Planetarium Beijing China

ISBN: (纸本)9780769543079

Map Reduce is a key-value based programming model and an associated implementation for processing large data sets. It has been adopted in various scenarios and seems promising. However, when spatial computation is expressed straightforward by this key-value based model, difficulties arise due to unfit features and performance degradation. In this paper, we present methods as follows: 1) a splitting method for balancing workload, 2) pending file structure and redundant data partition dealing with relation between spatial objects, 3) a strip-based two-direction plane sweeping algorithm for computation accelerating. Based on these methods, ANN(All nearest neighbors) query and astronomical cross-certification are developed. Performance evaluation shows that the Map Reduce-based spatial applications outperform the traditional one on DBMS. © 2010 IEEE.

关键词： MapReduce

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Automatically Tuned Dynamic Programming with an algorithm-by-blocks

Automatically Tuned Dynamic Programming with an algorithm-by...

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16th IEEE international conference on parallel and distributed systems, ICPADS 2010

作者： Li, Jiajia Tan, Guangming Chen, Mingyu Institute of Computing Technology Chinese Academy of Sciences China

ISBN: (纸本)9780769543079

As the complexity of current computer architecture increases, domain-specific program generators are extensively used to implement performance portable libraries. Dynamic programming is a performance-critical kernel in many applications including engineering operations and bioinformatics. In this paper, we propose an Automatically Tuned Dynamic Programming (ATDP) to optimize performance of dynamic programming algorithm across various architectures. First, an algorithm-by-blocks for dynamic programming is designed to facilitate optimizing with well-known techniques including cache and register tiling. Further, the parameterized algorithm-by-blocks is cooperative with an auto-tuning framework and leverages a hill climbing algorithm to search the possible best program on a given platform. The experiments on two x86 processors demonstrate that (i) the generated scalar programs improve performance by over 10 times, (ii) the vector programs further speedup the scalar ones by a factor of 4 and 2 for single-precision and double-precision, respectively. © 2010 IEEE.

关键词： Dynamic programming

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