Many prediction techniques based on historical data have been proposed to reduce over-estimations of job runtimes provided by users. they were shown to improve the accuracy of runtime estimates and scheduling performa...
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ISBN:
(纸本)9780889867048
Many prediction techniques based on historical data have been proposed to reduce over-estimations of job runtimes provided by users. they were shown to improve the accuracy of runtime estimates and scheduling performance of backfill policies, according to particular error metrics and average performance measures. However, using a more complete set of performancemeasures and a new error metric, we show potential performance problems of using previous prediction techniques for job scheduling. Furthermore, we show simply adding half of the requested runtime to each initial prediction greatly reduces the problems.
this paper presents comprehensive evaluations of parallel double Divide and Conquer for singular value decomposition on a super computer, HPC2500. For bidiagonal SVD, double Divide and Conquer was proposed. It first c...
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ISBN:
(纸本)9780889867048
this paper presents comprehensive evaluations of parallel double Divide and Conquer for singular value decomposition on a super computer, HPC2500. For bidiagonal SVD, double Divide and Conquer was proposed. It first computes singular values by a compact version of Divide and Conquer. the corresponding singular vectors are then computed by twisted factorization. the speed and accuracy of double Divide and Conquer are as good or even better than standard algorithms such as QR and the original Divide and Conquer. Moreover, it shows high scalability even on a PC cluster, distributed memory architecture. parallel algorithm of dDC and numerical results in some architectural options, matrix sizes and types on HPC2500, SMP cluster is shown.
Data clustering is a common technique for data analysis, which is used in many fields, including machine learning, data mining, pattern recognition, image analysis and bioinformatics. Due to the continuous increase of...
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ISBN:
(纸本)9780889867048
Data clustering is a common technique for data analysis, which is used in many fields, including machine learning, data mining, pattern recognition, image analysis and bioinformatics. Due to the continuous increase of datasets size and the intensive computation of clustering algorithms when used for analyzing large datasets, developing of efficient clustering algorithms is needed for processing time reduction. this paper describes the design and implementation of a recently developed clustering algorithm RACAL [1], which is a RAdius based Clustering ALgorithm. the proposed parallel algorithm (PRACAL) has the ability to cluster large datasets of high dimensions in a reasonable time, which leads to a higher performance computing.
An optimal mobile agent moving policy for a mobile agent network where a single mobile agent moves and collects management information, is studied. the network has one management station that maintains many network el...
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ISBN:
(纸本)9780889867048
An optimal mobile agent moving policy for a mobile agent network where a single mobile agent moves and collects management information, is studied. the network has one management station that maintains many network elements each of which generates the management information (e.g., the updated state of the element). We formulate this network model as a semi-Markov decision process (SMDP) and compute an optimal policy with a policy iteration algorithm. It is shown that an optimal mobile agent moving policy achieved by the policy iteration algorithm has a cost reduction effect for the network in comparison to a heuristic policy.
the co-operation of parallel simulated annealing processes to solve the vehicle routing problem with time windows (VRPTW) is considered. the objective is to investigate how the number of parallel processes and the fre...
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ISBN:
(纸本)9780889866386
the co-operation of parallel simulated annealing processes to solve the vehicle routing problem with time windows (VRPTW) is considered. the objective is to investigate how the number of parallel processes and the frequency of processes co-operation influence the accuracy of solutions to the VRPTW. the accuracy of solutions is measured by their proximity to the best known solution.
In this paper, we present a new method of static load balancing for parallel mining of all frequent itemsets on a distributed-memory (DM) parallel machine. the method partitions the space of all frequent itemsets into...
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ISBN:
(纸本)9780889866386
In this paper, we present a new method of static load balancing for parallel mining of all frequent itemsets on a distributed-memory (DM) parallel machine. the method partitions the space of all frequent itemsets into subspaces of approximately the same size. Hence, it allows to balance the computational load for an arbitrary frequent itemset mining algorithm.
Large-scale graph problems are becoming increasingly important in science and engineering. the irregular, sparse instances are especially challenging to solve on cache-based architectures as they are known to incur er...
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ISBN:
(纸本)9780889867048
Large-scale graph problems are becoming increasingly important in science and engineering. the irregular, sparse instances are especially challenging to solve on cache-based architectures as they are known to incur erratic memory access patterns. Yet many of the algorithms also exhibit some degree of regularity with memory accesses. It is important to characterize the locality behavior in order to bridge the gap between algorithm and architecture. In our study we quantify the locality of several fundamental graph algorithms, both sequential and parallel, and correlate our observations withthe algorithmic design. Our study of locality behavior brings insight into the impact of different cache architectures on the performance of both sequential and parallel graph algorithms.
the severe energy constraints of wireless sensor networks (WSNs) require energy-efficient communication protocols in order to fulfill the objectives of the application. Cross-layer design is a technique which can pote...
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ISBN:
(纸本)9780889867048
the severe energy constraints of wireless sensor networks (WSNs) require energy-efficient communication protocols in order to fulfill the objectives of the application. Cross-layer design is a technique which can potentially be used to improve the overall performance of WSNs by way of jointly optimizing and exploiting the interactions between various layers of the network protocol stack. In this paper, we propose a cross-layer framework design for the Embedded Middleware in Mobility Applications (EMMA) project. this optimization agent based framework design provides efficient data exchange between the various protocols layers via a state repository to improve the performance of WSN applications in terms of memory consumption and processing overhead.
Graph Partitioning has several important applications in Computer Science, including VLSI circuit layout, image processing, and distributing workloads for parallel computation. It is known to be NP-hard. In this paper...
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ISBN:
(纸本)9780889867048
Graph Partitioning has several important applications in Computer Science, including VLSI circuit layout, image processing, and distributing workloads for parallel computation. It is known to be NP-hard. In this paper we present in detail the K-Graph Partitioning Problem and the Dynamic distributed Double Guided Genetic Algorithm. this algorithm consists of agents dynamically created and cooperated in order to solve the problem. Each agent performs its own genetic algorithm, guided by the min-conflict-heuristic. the paper also presents the results of application the algorithm for the $K$-Graph Partitioning Problem using a multilevel paradigm.
To keep up withthe pace of fast development of Internet, cluster architecture has been proposed for next generation core routers. In a cluster router, parallel computation is expected. computing shortest path tree (S...
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ISBN:
(纸本)9780889866386
To keep up withthe pace of fast development of Internet, cluster architecture has been proposed for next generation core routers. In a cluster router, parallel computation is expected. computing shortest path tree (SPT) is a fundamental problem implementing OSPF, which is one of the most popular routing protocols. this paper presents a parallel algorithm BPA (Branching parallel Algorithm) for computing SPT, analyzes the performance of BPA, and finally validates the BPA performance by experiments
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