Search Results - parallel program clustering algorithms~
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A Community-Based Fault Isolation Approach for Effective Simultaneous Localization of Faults
Published 2019“…In an ideal case, faults are isolated into fault-focused clusters, each targeting a single fault for developers to localize them simultaneously in parallel. …”
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Parallel matrix-multiplication algorithm on network of workstations
Published 2004“…We present the comparison in terms of speed between serial algorithm and the parallel algorithm when we run them on our cluster. …”
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Investigation on the dynamic of computation of semi autonomous evolutionary computation for syntactic optimization of a set of programming codes
Published 2007“…In parallel programming, the challenges in optimizing the codes in general are more than that for serial programming. …”
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Effective software fault localization based on complex network theory / Abubakar Zakari
Published 2019“…In the case where a developer has checked 70% of the program statements and cannot fully localize all the multiple faults in a single diagnosis rank list, rather than resorting to using OBA bugging approach, a newly proposed community-based fault isolation approach that makes use of a divisive network community clustering algorithm is applied to aid in isolating faults into different fault-focused communities (clusters), each targeting a single fault. …”
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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
Published 2009“…The development of this architecture is based on several programming language as it involves algorithm implementation on C, parallelization using Parallel Virtual Machine (PVM) and Java for web services development. …”
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Parallel Implementation of Two Level Barotropic Models Applied to the Weather Prediction Problem
Published 2004“…Then the parallel algorithms are constructed and run using the Beowulf Cluster machine. …”
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K Nearest Neighbor Joins And Mapreduce Process Enforcement For The Cluster Of Data Sets In Bigdata
Published 2018“…K Nearest Neighbor Joins (KNN join) are regarded as highly primitive and expensive operations in the data mining.The efficient use of KNN join has proven good results in finding the objects from two data sets prevailed in the huge databases.This has been achieved with the combination of K-Nearest Neighbor query and join operation to find the distinct objects from different data sets.MapReduce is a newly introduced program with the combination of Map Procedure method and Reduce Method widely used in BigData.MapReduce is enriched with parallel distributed algorithm to find the results on a cluster of data sets in BigData.In this paper,the combination of KNN join and MapReduce methods are utilized on the cluster of data sets in BigData for knowledge discovery.Exploring the pinpoint data from huge data sets stored in Big Data demands the distributed large scale data processing.The present research paper is focusing on generic steps for KNN joins exploration operations on MapReduce.The operations of KNN Join are targeted to perform the data partitioning and data pre-processing and necessary calculations.By utilizing the combination of KNN joins with MapReduce methods on BigData data sets will demonstrate a solution for complex computational analysis. …”
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Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system
Published 2011“…The PLSR architecture model, workflow and algorithms are described. The PLSR has been developed using Java Programming language. …”
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