FRINK Linked Data Fragments server

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• W2405371566 abstract "As the growth of cluster scale, huge power consumption will be a major bottleneck for future large-scale high performance cluster. However, most existing cloud-clusters are based on power-hungry X86-64 which merely aims to common enterprise applications. In this paper, we improve the cluster performance by leveraging ARM SoCs which feature energy-efficient. In our prototype, cluster with five Cubieboard4, we run HPL and achieve 9.025 GFLOPS which exhibits a great computational potential. Moreover, we build our measurement model and conduct extensive evaluation by comparing the performance of the cluster with WordCount, k-Means (etc.) running in Map-Reduce mode and Spark mode respectively. The experiment results demonstrate that our cluster can guarantee higher computational efficiency on compute-intensive utilities with the RDD feature of Spark. Finally, we propose a more suitable theoretical hybrid architecture of future cloud clusters with a stronger master and customized ARMv8 based TaskTrackers for data-intensive computing." @default.
• W2405371566 created "2016-06-24" @default.
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• W2405371566 date "2016-01-01" @default.
• W2405371566 modified "2023-10-06" @default.
• W2405371566 title "An ARM-Based Hadoop Performance Evaluation Platform: Design and Implementation" @default.
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• W2405371566 doi "https://doi.org/10.1007/978-3-319-28910-6_8" @default.
• W2405371566 hasPublicationYear "2016" @default.
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