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Calculation of CPU performance, power and cost using Hadoop

机译:使用Hadoop计算CPU性能,功率和成本

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Technology is progressing at a fast pace, and it is the need of the hour to scrutinize big data workloads on cloud computing. The requisite of working with large data sets and more secure platforms gives rise to the necessity of analyzing techniques and tools regarding performance and power consumption. One of the most frequently used big data cloud computing framework is Hadoop. Hadoop - an open source implementation of MapReduce - is employed for processing big data, while handling extensive workload applications for several purposes. The performance, cost and power estimations of underlying processors on Hadoop can be done by characterizing different workloads on Hadoop framework. A comprehensive study is carried out to calculate CPU performance, cost and power consumption regarding different workloads, so as to facilitate efficient usage of different processors to deal with various workloads according to the user requirements.
机译:技术正在快速进步,需要时刻审查云计算上的大数据工作负载。使用大数据集和更安全平台的必要性引起了分析了关于性能和功耗的技术和工具的必要性。其中一个最常用的大数据云计算框架是Hadoop。 Hadoop - MapReduce的开源实现 - 用于处理大数据,同时处理多种目的的广泛工作负载应用程序。通过在Hadoop框架上表征不同的工作负载来完成Hadoop上的底层处理器的性能,成本和功率估计。进行全面的研究以计算有关不同工作负载的CPU性能,成本和功耗,以便于根据用户要求提供不同处理器的有效使用来处理各种工作负载。

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