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Empirical modeling and simulation of an heterogeneous Cloud computing environment

机译:异构云计算环境的经验建模与仿真

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Cloud computing offers users a convenient scalable and flexible scenario for developing, running, and testing different applications in a pay-as-you-go model. However, the increasing demand of computational resources have resulted in more power consumption. In order to address this issue, the use of energy efficient resources such as FPGAs within a Cloud computing environment is nowadays a hot research topic, driven both from industry and academy. The efficient use of this type of resources can lead to increase the profit obtained by Cloud providers by serving more client requests while fulfilling their requirements with the minimum set of resources. In this paper, we survey an architectural framework and algorithms for managing heterogeneous resources, focusing on FPGAs. Based on this architecture, a simulation tool for studying the impact on performance and energy consumption of scaling the number of FPGAs in the system is presented. This tool is based on statistical models of processing time and energy consumption. The scalability study demonstrates that increasing the number of FPGAs can improve energy consumption up to 40%, while also admitting up to 35% more requests into the system. (C) 2017 Elsevier B.V. All rights reserved.
机译:云计算为用户提供了一种方便的可扩展和灵活的方案,可在付费型号中开发,运行和测试不同的应用程序。然而,计算资源的日益增长的需求导致了更多的功耗。为了解决这个问题,现在是一项热门研究主题,在云计算环境中使用诸如FPGA之类的能源有效资源的使用,从工业和学院推动。这种类型的资源的有效使用可以通过在满足最小资源集的情况下提供更多客户端请求来提高云提供商获得的利润。在本文中,我们调查了管理异构资源的架构框架和算法,专注于FPGA。基于此架构,提出了一种用于研究系统中缩放FPGA数量的对性能和能耗的影响的仿真工具。该工具基于处理时间和能量消耗的统计模型。可扩展性研究表明,增加FPGA的数量可以提高能耗高达40%,同时也承认在系统中的要求增加35%。 (c)2017年Elsevier B.V.保留所有权利。

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