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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和仿真

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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且灵活的方案,以按需付费模式开发,运行和测试不同的应用程序。但是,对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,在云计算环境中使用诸如FPGA之类的高能效资源成为当今行业和学术界的热门研究课题。有效利用此类资源可以通过在满足更多客户请求的同时以最少的资源集满足他们的要求,从而提高云提供商所获得的利润。在本文中,我们主要针对FPGA考察了用于管理异构资源的体系结构框架和算法。基于该架构,提供了一种仿真工具,用于研究扩展系统中FPGA数量对性能和能耗的影响。该工具基于处理时间和能耗的统计模型。可扩展性研究表明,增加FPGA的数量可以将能耗降低40%,同时还可以将多达35%的请求接受到系统中。 (C)2017 Elsevier B.V.保留所有权利。

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