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Simulation Runner: A Cloud-Based Parallel and Distributed HPC Platform

机译:Simulation Runner:基于云的并行和分布式HPC平台

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Scientific workloads often require scalable computing resources. The traditional HPC paradigm provides large scale computing resources but requires IT specialists to buy and maintain large computer infrastructure in their organization. With the emergence of cloud computing, more and more scientists and engineers are moving their computing workloads from local clusters to public cloud. However, such a migration often requires experience both in understanding cloud architecture and cloud development skills, which can impede the efficiency and success of migration. This paper presents a cloud-based parallel and distributed computing platform to support scientific computing. With the Simulation Runner, scientists only need to submit their embarrassingly parallel scientific applications with appropriate arguments or parameters. There is no need to rebuild migrate cloud applications or purchase large computer infrastructures by themselves. The system also uses a file caching mechanism to improve performance and reduce the costs of data-intensive computing tasks. A 44X speedup was resulted from using 128 computing instances compared with premise high performance desktop computers. A comparison study on the performance of file cache is given at the end of the paper.
机译:科学工作负载通常需要可伸缩的计算资源。传统的HPC范例提供了大规模的计算资源,但需要IT专家在其组织中购买和维护大型计算机基础结构。随着云计算的出现,越来越多的科学家和工程师将其计算工作负载从本地集群转移到公共云。但是,这样的迁移通常需要了解云架构和云开发技能的经验,这可能会阻碍迁移的效率和成功。本文提出了一种基于云的并行和分布式计算平台,以支持科学计算。借助Simulation Runner,科学家仅需提交具有适当参数或参数的令人尴尬的并行科学应用程序即可。无需重建迁移的云应用程序或自行购买大型计算机基础架构。该系统还使用文件缓存机制来提高性能并降低数据密集型计算任务的成本。与使用高性能台式机相比,使用128个计算实例使速度提高了44倍。最后,对文件缓存的性能进行了比较研究。

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