An Empirical Study of SDN-accelerated HPC Infrastructure for Scientific Research
An Empirical Study of SDN-accelerated HPC Infrastructure for Scientific Research
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DOI：
10.1109/icccri.2015.13
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发表时间：
2015-10
期刊：
影响因子：
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通讯作者：
S. Date;H. Abe;Khureltulga Dashdavaa;Keichi Takahashi;Y. Kido;Yasuhiro Watashiba;Pongsakorn U-chupala;Koheix Ichikawa;Hiroaki Yamanaka;Eiji Kawai;S. Shimojo
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文献类型：
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作者：
S. Date;H. Abe;Khureltulga Dashdavaa;Keichi Takahashi;Y. Kido;Yasuhiro Watashiba;Pongsakorn U-chupala;Koheix Ichikawa;Hiroaki Yamanaka;Eiji Kawai;S. Shimojo
大型科学应用需要高性能计算，因为需要分析的扩散和大量科学数据是一个严重的问题。传统上，通常认为网络资源是静态资源用户无法控制需求的静态资源。通过将网络的可编程性整合到科学工作流的每个阶段，本研究探讨了下一代高性能计算基础架构，在该基础架构中，计算和网络资源都会根据科学应用的资源要求灵活地切成薄片，并有效地利用。从技术上讲，软件定义的网络已被用作为此目的的关键技术。在本文中，引入了下一代高性能计算基础架构的概念和目标，并讨论了我们研究的当前状态。
High performance computing is required for Big Science application because the proliferation and huge amount of scientific data that needs to be analyzed is a serious problem. Traditionally, network resources were generally assumed as a static resource users cannot control on demand. By integrating network programmability to every stage of a scientific workflow, this study explores a next-generation high performance computing infrastructure where both computational and network resources are flexibly sliced and efficiently leveraged based on the resource requirements of the scientific applications. Technically, Software Defined Networking has been adopted as a key technology for this purpose. In this paper the concept and goals of a next-generation high performance computing infrastructure is introduced and the current status of our research is discussed.