An empirical study of SDN-accelerated HPC infrastructure for scientific research

Susumu Date
Hirotake Abe
Dashdavaa Khureltulga
Keichi Takahashi
Yoshiyuki Kido
Yasuhiro Watashiba
Pongsakorn U-Chupala
Kohei Ichikawa
Hiroaki Yamanaka
Eiji Kawai
Shinji Shimojo

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.

Proceedings - 2015 International Conference on Cloud Computing Research and Innovation, ICCCRI 2015

Institute of Electrical and Electronics Engineers Inc.

89

96

10.1109/ICCCRI.2015.13

https://doi.org/10.1109/ICCCRI.2015.13
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