TY - GEN
T1 - An empirical study of SDN-accelerated HPC infrastructure for scientific research
AU - Date, Susumu
AU - Abe, Hirotake
AU - Khureltulga, Dashdavaa
AU - Takahashi, Keichi
AU - Kido, Yoshiyuki
AU - Watashiba, Yasuhiro
AU - U-Chupala, Pongsakorn
AU - Ichikawa, Kohei
AU - Yamanaka, Hiroaki
AU - Kawai, Eiji
AU - Shimojo, Shinji
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2016/2/26
Y1 - 2016/2/26
N2 - 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.
AB - 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.
KW - Job management system
KW - MPI
KW - On-demand cloud formation
KW - Remote visualization
KW - SDN
UR - http://www.scopus.com/inward/record.url?scp=84964878548&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84964878548&partnerID=8YFLogxK
U2 - 10.1109/ICCCRI.2015.13
DO - 10.1109/ICCCRI.2015.13
M3 - Conference contribution
AN - SCOPUS:84964878548
T3 - Proceedings - 2015 International Conference on Cloud Computing Research and Innovation, ICCCRI 2015
SP - 89
EP - 96
BT - Proceedings - 2015 International Conference on Cloud Computing Research and Innovation, ICCCRI 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd International Conference on Cloud Computing Research and Innovation, ICCCRI 2015
Y2 - 26 October 2015 through 27 October 2015
ER -