TY - GEN
T1 - A Software Licenses Aware Job Scheduling and Management Approach on Multi-clusters
AU - Hou, Zhengxiong
AU - Gu, Jianhua
AU - Zhou, Xingshe
AU - Zhao, Tianhai
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/7/14
Y1 - 2017/7/14
N2 - For commercial software in scientific and engineering computing, software licenses are needed when running them in high performance computing systems. Usually, there is a constraint for the number of software licenses. With the traditional software licenses management approaches, there is a prominent issue. The jobs will fail immediately without available software licenses. However, the existing job scheduling mechanisms mainly focus on hardware resources allocation. In this paper, we propose a software licenses aware job scheduling and management approach on multi-clusters, which is a common scenario for current high performance computing community. Based on floating licenses and scheduling policies, the submitted jobs from multi-clusters requiring software licenses will be uniformly queued and scheduled. A co-scheduling mechanism is provided for the software licenses and hardware resources. So software and limited licenses can be shared and used efficiently on multiclusters. We implemented and evaluated the approach in a real multi-clusters computing environment.
AB - For commercial software in scientific and engineering computing, software licenses are needed when running them in high performance computing systems. Usually, there is a constraint for the number of software licenses. With the traditional software licenses management approaches, there is a prominent issue. The jobs will fail immediately without available software licenses. However, the existing job scheduling mechanisms mainly focus on hardware resources allocation. In this paper, we propose a software licenses aware job scheduling and management approach on multi-clusters, which is a common scenario for current high performance computing community. Based on floating licenses and scheduling policies, the submitted jobs from multi-clusters requiring software licenses will be uniformly queued and scheduled. A co-scheduling mechanism is provided for the software licenses and hardware resources. So software and limited licenses can be shared and used efficiently on multiclusters. We implemented and evaluated the approach in a real multi-clusters computing environment.
KW - job scheduling
KW - multi-clusters
KW - resource management
KW - software licenses
UR - https://www.scopus.com/pages/publications/85026629776
U2 - 10.1109/CSE-EUC-DCABES.2016.265
DO - 10.1109/CSE-EUC-DCABES.2016.265
M3 - 会议稿件
AN - SCOPUS:85026629776
T3 - Proceedings - 19th IEEE International Conference on Computational Science and Engineering, 14th IEEE International Conference on Embedded and Ubiquitous Computing and 15th International Symposium on Distributed Computing and Applications to Business, Engineering and Science, CSE-EUC-DCABES 2016
SP - 706
EP - 711
BT - Proceedings - 19th IEEE International Conference on Computational Science and Engineering, 14th IEEE International Conference on Embedded and Ubiquitous Computing and 15th International Symposium on Distributed Computing and Applications to Business, Engineering and Science, CSE-EUC-DCABES 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 19th IEEE International Conference on Computational Science and Engineering, 14th IEEE International Conference on Embedded and Ubiquitous Computing and 15th International Symposium on Distributed Computing and Applications to Business, Engineering and Science, CSE-EUC-DCABES 2016
Y2 - 24 August 2016 through 26 August 2016
ER -