SchedP: I/O-aware Job Scheduling in Large-Scale Production HPC Systems
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-21395-3_29
Reference11 articles.
1. Ahn, D.H., Garlick, J., Grondona, M., Lipari, D., Springmeyer, B., Schulz, M.: Flux: a next-generation resource management framework for large HPC centers. In: 2014 43rd International Conference on Parallel Processing Workshops, pp. 9–17. IEEE (2014)
2. Fan, Y.: Job scheduling in high performance computing. arXiv preprint arXiv:2109.09269 (2021)
3. Herbein, S., et al.: Scalable I/O-aware job scheduling for burst buffer enabled HPC clusters. In: Proceedings of the 25th ACM International Symposium on High-Performance Parallel and Distributed Computing, pp. 69–80 (2016)
4. Li, D., Dong, M., Tang, Y., Ota, K.: A novel disk I/O scheduling framework of virtualized storage system. Clust. Comput. 22(1), 2395–2405 (2019)
5. Li, H., Liao, J., Liu, X.: Merging and prioritizing optimization in block I/O scheduling of disk storage. J. Circ. Syst. Comput. 30(10), 2150186 (2021)
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