Optimizing Job Coscheduling by Adaptive Deadlock-Free Scheduler

• Published in: Mathematical problems in engineering Vol. 2018; no. 2018; pp. 1 - 18
• Main Authors: Guo, Jing, Zhou, Naqin, Wang, Xinyang, Yu, Mincong, Qi, Deyu, Zheng, Zhishuo, Shen, Yang
• Format: Journal Article
• Language: English
• Published: Cairo, Egypt Hindawi Publishing Corporation 01.01.2018; Hindawi; Hindawi Limited
• Subjects: Adaptive control; Architectural engineering; Automatic control; Big Data; Computer centers; Computer simulation; Concurrency control; Distributed processing; Efficiency; Employment; International conferences; Logic; Mathematical problems; Operating systems; Performance degradation; Resource scheduling; Scheduling; Supercomputers; Workloads
• ISSN: 1024-123X; 1563-5147
• DOI: 10.1155/2018/1438792

It is ubiquitous that multiple jobs coexist on the same machine, because tens or hundreds of cores are able to reside on the same chip. To run multiple jobs efficiently, the schedulers should provide flexible scheduling logic. Besides, corunning jobs may compete for the shared resources, which may lead to performance degradation. While many scheduling algorithms have been proposed for supporting different scheduling logic schemes and alleviating this contention, job coscheduling without performance degradation on the same machine remains a challenging problem. In this paper, we propose a novel adaptive deadlock-free scheduler, which provides flexible scheduling logic schemes and adopts optimistic lock control mechanism to coordinate resource competition among corunning jobs. This scheduler exposes all underlying resource information to corunning jobs and gives them necessary utensils to make use of that information to compete resource in a free-for-all manner. To further relieve performance degradation of coscheduling, this scheduler enables the automated control over the number of active utensils when frequent conflict becomes the performance bottleneck. We justify our adaptive deadlock-free scheduling and present simulation results for synthetic and real-world workloads, in which we compare our proposed scheduler with two prevalent schedulers. It indicates that our proposed approach outperforms the compared schedulers in scheduling efficiency and scalability. Our results also manifest that the adaptive deadlock-free control facilitates significant improvements on the parallelism of node-level scheduling and the performance for workloads.