Open AccessMulti-User Concurrent Job Scheduling Method of Network Analysis Application Based on CPU/GPU Cluster
Author(s) -
Yimo Luo,
Jing Li,
Jun Lu,
Ziming Guo,
Bo Yan,
Ning Weng
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/677/4/042092
Subject(s) - computer science , cpu shielding , central processing unit , parallel computing , scheduling (production processes) , job scheduler , distributed computing , operating system , cloud computing , operations management , economics
Multi-channel multi-core CPU parallel and CPU+GPU heterogeneous parallel are effective means to enhance Network Analysis Application computing. To solve the job scheduling problem of Network Analysis Application with multi-level dispatching, multi-user, multi-task in CPU/GPU heterogeneous cluster environment, a multi-user concurrent job scheduling method for Network Analysis Application in CPU/GPU cluster is proposed. According to the characteristics of Network Analysis Application, it is suggested that state estimation and dispatcher power flow should be accelerated in parallel with CPU, while static security analysis, perturbation power flow calculation and interruption capacity scanning should be accelerated in parallel with CPU+GPU. The job scheduling method proposed in this paper can satisfy the high concurrent requests of multi-level Dispatching & Control Center in the isomorphic and heterogeneous computing environments.