Research on license management for CAE software resources shared across multiple slurm clusters

Parallel simulation tasks of computer-aided engineering (CAE) require software licenses when running on parallel computing clusters. However, most existing license management software lacks interfaces to interact with cluster scheduling systems. In the context of multiple Slurm clusters, the job scheduler of each cluster cannot obtain real-time information on available license counts from the license server, and the same software license is assigned to multiple jobs, resulting in abnormal job execution. The paper proposes a license management model called PMLP, which is designed to enable sharing of a software license resource repository among multiple Slurm clusters. PMLP can monitor the license server port and parse the logs of the license management software to obtain real-time information on available licenses and synchronize it across all clusters. Experimental results using a historical job dataset from a parallel computing center show that compared with the proportional allocation of licenses to each cluster, the average utilization of licenses is improved by 18.47%. Compared with the scheme of synchronizing usage information from the license server through periodic polling, the proportion of abnormal jobs is reduced by 4.76%.