For example, a job may request 20 processors and 5 MatLab licenses. The scheduler must be able to co-schedule these resources and the resource manager must be able to properly adjust access control for these resources. As these clusters continue to grow in size and functionality, it is becoming nearly impossible to monitor resource or workload state using a text based state display. Not only are the numbers of jobs and nodes increasing, but the amount of information associated with the state of each node and job is growing as well. Statistics Collection Bigger resources mean more management.
Management requires statistics.
This will be an issue as soon as it is supported on Linux. As the complexity of these systems has grown, the ability to estimate the effect of even a simple change on the system has been lost. The scheduler is able to collect both resource and workload traces. It can then run either a historical or artificial workload on the actual resources or on an imaginary system configured in whatever manner desired. Test mode allows the administator to watch what the scheduler would do on the actual system without any actual impact on the system.