On Identifying User Session Boundaries in Parallel Workload Logs
The stream of jobs submitted to a parallel supercomputer is actually the interleaving of many streams from different users, each of which is composed of sessions. Identifying and characterizing the sessions is important in the context of workload modeling, especially if a user-based workload model is considered. Traditionally, sessions have been delimited by long think times, that is, by intervals of more than, say, 20 minutes from the termination of one job to the submittal of the next job. We show that such a definition is problematic in this context, because jobs may be extremely long. As a result of including each job’s execution in the session, we may get unrealistically long sessions, and indeed, users most probably do not always stay connected and wait for the termination of long jobs. We therefore suggest that sessions be identified based on proven user activity, namely the submittal of new jobs, regardless of how long they run.
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