Self-Adaptive Scheduler Parameterization via Online Simulation

High-end parallel systems present a tremendous research challenge on how to best allocate their resources to match dynamic workload characteristics and user habits that are often unique to each system. Although thoroughly investigated, job scheduling for production systems remains an inexact science, requiring significant experience and intuition from system administrators to properly configure batch schedulers. State-of-theart schedulers provide many parameters for their configuration, but tuning these to optimize performance and to appropriately respond to the continuously varying characteristics of the workloads can be very difficult — the effects of different parameters and their interactions are often unintuitive. In this paper, we introduce a new and general methodology for automating the difficult process of job scheduler parameterization. Our proposed methodology is based on online simulations of a model of the actual system to provide on-the-fly suggestions to the sch...

• Type: Conference
• Year: 2005
• Where: IPPS
• Authors: Barry Lawson, Evgenia Smirni
• Keywords: Distributed And Parallel Computing, Dynamic Workload Characteristics, IPPS 2005, Job Scheduler Parameterization, Scheduler Parameterization