It is well known that efficient job scheduling plays a crucial role in achieving high system utilization in large-scale high performance computing environments. A good scheduling algorithm should schedule jobs to achieve high system utilization while satisfying various user demands in an equitable fashion. Designing such a scheduling algorithm is a non-trivial task even in a static environment. In practice, the computing environment and workload are constantly changing. There are several reasons for this. First, the computing platforms constantly evolve as the technology advances. For example, the availability of relatively powerful commodity off-the-shelf (COTS) components at steadily diminishing prices have made it feasible to construct ever larger massively parallel computers in recent years. Second, the workload imposed on the system also changes constantly. The rapidly increasing compute resources have provided many applications developers with the opportunity to radically alter program characteristics and take advantage of these additional resources. New developments in software technology may also trigger changes in user applications. Finally, political climate change may alter user priorities or the mission of the organization.
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