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ALS 2000 Abstract
The Portable Batch Scheduler and the Maui Scheduler on Linux Clusters
Brett Bode, David M. Halstead, Ricky Kendall, and Zhou Lei, Ames Laboratory
Abstract
The motivation for a stable, efficient, backfill scheduler that runs in a consistent manner on multiple hardware platforms and
operating systems is outlined and justified in this work. The combination of the Maui Scheduler and the Portable Batch System
(PBS), are evaluated on several cluster solutions of various size, performance and communications profiles. The total job throughput
is simulated in this work, with particular attention given to maximizing resource utilization and to the execution of large parallel
jobs.
With the ever increasing size of cluster computers, and the associated demand for a production quality shared resource management system,
the need for a policy based, parallel aware, batch scheduler is beyond dispute. To this end the combination of a stable, portable resource
management system, coupled to a flexible, extensible, scheduling policy engine will be presented and evaluated in this work. Features, such
as extensive advanced reservation, dynamic prioritization, aggressive backfill, consumable resource tracking and multiple fairness policies,
will be defined and illustrated on commodity component cluster systems. The increase in machine utilization and operational flexibility will
be demonstrated for a non-trivial set of resource requests over a range of duration, and processor count tasks.
We will use the term large to describe jobs that require a substantial portion (50%) of the available CPU resources of a parallel machine.
The duration of a job, is considered to be independent of its resource request, and for the purposes of this paper the term long will be used to
identify jobs with an extended runtime of multiple hours. The opposite terms of small and short will be used for the converse categories of
jobs respectively.
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