Maui Scheduler

A.3  Case Study: Background Load


A 64 proc Altix system needs to be scheduled with a significant 'background' load.



Range in size from 1 to 32 processors
Jobs range in length from 15 minutes to 48 hours
This is a login/development machine.  At any given time, there may be a significant load from jobs and processes outside of the resource manager's view or control.  The major impact of this load related to scheduling is in the area of cpu load and real memory consumption.


The scheduler must run the machine at maximum capacity without overcommitting either memory or processors.  A significant, variable background load exists from jobs submitted outside of the resource manager's view or control.  The scheduler must track and account for this load and allow space for some variability and growth of this load over time.  The scheduler should also kill any job which violates its requested resource allocation and notify the associated user of this violation.

The scheduler should maximize the throughput associated with the queued jobs while avoiding starvation as a secondary concern. 


The background load causes many problems in any mixed batch/interactive environment.  One problem is that a situation may arise in which the highest priority batch job cannot run.  Moab can make a reservation for this highest priority job.  But because there are no constraints on the background load, Moab cannot determine when it will drop enough to allow this job to run.  By default, it optimistically attempts a reservation for the next scheduling iteration, perhaps 1 minute out. 

The problem is that this reservation now exists one minute out and when Moab attempts to backfill, it can only consider jobs which request less than one minute or which can fit "beside" this high priority job.  During the next iteration, Moab still cannot run the job because the background load has not dropped and again creates a new reservation for one minute into the future. 

The background load has basically turned batch scheduling into an exercise in "resource scavenging."  If the priority job reservation was not there, other smaller queued jobs might be able to run.  Therefore, to maximize the "scavenging" effect, the scheduler should be configured to allow this high priority job the first opportunity to use available resources but prevent it from reserving these resources if it cannot run immediately. 


The configuration needs to accomplish several main objectives including:

  • track the background load to prevent oversubscription
  • favor small, short jobs to maximize job turnaround
  • prevent blocked high priority jobs from creating reservations
  • work with an allocation manager to charge for utilized CPU time
  • cancel jobs which exceed specified resource limits
  • notify users when a job is canceled due to resource usage limit violations
# allow jobs to share node

# track background load

# favor short jobs, disfavor large jobs
RESOURCEWEIGHT             -10
PROCWEIGHT                 128
MEMWEIGHT                  1
XFACTOR                    1000

# disable priority reservations for the default QOS

# debit by CPU
BANKTYPE                   QBANK
BANKSERVER                 develop1
BANKPORT                   2334

# kill resource hogs

# notify user of job events
NOTIFYSCRIPT               tools/


The most difficult aspects of this environment are properly reserving space for the untracked background load.  Since this load is outside the control of the scheduler and resource manager, it has no constraints.  It could grow suddenly and overwhelm the machine, or just as easily disappear.  The NODEUNTRACKEDLOADFACTOR parameter provides slack for this background load to grow and shrink.  However, since there is no control over the load, the effectiveness of this parameter will depend on the statistical behavior of the load.  The greater the value, the more slack provided, and the less likely the system is to be overcommitted.  However, a larger value also means more resources are in this reserve which are not available for scheduling. 

The second aspect of this environment which must be monitored is the trade-off between high job throughput and job starvation.  The 'locally greedy' approach of favoring the smallest, shortest jobs will have a negative effect on larger and longer jobs.  The large, long jobs which have been queued for some time can be pushed to the front of the queue by increasing the QUEUETIMEWEIGHT factor until a satisfactory balance is achieved. 


The right solution is to migrate the users over to the batch system or provide them with a constrained resource 'box' to play in, either through a processor partition, standing reservation, or a logical software system.  The value in this is that it prevents this unpredictable background load from wreaking havoc with a dedicated resource reservation system. 

Moab can reserve resources for jobs according to all currently available information.  However, the unpredictable nature of the background load means that those resources may not be available when they should be, which result in canceled reservations and hinder enforcement of site policies and priorities.