Tardis scheduling policy
We appear to need to take another look at tardis's scheduling policy. Greg and Catherine would like everyone to agree on a policy and then give it a reasonable trial before starting to tweak it again, so whatever we come up with we'd like to stick with until January 2009 at the earliest.
Current policy
Priority
This determines what order Idle jobs are on the queue. Type 'showq' to see the sorted queue.
Priority is currently: 20 * ( personal fairshare result + group fairshare result ) + job expansion factor .
Every individual user has a fairshare target of 20% of the machine. If you go over that usage then your fairshare result is negative; under it and it's positive. Everyone is also in one of four groups of users which have group fairshare targets. These are based on how the machine was funded: the 'stuart' group (Stuart Althorpe's research group) gets 38%, the 'michiel' group (Michiel Sprik) gets 20% (this includes their share of the Portfolio funding), the 'jochen' group (Jochen Blumberger) gets 14% and the 'portfolio' group (everyone else) gets 28%. Your group and your personal result are added, so other people in your group can make your fairshare negative by running lots of jobs.
Fairshare targets and usage can be seen by running 'diagnose -f'. The research group targets as labelled as QOS targets rather than group targets- this is a technical consequence of the way we set the system up. 'group' to Maui means 'Unix group' not 'research group'.
The fairshare calculation works on 48-hour slots (the longest queue is 48 hours) and uses the last ten. Older slots count for less than recent ones.
Job expansion factor rises with time spent on the queue, but rises faster for short jobs. The reason for using that and not basic queue time is that it helps the very short (30 min) test jobs to run. It makes practically no difference when compared to the fairshare numbers, but ensures that every job eventually runs.
Priority calculations for all queued jobs can be seen by running 'diagnose -p'
Throttling policies
There is one throttling policy in use: any user may only have four jobs in the 'Idle' state at any given time. This avoids queue stuffing. However it does not help when one person has a very big fairshare bonus and submits a lot of jobs, because every job that gets to run is replaced in the queue immediately.
Reservation and Backfill
The system makes a reservation for the top queued job and then backfills other jobs around that (ie lets them jump the queue if and only if they will not have any effect on the start time of the top queued job). This stops big parallel jobs being crowded out by small jobs, but only once they have got to the top of the queue. Without this the 64 proc jobs would almost never run.
Node groups
We force multinode jobs to run on a set of nodes that are all attached to the same Infiniband switch. This can cause very large jobs (64 and 32-way) to take a long time to start because the system has to clear most of a switch for them. Other jobs may appear to jump the queue in this situation but if you check then those jobs will be being started on switches other than the one the system has picked for the top job. The system picks the optimum switch for the top job, ie the one where the job can start soonest if all the other jobs in the system run to their maximum walltime. The calculation is redone each time the system state changes.
The current problem
32 and 64-way jobs are taking a very long time to start even with the above system.
I think the problem is this: one of these jobs reaches the top of the queue and the system books it a reservation and starts clearing space for it, but then a small, higher-priority job comes along and the top job loses its reservation. The small job takes some of the space. The system can't start the large job so it backfills the rest of the queue into what space is left. Once the small job starts the large job is top but has to start clearing space to run in all over again...and then another small job comes along.
This is made worse by the tendency of groups which run small jobs to be under their fairshare target and the large job groups to be over.
Things we could change and their likely effects
- Increase the reservation depth to 2 or 3, causing the system to make reservations for the top 2 or 3 queued jobs, not just the top one. This will reduce overall utilization but on average help larger jobs because they won't keep losing their reservations. Small jobs tend to run fast enough that reservations are not an issue for them.
- Give a straight priority boost to large jobs to try to keep them at the top of the queue. More complex to configure. Would need to decide how much is enough and define a 'large job'.
Please add any comments below. I'd like to get any changes agreed by 24th September.
--Catherine 14:04, 10 September 2008 (BST)
Increasing the reservation depth to 3 sounds the easiest thing to do first. We can see how that works. If this reduces the overall usage too much we can reduce it to 2. Chris