Balbir Singh wrote:
Peter Williams wrote:
Balbir Singh wrote:
Peter Williams wrote:
Balbir Singh wrote:
Peter Williams wrote:
<snip>
Is it possible that the effective tasks
is greater than the limit of the group?
Yes.
How do we handle this scenario?
You've got the problem back to front. If the number of effective
tasks is less than the group limit then you have the situation that
needs special handling (not the other way around). I.e. if the
number of effective tasks is less than the group limit then
(strictly speaking) there's no need to do any capping at all as the
demand is less than the limit. However, in the case where the group
limit is less than one CPU (i.e. less than 1000) the recommended
thing to do would be set the limit of each task in the group to the
group limit.
Obviously, group limits can be greater than one CPU (i.e. 1000).
The number of CPUs on the system also needs to be taken into account
for group capping as if the group cap is greater than the number of
CPUs there's no way it can be exceeded and tasks in this group would
not need any processing.
What if we have a group limit of 100 (out of 1000) and 150 effective
tasks in
the group? How do you calculate the cap of each task?
Personally I'd round up to 1 :-) but rounding down to zero is also an
option. The reason I'd opt for 1 is that a zero cap has a special
meaning i.e. background.
I hope my understanding of effective tasks is correct.
Yes, but I think that you fail to realize that this problem (a lower
limit to what caps can be enforced) exists for any mechanism due to
the fact we're stuck with discrete mathematics in computers. This
includes floating point representations of numbers which are just
crude (discrete maths) approximations of real numbers.
I do appreciate and realize the problem, thats why I asked the question.
There are some ways of solving this problem (that I could think about)
1. Keep a whole number and fraction pair and increment the fraction until
it reaches a whole number and then schedule the task when the whole
number value reaches a minimal threshold. Or provide tasks with some
minimal whole number ticks in advance and then do not schedule them
again till their fractions add up to the whole number (credit system).
For example if T1 and T2 have a cap of 0.5%. Then represent the values
as whole number zero and fraction represented as 1 and divisor as 2.
Every two ticks their whole number would become 1 and fraction 0,
divisor 2.
Schedule the tasks for a tick whenever its whole number becomes 1
and reset then its whole number to 0.
You're over engineering and you're not solving the problem. You're just
moving it down a bit.
2. In a group based cap management system, schedule some tasks (highest
priority)
until their cap run out. In the subsequent rounds pick and choose
tasks that
did not get a chance to run earlier.
Solving this is indeed a interesting problem.
Once again, you're over engineering and probably making the problem worse.
Peter
--
Peter Williams [email protected]
"Learning, n. The kind of ignorance distinguishing the studious."
-- Ambrose Bierce
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