On Wed, 28 Nov 2018 at 16:21, Patrick Bellasi <patrick.bell...@arm.com> wrote: > > On 28-Nov 15:55, Vincent Guittot wrote: > > On Wed, 28 Nov 2018 at 15:40, Patrick Bellasi <patrick.bell...@arm.com> > > wrote: > > > > > > On 28-Nov 14:33, Vincent Guittot wrote: > > > > On Wed, 28 Nov 2018 at 12:53, Patrick Bellasi <patrick.bell...@arm.com> > > > > wrote: > > > > > > > > > > On 28-Nov 11:02, Peter Zijlstra wrote: > > > > > > On Wed, Nov 28, 2018 at 10:54:13AM +0100, Vincent Guittot wrote: > > > > > > > > > > > > > Is there anything else that I should do for these patches ? > > > > > > > > > > > > IIRC, Morten mention they break util_est; Patrick was going to > > > > > > explain. > > > > > > > > > > I guess the problem is that, once we cross the current capacity, > > > > > strictly speaking util_avg does not represent anymore a utilization. > > > > > > > > > > With the new signal this could happen and we end up storing estimated > > > > > utilization samples which will overestimate the task requirements. > > > > > > > > > > We will have a spike in estimated utilization at next wakeup, since we > > > > > use MAX(util_avg@dequeue_time, ewma). Potentially we also inflate the > > > > > EWMA in > > > > > case we collect multiple samples above the current capacity. > > > > > > > > TBH I don't see how it's different from current implementation with a > > > > task that was scheduled on big core and now wakes up on little core. > > > > The util_est is overestimated as well. > > > > > > While running below the capacity of a CPU, either big or LITTLE, we > > > can still measure the actual used bandwidth as long as we have idle > > > time. If the task is then moved into a lower capacity core, I think > > > it's still safe to assume that, likely, it would need more capacity. > > > > > > Why do you say it's the same ? > > > > In the example of a task that runs 39ms in period of 80ms that we used > > during previous version, > > the utilization on the big core will reach 709 so will util_est too > > When the task migrates on little core (512), util_est is higher than > > current cpu capacity > > Right, and what's the problem ?
you worry about an util_est being higher than capacity which is the case there > > 1) We know that PELT is calibrated to 32ms period task and in your > example, since the runtime is higher then the half-life, it's > correct to estimate a utilization higher then 50%. > > PELT utilization is defined _based on the half-life_: thus > your task having a 50% duty cycle does not mean we are not correct > if report a utilization != 50%. > It would be as broken as reporting 10% utilization for a task > running 100ms every 1s. > > 2) If it was a 70% task on a previous activation, once it's moved into > a lower capacity CPU it's still correct to assume that it's likely > going to require the same bandwidth and thus will be > under-provisioned. > > I still don't see where we are wrong in this case :/ > > To me it looks different then the problem I described. > > > > With your new signal instead, once we cross the current capacity, > > > utilization is just not anymore utilization. Thus, IMHO it make sense > > > avoid to accumulate a sample for what we call "estimated utilization". This is not true. With the example above, the util_est will be exactly the same on big and little cores with the new signal > > > > > > I would also say that, with the current implementation which caps > > > utilization to the current capacity, we get better estimation in > > > general. At least we can say with absolute precision: > > > > > > "the task needs _at least_ that amount of capacity". > > > > > > Potentially we can also flag the task as being under-provisioned, in > > > case there was not idle time, and _let a policy_ decide what to do > > > with it and the granted information we have. > > > > > > While, with your new signal, once we are over the current capacity, > > > the "utilization" is just a sort of "random" number at best useful to > > > drive some conclusions about how long the task has been delayed. see my comment above > > > > > > IOW, I fear that we are embedding a policy within a signal which is > > > currently representing something very well defined: how much cpu > > > bandwidth a task used. While, latency/under-provisioning policies > > > perhaps should be better placed somewhere else. > > > > > > Perhaps I've missed it in some of the previous discussions: > > > have we have considered/discussed this signal-vs-policy aspect ? > > What's your opinion on the above instead ? It's not a policy but it gives better knowledge about the amount a work done I have put below discussion on the subject on previous version > > > > With contribution scaling the PELT utilization of a task is a _minimum_ > > utilization. Regardless of where the task is currently/was running (and > > provided that it doesn't change behaviour) its PELT utilization will > > approximate its _minimum_ utilization on an idle 1024 capacity CPU. > > The main drawback is that the _minimum_ utilization depends on the CPU > capacity on which the task runs. The two 25% tasks on a 256 capacity > CPU will have an utilization of 128 as an example > > > > > With time scaling the PELT utilization doesn't really have a meaning on > > its own. It has to be compared to the capacity of the CPU where it > > is/was running to know what the its current PELT utilization means. When > > I would have said the opposite. The utilization of the task will > always reflect the same amount of work that has been already done > whatever the CPU capacity. > In fact, the new scaling mechanism uses the real amount of work that > has been already done to compute the utilization signal which is not > the case currently. This gives more information about the real amount > of worked that has been computed in the over utilization case. > > > the utilization over-shoots the capacity its value is no longer > > represents utilization, it just means that it has a higher compute > > demand than is offered on its current CPU and a high value means that it > > has been suffering longer. It can't be used to predict the actual > > utilization on an idle 1024 capacity any better than contribution scaled > > PELT utilization. > > I think that it provides earlier detection of over utilization and > more accurate signal for a longer time duration which can help the > load balance > Coming back to 50% task example . I will use a 50ms running time > during a 100ms period for the example below to make it easier > > Starting from 0, the evolution of the utilization is: > > With contribution scaling: > time 0ms 50ms 100ms 150ms 200ms > capacity > 1024 0 666 > 512 0 333 453 > When the CPU start to be over utilized (@100ms), the utilization is > already too low (453 instead of 666) and scheduler doesn't detect yet > that we are over utilized > 256 0 169 226 246 252 > That's even worse with this lower capacity > > With time scaling, > time 0ms 50ms 100ms 150ms 200ms > capacity > 1024 0 666 > 512 0 428 677 > We know that the current capacity is not enough and the utilization > reflect the correct utilization level compare to 1024 capacity (the > 666 vs 677 difference comes from the 1024us window so the last window > is not full in the case of max capacity) > 256 0 234 468 564 677 > At 100ms, we know that there is not enough capacity. (In fact we know > that at 56ms). And even at time 200ms, the amount of work is exactly > what would have been executed on a CPU 4x faster > > > > > This change might not be a showstopper, but it is something to be aware > > off and take into account wherever PELT utilization is used. > > The point above is clearly a big difference between the 2 approaches > of the no spare cycle case but I think it will help by giving more > information in the over utilization case > > Vincent > > > > Morten > > -- > #include <best/regards.h> > > Patrick Bellasi