Re: [patch] CFS scheduler, -v8

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Hi, Ingo

My name is Ting Yang, a graduate student from UMASS. I am currently studying the linux scheduler and virtual memory manager to solve some page swapping problems. I am very excited with the new scheduler CFS. After I read through your code, I think that you might be interested in reading this paper:

"A Proportional Share REsource Allocation Algorithm for Real-Time, Time-Shared Systems", by Ion Stoica. You can find the paper here: http://citeseer.ist.psu.edu/37752.html

Authors of this paper proposed a scheduler: Earlist Eligible Virtual Deadline First (EEVDF). EEVDF uses exactly the same method as CFS to track the execution of each running task. The only difference between EEVDF and CFS is that EEVDF tries to _deadline_ fair while CFS is _start-time_ fair. Scheduling based on deadline gives better reponse time bound and seems to more fair.

In the following part of this email, I will try to explain the similarities and differences between EEVDF and CFS. Hopefully, this might provide you with some useful information w.r.t your current work on CFS.

Similarities:
1. both EEVDF and CFS use virtual time to track the system's progress.

CFS maintains rq->fair_clock for each cpu, which is updated every tick by:
               SCALE/sum(p_i->loadweight)
where p_i->loadweight is the weight of each task mapped from its nice value in prio_to_load_shift[], given that the default weight is SCALE (1024)

 EEVDF maintains a virtual time, which is advanced every tick by:
1/sum(w_i) where w_i is the weight of each task, given that the default weight is 1.

Therefore, EEVDF and CFS monitors system progress in the same way, except normalized to different scale.

2. EEVDF and CFS monitors the progress in the same way.

CFS maintains a p->fair_key which indicating the amount of work done by this task. When p executes for a period t, then p->fair_key incremented by:
          t * SCALE/p->loadweight //the default weight is SCALE
          (based on solving equations in your code :-))

EEVDF does the same thing with assumption that the default weight is 1, it uses the same equation to calculate deadlines for running tasks.

Differences:
The main difference between CFS and EEVDF lies in the scheduling policy, although they follow the same model for tracking tasks.

*** CFS: When a task starts, it gets p->fair_key from the current virtual time rq->fair_clock. It will not be scheduled for execution until all other running tasks' fair_key go beyond p->fair_key by certain virtual ticks (which is 5 ticks for the current setting of CFS).

(I wish I could show examples with graphs, instead of my not-so-good english, but I am not sure if it appropriate to attach figures on this maillist)

EXAMPLE: assume the system runs at 1000 tick/second, i.e. 1ms a tick, and the granularity of pre-exemption for CFS is 5 virtual ticks (the current setting). If, at time t=0, we start 2 tasks: p1 and p2, both have nice value 0 (weight 1024), and rq->fair_clock is initialized to 0. Now we have: p1->fair_key = p2->fair_key = rq->fair_clock = 0. CFS breaks the tie arbitrarily, say it executes p1. After 1 system tick (1ms later) t=1, we have:
       rq->fair_clock = 1/2, p1->fair_key = 1,  p2->fair_key = 0.
Suppose, a new task p3 starts with nice value -10 at this moment, that is p3->fair_key=1/2. In this case, CFS will not schedule p3 for execution until the fair_keys of p1 and p2 go beyond 5+1/2 (which translates to about 10ms later in this setting), _regardless_ the priority (weight) of p3. Further imagine, if we starts n tasks at time t=0 and then start a task p_(n+1) at time t = 1, the delay of task p_(n+1) actually is proportional to the number of running tasks n.

Formally speaking, CFS can has a *O(n)* lag w.r.t the ideal proportional shared fluid-flow system, which can be arbitrarily fine granularity. The cause of this problem is that p->fair_key only reflects a fair point that a task should be started, but does not has any information about how urgent the task is (i.e. the priority or weight of the task).

*** In EEVDF, each task p_i is specified by 2 parameters: weight w_i and timeslice length l_i. EEVDF tries to schedule tasks based on the virtual deadline vd_i where a timeslice l_i should be finished. EEVDF keeps a virtual start (ve_i) and virtual deadline (vd_i) for each tasks. When a tasks starts, its ve_i is initialized to be the current virtual time, and calculates its virtual deadline as:
       vd_i = ve_i + l_i/w_i  //the same method as CFS updates fair_key.
When l_i amount of work is done, the just finished vd_i becomes the new ve_i. That is the virtual start time of next l_i amount work is the deadline of previous finished timeslice. The virtual deadline vd_i is then updated using the above equation.

EEVDF schedule policy: always executes the task with the _earliest_ virtual deadline.

EXAMPLE: Assume the system has 1000 ticks per second. At time t = 0, we start 2 tasks: p1 and p2, such that w_1 = w_2 = 1 and l_1 = l_2 = 5 ticks, i.e 5ms (which reflects the similar setting in CFS case). Furthermore, the system virtual time vt is initialized to be 0. Now at time t = 0, we have
           vt = 0,
           ve_1 = 0, vd_1 = ve_1 + l_1/w_1 = 5
           ve_2 = 0, vd_2 = vd_2 + l_2/w_2 = 5
As p1 and p2 have the same virtual deadline, EEVDF breaks the tie arbitrarily, say it executes p1. After 1 system tick (1ms later), we have:
     vt = 0 + 1 / (w_1 + w_2) = 1/2 //just as CFS updates rq->fair_clock
     ve_1 = 0, vd_1 = 5             //not changed
     ve_2 = 0, vd_1 = 5             //not changed
Suppose, we starts a new task p2 at this moment, with weight w_3 = 2 and timeslice l_3 = 5 ticks (5ms), Then
     ve_3 = vt = 1/2
     vd_3 = ve_3 + l_3/w_2 = 1/2 + 5/2 = 3
hmmm, the scheduler now will execute task p3 first since it has the earliest deadline. The deadline implicitly contains some very important information that the CFS fair_key does not have: how urgent this amount of
work has to be done, which comes from the weight of a task.

Formally speaking, EEVDF has a constant O(1) lag w.r.t the ideal proportional shared fluid-flow system. (Please look at the paper for detail proofs.) Under normal cases, for a task p_i, EEVDF ensures that it does not fall behind the ideal system by more than l_i time. Occasionally, the delay can be max(l_i), the maximum timeslice used by all active tasks, due to the dynamic entering and leaving of tasks. (Again, the paper give more detailed explanation on this).

We can see that here the timeslice l_i used by a task p_i actually controls accuracy of scheduling p_i. The smaller l_i, the closer to the ideal system during p_i's execution. For example, in above case, if p3 has w_3 = 1 (the same as p1 and p2) and l_3 = 3 (3ms). Since vd_3 = 1/2 + l_3/w_3 = 7/2, the scheduler still executes p3 first, even though p1,p2 and p3 have the same weight. Smaller l_i leads the scheduler to handle p_i in finer granularity. Intuitively, it makes scheduler checks the deadline of p_i more frequently and ensures each small piece of work is done on time, while larger l_i does the reverse.

The decouple of weight w_i and timeslice l_i is important. Generally speaking, weight determines throughput and timeslice determines the responsiveness of a task. In normal situation, high priority tasks usually need more cpu capacity within short period of time (bursty, such as keyboard, mouse move, X updates, daemons, etc), and need to be processed as quick as possible (responsiveness and interactiveness). Follow the analysis above, we know that for higher priority tasks we should give _higher weight_ to ensure its CPU throughput, and at the same time give _smaller timeslice_ to ensure better responsiveness. This is a bit counter-intuitive against the current linux implementation: smaller nice value leads to higher weight and larger timeslice.

Now let's see what happens in the Real-Time world. Usually a real-time application is specified with (C_i, T_i), where C_i is the amount of work and T_i is the period of time that the work has to be finished. For example, (20ms, 50ms) says the scheduler has to do 20ms work within a window of 50ms for this task. Smaller T_i gives tighter response constraints. Note that Bi = Ci/Ti is really the CPU proportion for the task during its execution. In our proportional time share world, weight w_i decides the cpu proportion which maps to Bi, and timeslice l_i gives the amount works should be done each time, which maps Ci. Then using w_i and l_i, we can get a window size, which actually maps Ti. Therefore smaller l_i leads to smaller Ti which means tighter response constraints. It seems to me all these make a lot sense in both proportional time share and real-time world. Based on my understanding, adopting something like EEVDF in CFS should not be very difficult given their similarities, although I do not have any idea on how this impacts the load balancing for SMP. Does this worth a try?

 Sorry for such a long email :-)

Ting

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