On Wed, Jun 04, 2014 at 11:32:10AM +0200, Vincent Guittot wrote:
On 4 June 2014 10:08, Peter Zijlstra peterz@infradead.org wrote:
On Wed, Jun 04, 2014 at 09:47:26AM +0200, Vincent Guittot wrote:
On 3 June 2014 17:50, Peter Zijlstra peterz@infradead.org wrote:
On Wed, May 28, 2014 at 04:47:03PM +0100, Morten Rasmussen wrote:
Since we may do periodic load-balance every 10 ms or so, we will perform a number of load-balances where runnable_avg_sum will mostly be reflecting the state of the world before a change (new task queued or moved a task to a different cpu). If you had have two tasks continuously on one cpu and your other cpu is idle, and you move one of the tasks to the other cpu, runnable_avg_sum will remain unchanged, 47742, on the first cpu while it starts from 0 on the other one. 10 ms later it will have increased a bit, 32 ms later it will be 47742/2, and 345 ms later it reaches 47742. In the mean time the cpu doesn't appear fully utilized and we might decide to put more tasks on it because we don't know if runnable_avg_sum represents a partially utilized cpu (for example a 50% task) or if it will continue to rise and eventually get to 47742.
Ah, no, since we track per task, and update the per-cpu ones when we migrate tasks, the per-cpu values should be instantly updated.
If we were to increase per task storage, we might as well also track running_avg not only runnable_avg.
I agree that the removed running_avg should give more useful information about the the load of a CPU.
The main issue with running_avg is that it's disturbed by other tasks (as point out previously). As a typical example, if we have 2 tasks with a load of 25% on 1 CPU, the unweighted runnable_load_avg will be in the range of [100% - 50%] depending of the parallelism of the runtime of the tasks whereas the reality is 50% and the use of running_avg will return this value
I'm not sure I see how 100% is possible, but yes I agree that runnable can indeed be inflated due to this queueing effect.
Let me explain the 75%, take any one of the above scenarios. Lets call the two tasks A and B, and let for a moment assume A always wins and runs first, and then B.
So A will be runnable for 25%, B otoh will be runnable the entire time A is actually running plus its own running time, giving 50%. Together that makes 75%.
If you release the assumption that A runs first, but instead assume they equally win the first execution, you get them averaging at 37.5% each, which combined will still give 75%.
In fact, it can be even worse than that because i forgot to take into account the geometric series effect which implies that it depends of the runtime (idletime) of the task
Take 3 examples:
2 tasks that need to run 10ms simultaneously each 40ms. If they share the same CPU, they will be on the runqueue 20ms (in fact a bit less for one of them), Their load (runnable_avg_sum/runnable_avg_period) will be 33% each so the unweighted runnable_load_avg of the CPU will be 66%
2 tasks that need to run 25ms simultaneously each 100ms. If they share the same CPU, they will be on the runqueue 50ms (in fact a bit less for one of them), Their load (runnable_avg_sum/runnable_avg_period) will be 74% each so the unweighted runnable_load_avg of the CPU will be 148%
2 tasks that need to run 50ms simultaneously each 200ms. If they share the same CPU, they will be on the runqueue 100ms (in fact a bit less for one of them), Their load (runnable_avg_sum/runnable_avg_period) will be 89% each so the unweighted runnable_load_avg of the CPU will be 180%
And this is because the running time is 'large' compared to the decay and we get hit by the weight of the recent state? Yes, I can see that, the avg will fluctuate due to the nature of this thing.