Goals, Design and Implementation of the
new ultra-scalable O(1) scheduler
This is an edited version of an email Ingo Molnar sent to
lkml on 4 Jan 2002. It describes the goals, design, and
implementation of Ingo's new ultra-scalable O(1) scheduler.
Last Updated: 18 April 2002.
The main goal of the new scheduler is to keep all the good things we know
and love about the current Linux scheduler:
- good interactive performance even during high load: if the user
types or clicks then the system must react instantly and must execute
the user tasks smoothly, even during considerable background load.
- good scheduling/wakeup performance with 1-2 runnable processes.
- fairness: no process should stay without any timeslice for any
unreasonable amount of time. No process should get an unjustly high
amount of CPU time.
- priorities: less important tasks can be started with lower priority,
more important tasks with higher priority.
- SMP efficiency: no CPU should stay idle if there is work to do.
- SMP affinity: processes which run on one CPU should stay affine to
that CPU. Processes should not bounce between CPUs too frequently.
- plus additional scheduler features: RT scheduling, CPU binding.
and the goal is also to add a few new things:
- fully O(1) scheduling. Are you tired of the recalculation loop
blowing the L1 cache away every now and then? Do you think the goodness
loop is taking a bit too long to finish if there are lots of runnable
processes? This new scheduler takes no prisoners: wakeup(), schedule(),
the timer interrupt are all O(1) algorithms. There is no recalculation
loop. There is no goodness loop either.
- 'perfect' SMP scalability. With the new scheduler there is no 'big'
runqueue_lock anymore - it's all per-CPU runqueues and locks - two
tasks on two separate CPUs can wake up, schedule and context-switch
completely in parallel, without any interlocking. All
scheduling-relevant data is structured for maximum scalability.
- better SMP affinity. The old scheduler has a particular weakness that
causes the random bouncing of tasks between CPUs if/when higher
priority/interactive tasks, this was observed and reported by many
people. The reason is that the timeslice recalculation loop first needs
every currently running task to consume its timeslice. But when this
happens on eg. an 8-way system, then this property starves an
increasing number of CPUs from executing any process. Once the last
task that has a timeslice left has finished using up that timeslice,
the recalculation loop is triggered and other CPUs can start executing
tasks again - after having idled around for a number of timer ticks.
The more CPUs, the worse this effect.
Furthermore, this same effect causes the bouncing effect as well:
whenever there is such a 'timeslice squeeze' of the global runqueue,
idle processors start executing tasks which are not affine to that CPU.
(because the affine tasks have finished off their timeslices already.)
The new scheduler solves this problem by distributing timeslices on a
per-CPU basis, without having any global synchronization or
- batch scheduling. A significant proportion of computing-intensive tasks
benefit from batch-scheduling, where timeslices are long and processes
are roundrobin scheduled. The new scheduler does such batch-scheduling
of the lowest priority tasks - so nice +19 jobs will get
'batch-scheduled' automatically. With this scheduler, nice +19 jobs are
in essence SCHED_IDLE, from an interactiveness point of view.
- handle extreme loads more smoothly, without breakdown and scheduling
- O(1) RT scheduling. For those RT folks who are paranoid about the
O(nr_running) property of the goodness loop and the recalculation loop.
- run fork()ed children before the parent. Andrea has pointed out the
advantages of this a few months ago, but patches for this feature
do not work with the old scheduler as well as they should,
because idle processes often steal the new child before the fork()ing
CPU gets to execute it.
The core of the new scheduler contains the following mechanisms:
- *two* priority-ordered 'priority arrays' per CPU. There is an 'active'
array and an 'expired' array. The active array contains all tasks that
are affine to this CPU and have timeslices left. The expired array
contains all tasks which have used up their timeslices - but this array
is kept sorted as well. The active and expired array is not accessed
directly, it's accessed through two pointers in the per-CPU runqueue
structure. If all active tasks are used up then we 'switch' the two
pointers and from now on the ready-to-go (former-) expired array is the
active array - and the empty active array serves as the new collector
for expired tasks.
- there is a 64-bit bitmap cache for array indices. Finding the highest
priority task is thus a matter of two x86 BSFL bit-search instructions.
the split-array solution enables us to have an arbitrary number of active
and expired tasks, and the recalculation of timeslices can be done
immediately when the timeslice expires. Because the arrays are always
access through the pointers in the runqueue, switching the two arrays can
be done very quickly.
this is a hybride priority-list approach coupled with roundrobin
scheduling and the array-switch method of distributing timeslices.
- there is a per-task 'load estimator'.
one of the toughest things to get right is good interactive feel during
heavy system load. While playing with various scheduler variants i found
that the best interactive feel is achieved not by 'boosting' interactive
tasks, but by 'punishing' tasks that want to use more CPU time than there
is available. This method is also much easier to do in an O(1) fashion.
to establish the actual 'load' the task contributes to the system, a
complex-looking but pretty accurate method is used: there is a 4-entry
'history' ringbuffer of the task's activities during the last 4 seconds.
This ringbuffer is operated without much overhead. The entries tell the
scheduler a pretty accurate load-history of the task: has it used up more
CPU time or less during the past N seconds. [the size '4' and the interval
of 4x 1 seconds was found by lots of experimentation - this part is
flexible and can be changed in both directions.]
the penalty a task gets for generating more load than the CPU can handle
is a priority decrease - there is a maximum amount to this penalty
relative to their static priority, so even fully CPU-bound tasks will
observe each other's priorities, and will share the CPU accordingly.
the SMP load-balancer can be extended/switched with additional parallel
computing and cache hierarchy concepts: NUMA scheduling, multi-core CPUs
can be supported easily by changing the load-balancer. Right now it's
tuned for my SMP systems.
i skipped the prev->mm == next->mm advantage - no workload i know of shows
any sensitivity to this. It can be added back by sacrificing O(1)
schedule() [the current and one-lower priority list can be searched for a
that->mm == current->mm condition], but costs a fair number of cycles
during a number of important workloads, so i wanted to avoid this as much
- the SMP idle-task startup code was still racy and the new scheduler
triggered this. So i streamlined the idle-setup code a bit. We do not call
into schedule() before all processors have started up fully and all idle
threads are in place.
- the patch also cleans up a number of aspects of sched.c - moves code
into other areas of the kernel where it's appropriate, and simplifies
certain code paths and data constructs. As a result, the new scheduler's
code is smaller than the old one.