mirror of
https://git.kernel.org/pub/scm/linux/kernel/git/stable/linux.git
synced 2024-08-26 10:49:33 +00:00
![Lukasz Luba](/assets/img/avatar_default.png)
The Energy Model (EM) can store power values in milli-Watts or in abstract scale. This might cause issues in the subsystems which use the EM for estimating the device power, such as: - mixing of different scales in a subsystem which uses multiple (cooling) devices (e.g. thermal Intelligent Power Allocation (IPA)) - assuming that energy [milli-Joules] can be derived from the EM power values which might not be possible since the power scale doesn't have to be in milli-Watts To avoid misconfiguration add the requisite documentation to the EM and related subsystems: EAS and IPA. Signed-off-by: Lukasz Luba <lukasz.luba@arm.com> Signed-off-by: Rafael J. Wysocki <rafael.j.wysocki@intel.com>
427 lines
20 KiB
ReStructuredText
427 lines
20 KiB
ReStructuredText
=======================
|
|
Energy Aware Scheduling
|
|
=======================
|
|
|
|
1. Introduction
|
|
---------------
|
|
|
|
Energy Aware Scheduling (or EAS) gives the scheduler the ability to predict
|
|
the impact of its decisions on the energy consumed by CPUs. EAS relies on an
|
|
Energy Model (EM) of the CPUs to select an energy efficient CPU for each task,
|
|
with a minimal impact on throughput. This document aims at providing an
|
|
introduction on how EAS works, what are the main design decisions behind it, and
|
|
details what is needed to get it to run.
|
|
|
|
Before going any further, please note that at the time of writing::
|
|
|
|
/!\ EAS does not support platforms with symmetric CPU topologies /!\
|
|
|
|
EAS operates only on heterogeneous CPU topologies (such as Arm big.LITTLE)
|
|
because this is where the potential for saving energy through scheduling is
|
|
the highest.
|
|
|
|
The actual EM used by EAS is _not_ maintained by the scheduler, but by a
|
|
dedicated framework. For details about this framework and what it provides,
|
|
please refer to its documentation (see Documentation/power/energy-model.rst).
|
|
|
|
|
|
2. Background and Terminology
|
|
-----------------------------
|
|
|
|
To make it clear from the start:
|
|
- energy = [joule] (resource like a battery on powered devices)
|
|
- power = energy/time = [joule/second] = [watt]
|
|
|
|
The goal of EAS is to minimize energy, while still getting the job done. That
|
|
is, we want to maximize::
|
|
|
|
performance [inst/s]
|
|
--------------------
|
|
power [W]
|
|
|
|
which is equivalent to minimizing::
|
|
|
|
energy [J]
|
|
-----------
|
|
instruction
|
|
|
|
while still getting 'good' performance. It is essentially an alternative
|
|
optimization objective to the current performance-only objective for the
|
|
scheduler. This alternative considers two objectives: energy-efficiency and
|
|
performance.
|
|
|
|
The idea behind introducing an EM is to allow the scheduler to evaluate the
|
|
implications of its decisions rather than blindly applying energy-saving
|
|
techniques that may have positive effects only on some platforms. At the same
|
|
time, the EM must be as simple as possible to minimize the scheduler latency
|
|
impact.
|
|
|
|
In short, EAS changes the way CFS tasks are assigned to CPUs. When it is time
|
|
for the scheduler to decide where a task should run (during wake-up), the EM
|
|
is used to break the tie between several good CPU candidates and pick the one
|
|
that is predicted to yield the best energy consumption without harming the
|
|
system's throughput. The predictions made by EAS rely on specific elements of
|
|
knowledge about the platform's topology, which include the 'capacity' of CPUs,
|
|
and their respective energy costs.
|
|
|
|
|
|
3. Topology information
|
|
-----------------------
|
|
|
|
EAS (as well as the rest of the scheduler) uses the notion of 'capacity' to
|
|
differentiate CPUs with different computing throughput. The 'capacity' of a CPU
|
|
represents the amount of work it can absorb when running at its highest
|
|
frequency compared to the most capable CPU of the system. Capacity values are
|
|
normalized in a 1024 range, and are comparable with the utilization signals of
|
|
tasks and CPUs computed by the Per-Entity Load Tracking (PELT) mechanism. Thanks
|
|
to capacity and utilization values, EAS is able to estimate how big/busy a
|
|
task/CPU is, and to take this into consideration when evaluating performance vs
|
|
energy trade-offs. The capacity of CPUs is provided via arch-specific code
|
|
through the arch_scale_cpu_capacity() callback.
|
|
|
|
The rest of platform knowledge used by EAS is directly read from the Energy
|
|
Model (EM) framework. The EM of a platform is composed of a power cost table
|
|
per 'performance domain' in the system (see Documentation/power/energy-model.rst
|
|
for futher details about performance domains).
|
|
|
|
The scheduler manages references to the EM objects in the topology code when the
|
|
scheduling domains are built, or re-built. For each root domain (rd), the
|
|
scheduler maintains a singly linked list of all performance domains intersecting
|
|
the current rd->span. Each node in the list contains a pointer to a struct
|
|
em_perf_domain as provided by the EM framework.
|
|
|
|
The lists are attached to the root domains in order to cope with exclusive
|
|
cpuset configurations. Since the boundaries of exclusive cpusets do not
|
|
necessarily match those of performance domains, the lists of different root
|
|
domains can contain duplicate elements.
|
|
|
|
Example 1.
|
|
Let us consider a platform with 12 CPUs, split in 3 performance domains
|
|
(pd0, pd4 and pd8), organized as follows::
|
|
|
|
CPUs: 0 1 2 3 4 5 6 7 8 9 10 11
|
|
PDs: |--pd0--|--pd4--|---pd8---|
|
|
RDs: |----rd1----|-----rd2-----|
|
|
|
|
Now, consider that userspace decided to split the system with two
|
|
exclusive cpusets, hence creating two independent root domains, each
|
|
containing 6 CPUs. The two root domains are denoted rd1 and rd2 in the
|
|
above figure. Since pd4 intersects with both rd1 and rd2, it will be
|
|
present in the linked list '->pd' attached to each of them:
|
|
|
|
* rd1->pd: pd0 -> pd4
|
|
* rd2->pd: pd4 -> pd8
|
|
|
|
Please note that the scheduler will create two duplicate list nodes for
|
|
pd4 (one for each list). However, both just hold a pointer to the same
|
|
shared data structure of the EM framework.
|
|
|
|
Since the access to these lists can happen concurrently with hotplug and other
|
|
things, they are protected by RCU, like the rest of topology structures
|
|
manipulated by the scheduler.
|
|
|
|
EAS also maintains a static key (sched_energy_present) which is enabled when at
|
|
least one root domain meets all conditions for EAS to start. Those conditions
|
|
are summarized in Section 6.
|
|
|
|
|
|
4. Energy-Aware task placement
|
|
------------------------------
|
|
|
|
EAS overrides the CFS task wake-up balancing code. It uses the EM of the
|
|
platform and the PELT signals to choose an energy-efficient target CPU during
|
|
wake-up balance. When EAS is enabled, select_task_rq_fair() calls
|
|
find_energy_efficient_cpu() to do the placement decision. This function looks
|
|
for the CPU with the highest spare capacity (CPU capacity - CPU utilization) in
|
|
each performance domain since it is the one which will allow us to keep the
|
|
frequency the lowest. Then, the function checks if placing the task there could
|
|
save energy compared to leaving it on prev_cpu, i.e. the CPU where the task ran
|
|
in its previous activation.
|
|
|
|
find_energy_efficient_cpu() uses compute_energy() to estimate what will be the
|
|
energy consumed by the system if the waking task was migrated. compute_energy()
|
|
looks at the current utilization landscape of the CPUs and adjusts it to
|
|
'simulate' the task migration. The EM framework provides the em_pd_energy() API
|
|
which computes the expected energy consumption of each performance domain for
|
|
the given utilization landscape.
|
|
|
|
An example of energy-optimized task placement decision is detailed below.
|
|
|
|
Example 2.
|
|
Let us consider a (fake) platform with 2 independent performance domains
|
|
composed of two CPUs each. CPU0 and CPU1 are little CPUs; CPU2 and CPU3
|
|
are big.
|
|
|
|
The scheduler must decide where to place a task P whose util_avg = 200
|
|
and prev_cpu = 0.
|
|
|
|
The current utilization landscape of the CPUs is depicted on the graph
|
|
below. CPUs 0-3 have a util_avg of 400, 100, 600 and 500 respectively
|
|
Each performance domain has three Operating Performance Points (OPPs).
|
|
The CPU capacity and power cost associated with each OPP is listed in
|
|
the Energy Model table. The util_avg of P is shown on the figures
|
|
below as 'PP'::
|
|
|
|
CPU util.
|
|
1024 - - - - - - - Energy Model
|
|
+-----------+-------------+
|
|
| Little | Big |
|
|
768 ============= +-----+-----+------+------+
|
|
| Cap | Pwr | Cap | Pwr |
|
|
+-----+-----+------+------+
|
|
512 =========== - ##- - - - - | 170 | 50 | 512 | 400 |
|
|
## ## | 341 | 150 | 768 | 800 |
|
|
341 -PP - - - - ## ## | 512 | 300 | 1024 | 1700 |
|
|
PP ## ## +-----+-----+------+------+
|
|
170 -## - - - - ## ##
|
|
## ## ## ##
|
|
------------ -------------
|
|
CPU0 CPU1 CPU2 CPU3
|
|
|
|
Current OPP: ===== Other OPP: - - - util_avg (100 each): ##
|
|
|
|
|
|
find_energy_efficient_cpu() will first look for the CPUs with the
|
|
maximum spare capacity in the two performance domains. In this example,
|
|
CPU1 and CPU3. Then it will estimate the energy of the system if P was
|
|
placed on either of them, and check if that would save some energy
|
|
compared to leaving P on CPU0. EAS assumes that OPPs follow utilization
|
|
(which is coherent with the behaviour of the schedutil CPUFreq
|
|
governor, see Section 6. for more details on this topic).
|
|
|
|
**Case 1. P is migrated to CPU1**::
|
|
|
|
1024 - - - - - - -
|
|
|
|
Energy calculation:
|
|
768 ============= * CPU0: 200 / 341 * 150 = 88
|
|
* CPU1: 300 / 341 * 150 = 131
|
|
* CPU2: 600 / 768 * 800 = 625
|
|
512 - - - - - - - ##- - - - - * CPU3: 500 / 768 * 800 = 520
|
|
## ## => total_energy = 1364
|
|
341 =========== ## ##
|
|
PP ## ##
|
|
170 -## - - PP- ## ##
|
|
## ## ## ##
|
|
------------ -------------
|
|
CPU0 CPU1 CPU2 CPU3
|
|
|
|
|
|
**Case 2. P is migrated to CPU3**::
|
|
|
|
1024 - - - - - - -
|
|
|
|
Energy calculation:
|
|
768 ============= * CPU0: 200 / 341 * 150 = 88
|
|
* CPU1: 100 / 341 * 150 = 43
|
|
PP * CPU2: 600 / 768 * 800 = 625
|
|
512 - - - - - - - ##- - -PP - * CPU3: 700 / 768 * 800 = 729
|
|
## ## => total_energy = 1485
|
|
341 =========== ## ##
|
|
## ##
|
|
170 -## - - - - ## ##
|
|
## ## ## ##
|
|
------------ -------------
|
|
CPU0 CPU1 CPU2 CPU3
|
|
|
|
|
|
**Case 3. P stays on prev_cpu / CPU 0**::
|
|
|
|
1024 - - - - - - -
|
|
|
|
Energy calculation:
|
|
768 ============= * CPU0: 400 / 512 * 300 = 234
|
|
* CPU1: 100 / 512 * 300 = 58
|
|
* CPU2: 600 / 768 * 800 = 625
|
|
512 =========== - ##- - - - - * CPU3: 500 / 768 * 800 = 520
|
|
## ## => total_energy = 1437
|
|
341 -PP - - - - ## ##
|
|
PP ## ##
|
|
170 -## - - - - ## ##
|
|
## ## ## ##
|
|
------------ -------------
|
|
CPU0 CPU1 CPU2 CPU3
|
|
|
|
|
|
From these calculations, the Case 1 has the lowest total energy. So CPU 1
|
|
is be the best candidate from an energy-efficiency standpoint.
|
|
|
|
Big CPUs are generally more power hungry than the little ones and are thus used
|
|
mainly when a task doesn't fit the littles. However, little CPUs aren't always
|
|
necessarily more energy-efficient than big CPUs. For some systems, the high OPPs
|
|
of the little CPUs can be less energy-efficient than the lowest OPPs of the
|
|
bigs, for example. So, if the little CPUs happen to have enough utilization at
|
|
a specific point in time, a small task waking up at that moment could be better
|
|
of executing on the big side in order to save energy, even though it would fit
|
|
on the little side.
|
|
|
|
And even in the case where all OPPs of the big CPUs are less energy-efficient
|
|
than those of the little, using the big CPUs for a small task might still, under
|
|
specific conditions, save energy. Indeed, placing a task on a little CPU can
|
|
result in raising the OPP of the entire performance domain, and that will
|
|
increase the cost of the tasks already running there. If the waking task is
|
|
placed on a big CPU, its own execution cost might be higher than if it was
|
|
running on a little, but it won't impact the other tasks of the little CPUs
|
|
which will keep running at a lower OPP. So, when considering the total energy
|
|
consumed by CPUs, the extra cost of running that one task on a big core can be
|
|
smaller than the cost of raising the OPP on the little CPUs for all the other
|
|
tasks.
|
|
|
|
The examples above would be nearly impossible to get right in a generic way, and
|
|
for all platforms, without knowing the cost of running at different OPPs on all
|
|
CPUs of the system. Thanks to its EM-based design, EAS should cope with them
|
|
correctly without too many troubles. However, in order to ensure a minimal
|
|
impact on throughput for high-utilization scenarios, EAS also implements another
|
|
mechanism called 'over-utilization'.
|
|
|
|
|
|
5. Over-utilization
|
|
-------------------
|
|
|
|
From a general standpoint, the use-cases where EAS can help the most are those
|
|
involving a light/medium CPU utilization. Whenever long CPU-bound tasks are
|
|
being run, they will require all of the available CPU capacity, and there isn't
|
|
much that can be done by the scheduler to save energy without severly harming
|
|
throughput. In order to avoid hurting performance with EAS, CPUs are flagged as
|
|
'over-utilized' as soon as they are used at more than 80% of their compute
|
|
capacity. As long as no CPUs are over-utilized in a root domain, load balancing
|
|
is disabled and EAS overridess the wake-up balancing code. EAS is likely to load
|
|
the most energy efficient CPUs of the system more than the others if that can be
|
|
done without harming throughput. So, the load-balancer is disabled to prevent
|
|
it from breaking the energy-efficient task placement found by EAS. It is safe to
|
|
do so when the system isn't overutilized since being below the 80% tipping point
|
|
implies that:
|
|
|
|
a. there is some idle time on all CPUs, so the utilization signals used by
|
|
EAS are likely to accurately represent the 'size' of the various tasks
|
|
in the system;
|
|
b. all tasks should already be provided with enough CPU capacity,
|
|
regardless of their nice values;
|
|
c. since there is spare capacity all tasks must be blocking/sleeping
|
|
regularly and balancing at wake-up is sufficient.
|
|
|
|
As soon as one CPU goes above the 80% tipping point, at least one of the three
|
|
assumptions above becomes incorrect. In this scenario, the 'overutilized' flag
|
|
is raised for the entire root domain, EAS is disabled, and the load-balancer is
|
|
re-enabled. By doing so, the scheduler falls back onto load-based algorithms for
|
|
wake-up and load balance under CPU-bound conditions. This provides a better
|
|
respect of the nice values of tasks.
|
|
|
|
Since the notion of overutilization largely relies on detecting whether or not
|
|
there is some idle time in the system, the CPU capacity 'stolen' by higher
|
|
(than CFS) scheduling classes (as well as IRQ) must be taken into account. As
|
|
such, the detection of overutilization accounts for the capacity used not only
|
|
by CFS tasks, but also by the other scheduling classes and IRQ.
|
|
|
|
|
|
6. Dependencies and requirements for EAS
|
|
----------------------------------------
|
|
|
|
Energy Aware Scheduling depends on the CPUs of the system having specific
|
|
hardware properties and on other features of the kernel being enabled. This
|
|
section lists these dependencies and provides hints as to how they can be met.
|
|
|
|
|
|
6.1 - Asymmetric CPU topology
|
|
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
|
|
|
|
|
|
As mentioned in the introduction, EAS is only supported on platforms with
|
|
asymmetric CPU topologies for now. This requirement is checked at run-time by
|
|
looking for the presence of the SD_ASYM_CPUCAPACITY flag when the scheduling
|
|
domains are built.
|
|
|
|
See Documentation/scheduler/sched-capacity.rst for requirements to be met for this
|
|
flag to be set in the sched_domain hierarchy.
|
|
|
|
Please note that EAS is not fundamentally incompatible with SMP, but no
|
|
significant savings on SMP platforms have been observed yet. This restriction
|
|
could be amended in the future if proven otherwise.
|
|
|
|
|
|
6.2 - Energy Model presence
|
|
^^^^^^^^^^^^^^^^^^^^^^^^^^^
|
|
|
|
EAS uses the EM of a platform to estimate the impact of scheduling decisions on
|
|
energy. So, your platform must provide power cost tables to the EM framework in
|
|
order to make EAS start. To do so, please refer to documentation of the
|
|
independent EM framework in Documentation/power/energy-model.rst.
|
|
|
|
Please also note that the scheduling domains need to be re-built after the
|
|
EM has been registered in order to start EAS.
|
|
|
|
EAS uses the EM to make a forecasting decision on energy usage and thus it is
|
|
more focused on the difference when checking possible options for task
|
|
placement. For EAS it doesn't matter whether the EM power values are expressed
|
|
in milli-Watts or in an 'abstract scale'.
|
|
|
|
|
|
6.3 - Energy Model complexity
|
|
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
|
|
|
|
The task wake-up path is very latency-sensitive. When the EM of a platform is
|
|
too complex (too many CPUs, too many performance domains, too many performance
|
|
states, ...), the cost of using it in the wake-up path can become prohibitive.
|
|
The energy-aware wake-up algorithm has a complexity of:
|
|
|
|
C = Nd * (Nc + Ns)
|
|
|
|
with: Nd the number of performance domains; Nc the number of CPUs; and Ns the
|
|
total number of OPPs (ex: for two perf. domains with 4 OPPs each, Ns = 8).
|
|
|
|
A complexity check is performed at the root domain level, when scheduling
|
|
domains are built. EAS will not start on a root domain if its C happens to be
|
|
higher than the completely arbitrary EM_MAX_COMPLEXITY threshold (2048 at the
|
|
time of writing).
|
|
|
|
If you really want to use EAS but the complexity of your platform's Energy
|
|
Model is too high to be used with a single root domain, you're left with only
|
|
two possible options:
|
|
|
|
1. split your system into separate, smaller, root domains using exclusive
|
|
cpusets and enable EAS locally on each of them. This option has the
|
|
benefit to work out of the box but the drawback of preventing load
|
|
balance between root domains, which can result in an unbalanced system
|
|
overall;
|
|
2. submit patches to reduce the complexity of the EAS wake-up algorithm,
|
|
hence enabling it to cope with larger EMs in reasonable time.
|
|
|
|
|
|
6.4 - Schedutil governor
|
|
^^^^^^^^^^^^^^^^^^^^^^^^
|
|
|
|
EAS tries to predict at which OPP will the CPUs be running in the close future
|
|
in order to estimate their energy consumption. To do so, it is assumed that OPPs
|
|
of CPUs follow their utilization.
|
|
|
|
Although it is very difficult to provide hard guarantees regarding the accuracy
|
|
of this assumption in practice (because the hardware might not do what it is
|
|
told to do, for example), schedutil as opposed to other CPUFreq governors at
|
|
least _requests_ frequencies calculated using the utilization signals.
|
|
Consequently, the only sane governor to use together with EAS is schedutil,
|
|
because it is the only one providing some degree of consistency between
|
|
frequency requests and energy predictions.
|
|
|
|
Using EAS with any other governor than schedutil is not supported.
|
|
|
|
|
|
6.5 Scale-invariant utilization signals
|
|
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
|
|
|
|
In order to make accurate prediction across CPUs and for all performance
|
|
states, EAS needs frequency-invariant and CPU-invariant PELT signals. These can
|
|
be obtained using the architecture-defined arch_scale{cpu,freq}_capacity()
|
|
callbacks.
|
|
|
|
Using EAS on a platform that doesn't implement these two callbacks is not
|
|
supported.
|
|
|
|
|
|
6.6 Multithreading (SMT)
|
|
^^^^^^^^^^^^^^^^^^^^^^^^
|
|
|
|
EAS in its current form is SMT unaware and is not able to leverage
|
|
multithreaded hardware to save energy. EAS considers threads as independent
|
|
CPUs, which can actually be counter-productive for both performance and energy.
|
|
|
|
EAS on SMT is not supported.
|