kernel_samsung_a34x-permissive/Documentation/scheduler/sched-tune.txt

             Central, scheduler-driven, power-performance control
                               (EXPERIMENTAL)

Abstract
========

The topic of a single simple power-performance tunable, that is wholly
scheduler centric, and has well defined and predictable properties has come up
on several occasions in the past [1,2]. With techniques such as a scheduler
driven DVFS [3], we now have a good framework for implementing such a tunable.
This document describes the overall ideas behind its design and implementation.


Table of Contents
=================

1. Motivation
2. Introduction
3. Signal Boosting Strategy
4. OPP selection using boosted CPU utilization
5. Per task group boosting
6. Per-task wakeup-placement-strategy Selection
7. Question and Answers
   - What about "auto" mode?
   - What about boosting on a congested system?
   - How CPUs are boosted when we have tasks with multiple boost values?
8. References


1. Motivation
=============

Schedutil [3] is a utilization-driven cpufreq governor which allows the
scheduler to select the optimal DVFS operating point (OPP) for running a task
allocated to a CPU.

However, sometimes it may be desired to intentionally boost the performance of
a workload even if that could imply a reasonable increase in energy
consumption. For example, in order to reduce the response time of a task, we
may want to run the task at a higher OPP than the one that is actually required
by it's CPU bandwidth demand.

This last requirement is especially important if we consider that one of the
main goals of the utilization-driven governor component is to replace all
currently available CPUFreq policies. Since schedutil is event-based, as
opposed to the sampling driven governors we currently have, they are already
more responsive at selecting the optimal OPP to run tasks allocated to a CPU.
However, just tracking the actual task utilization may not be enough from a
performance standpoint.  For example, it is not possible to get behaviors
similar to those provided by the "performance" and "interactive" CPUFreq
governors.

This document describes an implementation of a tunable, stacked on top of the
utilization-driven governor which extends its functionality to support task
performance boosting.

By "performance boosting" we mean the reduction of the time required to
complete a task activation, i.e. the time elapsed from a task wakeup to its
next deactivation (e.g. because it goes back to sleep or it terminates).  For
example, if we consider a simple periodic task which executes the same workload
for 5[s] every 20[s] while running at a certain OPP, a boosted execution of
that task must complete each of its activations in less than 5[s].

The rest of this document introduces in more details the proposed solution
which has been named SchedTune.


2. Introduction
===============

SchedTune exposes a simple user-space interface provided through a new
CGroup controller 'stune' which provides two power-performance tunables
per group:

  /<stune cgroup mount point>/schedtune.prefer_idle
  /<stune cgroup mount point>/schedtune.boost

The CGroup implementation permits arbitrary user-space defined task
classification to tune the scheduler for different goals depending on the
specific nature of the task, e.g. background vs interactive vs low-priority.

More details are given in section 5.

2.1 Boosting
============

The boost value is expressed as an integer in the range [0..100].

A value of 0 (default) configures the CFS scheduler for maximum energy
efficiency. This means that schedutil runs the tasks at the minimum OPP
required to satisfy their workload demand.

A value of 100 configures scheduler for maximum performance, which translates
to the selection of the maximum OPP on that CPU.

The range between 0 and 100 can be set to satisfy other scenarios suitably. For
example to satisfy interactive response or depending on other system events
(battery level etc).

The overall design of the SchedTune module is built on top of "Per-Entity Load
Tracking" (PELT) signals and schedutil by introducing a bias on the OPP
selection.

Each time a task is allocated on a CPU, cpufreq is given the opportunity to tune
the operating frequency of that CPU to better match the workload demand. The
selection of the actual OPP being activated is influenced by the boost value
for the task CGroup.

This simple biasing approach leverages existing frameworks, which means minimal
modifications to the scheduler, and yet it allows to achieve a range of
different behaviours all from a single simple tunable knob.

In EAS schedulers, we use boosted task and CPU utilization for energy
calculation and energy-aware task placement.

2.2 prefer_idle
===============

This is a flag which indicates to the scheduler that userspace would like
the scheduler to focus on energy or to focus on performance.

A value of 0 (default) signals to the CFS scheduler that tasks in this group
can be placed according to the energy-aware wakeup strategy.

A value of 1 signals to the CFS scheduler that tasks in this group should be
placed to minimise wakeup latency.

Android platforms typically use this flag for application tasks which the
user is currently interacting with.


3. Signal Boosting Strategy
===========================

The whole PELT machinery works based on the value of a few load tracking signals
which basically track the CPU bandwidth requirements for tasks and the capacity
of CPUs. The basic idea behind the SchedTune knob is to artificially inflate
some of these load tracking signals to make a task or RQ appears more demanding
that it actually is.

Which signals have to be inflated depends on the specific "consumer".  However,
independently from the specific (signal, consumer) pair, it is important to
define a simple and possibly consistent strategy for the concept of boosting a
signal.

A boosting strategy defines how the "abstract" user-space defined
sched_cfs_boost value is translated into an internal "margin" value to be added
to a signal to get its inflated value:

  margin         := boosting_strategy(sched_cfs_boost, signal)
  boosted_signal := signal + margin

The boosting strategy currently implemented in SchedTune is called 'Signal
Proportional Compensation' (SPC). With SPC, the sched_cfs_boost value is used to
compute a margin which is proportional to the complement of the original signal.
When a signal has a maximum possible value, its complement is defined as
the delta from the actual value and its possible maximum.

Since the tunable implementation uses signals which have SCHED_CAPACITY_SCALE as
the maximum possible value, the margin becomes:

	margin := sched_cfs_boost * (SCHED_CAPACITY_SCALE - signal)

Using this boosting strategy:
- a 100% sched_cfs_boost means that the signal is scaled to the maximum value
- each value in the range of sched_cfs_boost effectively inflates the signal in
  question by a quantity which is proportional to the maximum value.

For example, by applying the SPC boosting strategy to the selection of the OPP
to run a task it is possible to achieve these behaviors:

-   0% boosting: run the task at the minimum OPP required by its workload
- 100% boosting: run the task at the maximum OPP available for the CPU
-  50% boosting: run at the half-way OPP between minimum and maximum

Which means that, at 50% boosting, a task will be scheduled to run at half of
the maximum theoretically achievable performance on the specific target
platform.

A graphical representation of an SPC boosted signal is represented in the
following figure where:
 a) "-" represents the original signal
 b) "b" represents a  50% boosted signal
 c) "p" represents a 100% boosted signal


   ^
   |  SCHED_CAPACITY_SCALE
   +-----------------------------------------------------------------+
   |pppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppp
   |
   |                                             boosted_signal
   |                                          bbbbbbbbbbbbbbbbbbbbbbbb
   |
   |                                            original signal
   |                  bbbbbbbbbbbbbbbbbbbbbbbb+----------------------+
   |                                          |
   |bbbbbbbbbbbbbbbbbb                        |
   |                                          |
   |                                          |
   |                                          |
   |                  +-----------------------+
   |                  |
   |                  |
   |                  |
   |------------------+
   |
   |
   +----------------------------------------------------------------------->

The plot above shows a ramped load signal (titled 'original_signal') and it's
boosted equivalent. For each step of the original signal the boosted signal
corresponding to a 50% boost is midway from the original signal and the upper
bound. Boosting by 100% generates a boosted signal which is always saturated to
the upper bound.


4. OPP selection using boosted CPU utilization
==============================================

It is worth calling out that the implementation does not introduce any new load
signals. Instead, it provides an API to tune existing signals. This tuning is
done on demand and only in scheduler code paths where it is sensible to do so.
The new API calls are defined to return either the default signal or a boosted
one, depending on the value of sched_cfs_boost. This is a clean an non invasive
modification of the existing existing code paths.

The signal representing a CPU's utilization is boosted according to the
previously described SPC boosting strategy. To schedutil, this allows a CPU
(ie CFS run-queue) to appear more used then it actually is.

Thus, with the sched_cfs_boost enabled we have the following main functions to
get the current utilization of a CPU:

  cpu_util()
  stune_util()

The new stune_util() is similar to the first but returns a boosted
utilization signal which is a function of the sched_cfs_boost value.

This function is used in the CFS scheduler code paths where schedutil needs to
decide the OPP to run a CPU at. For example, this allows selecting the highest
OPP for a CPU which has the boost value set to 100%.


5. Per task group boosting
==========================

On battery powered devices there usually are many background services which are
long running and need energy efficient scheduling. On the other hand, some
applications are more performance sensitive and require an interactive
response and/or maximum performance, regardless of the energy cost.

To better service such scenarios, the SchedTune implementation has an extension
that provides a more fine grained boosting interface.

A new CGroup controller, namely "schedtune", can be enabled which allows to
defined and configure task groups with different boosting values.
Tasks that require special performance can be put into separate CGroups.
The value of the boost associated with the tasks in this group can be specified
using a single knob exposed by the CGroup controller:

   schedtune.boost

This knob allows the definition of a boost value that is to be used for
SPC boosting of all tasks attached to this group.

The current schedtune controller implementation is really simple and has these
main characteristics:

  1) It is only possible to create 1 level depth hierarchies

     The root control groups define the system-wide boost value to be applied
     by default to all tasks. Its direct subgroups are named "boost groups" and
     they define the boost value for specific set of tasks.
     Further nested subgroups are not allowed since they do not have a sensible
     meaning from a user-space standpoint.

  2) It is possible to define only a limited number of "boost groups"

     This number is defined at compile time and by default configured to 16.
     This is a design decision motivated by two main reasons:
     a) In a real system we do not expect utilization scenarios with more than
        a few boost groups. For example, a reasonable collection of groups could
        be just "background", "interactive" and "performance".
     b) It simplifies the implementation considerably, especially for the code
	which has to compute the per CPU boosting once there are multiple
        RUNNABLE tasks with different boost values.

Such a simple design should allow servicing the main utilization scenarios
identified so far. It provides a simple interface which can be used to manage
the power-performance of all tasks or only selected tasks.
Moreover, this interface can be easily integrated by user-space run-times (e.g.
Android, ChromeOS) to implement a QoS solution for task boosting based on tasks
classification, which has been a long standing requirement.

Setup and usage
---------------

0. Use a kernel with CONFIG_SCHED_TUNE support enabled

1. Check that the "schedtune" CGroup controller is available:

   root@linaro-nano:~# cat /proc/cgroups
   #subsys_name	hierarchy	num_cgroups	enabled
   cpuset  	0		1		1
   cpu     	0		1		1
   schedtune	0		1		1

2. Mount a tmpfs to create the CGroups mount point (Optional)

   root@linaro-nano:~# sudo mount -t tmpfs cgroups /sys/fs/cgroup

3. Mount the "schedtune" controller

   root@linaro-nano:~# mkdir /sys/fs/cgroup/stune
   root@linaro-nano:~# sudo mount -t cgroup -o schedtune stune /sys/fs/cgroup/stune

4. Create task groups and configure their specific boost value (Optional)

   For example here we create a "performance" boost group configure to boost
   all its tasks to 100%

   root@linaro-nano:~# mkdir /sys/fs/cgroup/stune/performance
   root@linaro-nano:~# echo 100 > /sys/fs/cgroup/stune/performance/schedtune.boost

5. Move tasks into the boost group

   For example, the following moves the tasks with PID $TASKPID (and all its
   threads) into the "performance" boost group.

   root@linaro-nano:~# echo "TASKPID > /sys/fs/cgroup/stune/performance/cgroup.procs

This simple configuration allows only the threads of the $TASKPID task to run,
when needed, at the highest OPP in the most capable CPU of the system.


6. Per-task wakeup-placement-strategy Selection
===============================================

Many devices have a number of CFS tasks in use which require an absolute
minimum wakeup latency, and many tasks for which wakeup latency is not
important.

For touch-driven environments, removing additional wakeup latency can be
critical.

When you use the Schedtume CGroup controller, you have access to a second
parameter which allows a group to be marked such that energy_aware task
placement is bypassed for tasks belonging to that group.

prefer_idle=0 (default - use energy-aware task placement if available)
prefer_idle=1 (never use energy-aware task placement for these tasks)

Since the regular wakeup task placement algorithm in CFS is biased for
performance, this has the effect of restoring minimum wakeup latency
for the desired tasks whilst still allowing energy-aware wakeup placement
to save energy for other tasks.


7. Question and Answers
=======================

What about "auto" mode?
-----------------------

The 'auto' mode as described in [5] can be implemented by interfacing SchedTune
with some suitable user-space element. This element could use the exposed
system-wide or cgroup based interface.

How are multiple groups of tasks with different boost values managed?
---------------------------------------------------------------------

The current SchedTune implementation keeps track of the boosted RUNNABLE tasks
on a CPU. The CPU utilization seen by schedutil (and used to select an
appropriate OPP) is boosted with a value which is the maximum of the boost
values of the currently RUNNABLE tasks in its RQ.

This allows cpufreq to boost a CPU only while there are boosted tasks ready
to run and switch back to the energy efficient mode as soon as the last boosted
task is dequeued.


8. References
=============
[1] http://lwn.net/Articles/552889
[2] http://lkml.org/lkml/2012/5/18/91
[3] https://lkml.org/lkml/2016/3/29/1041