cpuidle: teo: Introduce util-awareness

Modern interactive systems, such as recent Android phones, tend to have
power efficient shallow idle states. Selecting deeper idle states on a
device while a latency-sensitive workload is running can adversely
impact performance due to increased latency. Additionally, if the CPU
wakes up from a deeper sleep before its target residency as is often the
case, it results in a waste of energy on top of that.

At the moment, none of the available idle governors take any scheduling
information into account. They also tend to overestimate the idle
duration quite often, which causes them to select excessively deep idle
states, thus leading to increased wakeup latency and lower performance
with no power saving. For 'menu' while web browsing on Android for
instance, those types of wakeups ('too deep') account for over 24% of
all wakeups.

At the same time, on some platforms idle state 0 can be power efficient
enough to warrant wanting to prefer it over idle state 1. This is
because the power usage of the two states can be so close that
sufficient amounts of too deep state 1 sleeps can completely offset the
state 1 power saving to the point where it would've been more power
efficient to just use state 0 instead. This is, of course, for systems
where state 0 is not a polling state, such as arm-based devices.

Sleeps that happened in state 0 while they could have used state 1 ('too
shallow') only save less power than they otherwise could have. Too deep
sleeps, on the other hand, harm performance and nullify the potential
power saving from using state 1 in the first place. While taking this
into account, it is clear that on balance it is preferable for an idle
governor to have more too shallow sleeps instead of more too deep sleeps
on those kinds of platforms.

This patch specifically tunes TEO to prefer shallower idle states in
order to reduce wakeup latency and achieve better performance.

To this end, before selecting the next idle state it uses the avg_util
signal of a CPU's runqueue in order to determine to what extent the CPU
is being utilized. This util value is then compared to a threshold
defined as a percentage of the CPU's capacity (capacity >> 6 ie. ~1.5%
in the current implementation). If the util is above the threshold, the
index of the idle state selected by TEO metrics will be reduced by 1,
thus selecting a shallower state. If the util is below the threshold,
the governor defaults to the TEO metrics mechanism to try to select the
deepest available idle state based on the closest timer event and its
own correctness.

The main goal of this is to reduce latency and increase performance for
some workloads. Under some workloads it will result in an increase in
power usage (Geekbench 5) while for other workloads it will also result
in a decrease in power usage compared to TEO (PCMark Web, Jankbench,
Speedometer).

It can provide drastically decreased latency and performance benefits in
certain types of workloads that are sensitive to latency.

Example test results:

1. GB5 (better score, latency & more power usage)

| metric                                | menu           | teo               | teo-util-aware    |
| ------------------------------------- | -------------- | ----------------- | ----------------- |
| gmean score                           | 2826.5 (0.0%)  | 2764.8 (-2.18%)   | 2865 (1.36%)      |
| gmean power usage [mW]                | 2551.4 (0.0%)  | 2606.8 (2.17%)    | 2722.3 (6.7%)     |
| gmean too deep %                      | 14.99%         | 9.65%             | 4.02%             |
| gmean too shallow %                   | 2.5%           | 5.96%             | 14.59%            |
| gmean task wakeup latency (asynctask) | 78.16μs (0.0%) | 61.60μs (-21.19%) | 54.45μs (-30.34%) |

2. Jankbench (better score, latency & less power usage)

| metric                                | menu           | teo               | teo-util-aware    |
| ------------------------------------- | -------------- | ----------------- | ----------------- |
| gmean frame duration                  | 13.9 (0.0%)    | 14.7 (6.0%)       | 12.6 (-9.0%)      |
| gmean jank percentage                 | 1.5 (0.0%)     | 2.1 (36.99%)      | 1.3 (-17.37%)     |
| gmean power usage [mW]                | 144.6 (0.0%)   | 136.9 (-5.27%)    | 121.3 (-16.08%)   |
| gmean too deep %                      | 26.00%         | 11.00%            | 2.54%             |
| gmean too shallow %                   | 4.74%          | 11.89%            | 21.93%            |
| gmean wakeup latency (RenderThread)   | 139.5μs (0.0%) | 116.5μs (-16.49%) | 91.11μs (-34.7%)  |
| gmean wakeup latency (surfaceflinger) | 124.0μs (0.0%) | 151.9μs (22.47%)  | 87.65μs (-29.33%) |

Signed-off-by: Kajetan Puchalski <kajetan.puchalski@arm.com>
[ rjw: Comment edits and white space adjustments ]
Signed-off-by: Rafael J. Wysocki <rafael.j.wysocki@intel.com>

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