On 29/11/2023 12:08, Lukasz Luba wrote:
Hi all,
This patch set adds a new feature which allows to modify Energy Model (EM)
power values at runtime. It will allow to better reflect power model of
a recent SoCs and silicon. Different characteristics of the power usage
can be leveraged and thus better decisions made during task placement in EAS.
It's part of feature set know as Dynamic Energy Model. It has been presented
and discussed recently at OSPM2023 [3]. This patch set implements the 1st
improvement for the EM.
The concepts:
1. The CPU power usage can vary due to the workload that it's running or due
to the temperature of the SoC. The same workload can use more power when the
temperature of the silicon has increased (e.g. due to hot GPU or ISP).
In such situation the EM can be adjusted and reflect the fact of increased
power usage. That power increase is due to static power
(sometimes called simply: leakage). The CPUs in recent SoCs are different.
We have heterogeneous SoCs with 3 (or even 4) different microarchitectures.
They are also built differently with High Performance (HP) cells or
Low Power (LP) cells. They are affected by the temperature increase
differently: HP cells have bigger leakage. The SW model can leverage that
knowledge.
2. It is also possible to change the EM to better reflect the currently
running workload. Usually the EM is derived from some average power values
taken from experiments with benchmark (e.g. Dhrystone). The model derived
from such scenario might not represent properly the workloads usually running
on the device. Therefore, runtime modification of the EM allows to switch to
a different model, when there is a need.
3. The EM can be adjusted after boot, when all the modules are loaded and
more information about the SoC is available e.g. chip binning. This would help
to better reflect the silicon characteristics. Thus, this EM modification
API allows it now. It wasn't possible in the past and the EM had to be
'set in stone'.
More detailed explanation and background can be found in presentations
during LPC2022 [1][2] or in the documentation patches.
Some test results.
The EM can be updated to fit better the workload type. In the case below the EM
has been updated for the Jankbench test on Pixel6 (running v5.18 w/ mainline backports
for the scheduler bits). The Jankbench was run 10 times for those two configurations,
to get more reliable data.
1. Janky frames percentage
+--------+-----------------+---------------------+-------+-----------+
| metric | variable | kernel | value | perc_diff |
+--------+-----------------+---------------------+-------+-----------+
| gmean | jank_percentage | EM_default | 2.0 | 0.0% |
| gmean | jank_percentage | EM_modified_runtime | 1.3 | -35.33% |
+--------+-----------------+---------------------+-------+-----------+
2. Avg frame render time duration
+--------+---------------------+---------------------+-------+-----------+
| metric | variable | kernel | value | perc_diff |
+--------+---------------------+---------------------+-------+-----------+
| gmean | mean_frame_duration | EM_default | 10.5 | 0.0% |
| gmean | mean_frame_duration | EM_modified_runtime | 9.6 | -8.52% |
+--------+---------------------+---------------------+-------+-----------+
3. Max frame render time duration
+--------+--------------------+---------------------+-------+-----------+
| metric | variable | kernel | value | perc_diff |
+--------+--------------------+---------------------+-------+-----------+
| gmean | max_frame_duration | EM_default | 251.6 | 0.0% |
| gmean | max_frame_duration | EM_modified_runtime | 115.5 | -54.09% |
+--------+--------------------+---------------------+-------+-----------+
4. OS overutilized state percentage (when EAS is not working)
+--------------+---------------------+------+------------+------------+
| metric | wa_path | time | total_time | percentage |
+--------------+---------------------+------+------------+------------+
| overutilized | EM_default | 1.65 | 253.38 | 0.65 |
| overutilized | EM_modified_runtime | 1.4 | 277.5 | 0.51 |
+--------------+---------------------+------+------------+------------+
5. All CPUs (Little+Mid+Big) power values in mW
+------------+--------+---------------------+-------+-----------+
| channel | metric | kernel | value | perc_diff |
+------------+--------+---------------------+-------+-----------+
| CPU | gmean | EM_default | 142.1 | 0.0% |
| CPU | gmean | EM_modified_runtime | 131.8 | -7.27% |
+------------+--------+---------------------+-------+-----------+
The time cost to update the EM decreased in this v5 vs v4:
big: 5us vs 2us -> 2.6x faster
mid: 9us vs 3us -> 3x faster
little: 16us vs 16us -> no change
I guess this is entirely due to the changes in
em_dev_update_perf_domain()? Moving from per-OPP em_update_callback to
switching the entire table (pd->runtime_table) inside
em_dev_update_perf_domain()?
We still have to update the inefficiency in the cpufreq framework, thus
a bit of overhead will be there.
Changelog:
v5:
- removed 2 tables design
- have only one table (runtime_table) used also in thermal (Wei, Rafael)
Until v4 you had 2 EM's, the static and the modifiable (runtime). Now in
v5 this changed to only have one, the modifiable. IMHO it would be
better to change the existing table to be modifiable rather than staring
with two EM's and then removing the static one. I assume you end up with
way less code changes and the patch-set will become easier to digest for
reviewers.
I would mention that 14/23 "PM: EM: Support late CPUs booting and
capacity adjustment" is a testcase for the modifiable EM build-in into
the code changes. This relies on the table being modifiable.