Here we add the ability to save subsystem benchmark results in JSON
format to display them as graphs

To draw graphs, CI team will use
[github-action-benchmark](https://github.com/benchmark-action/github-action-benchmark).
Since we are using custom benchmarks, we need to prepare [a specific
data
type](https://github.com/benchmark-action/github-action-benchmark?tab=readme-ov-file#examples):
```
[
    {
        "name": "CPU Load",
        "unit": "Percent",
        "value": 50
    }
]
```

Then we'll get graphs like this: 

![example](https://raw.githubusercontent.com/rhysd/ss/master/github-action-benchmark/main.png)

[A live page with
graphs](https://benchmark-action.github.io/github-action-benchmark/dev/bench/)

---------

Co-authored-by: ordian <[email protected]>

Adds availability-write regression tests.
The results for the `availability-distribution` subsystem are volatile,
so I had to reduce the precision of the test.

Fixes https://github.com/paritytech/polkadot-sdk/issues/3530

### What's been done
- `subsystem-bench` has been split into two parts: a cli benchmark
runner and a library.
- The cli runner is quite simple. It just allows us to run `.yaml` based
test sequences. Now it should only be used to run benchmarks during
development.
- The library is used in the cli runner and in regression tests. Some
code is changed to make the library independent of the runner.
- Added first regression tests for availability read and write that
replicate existing test sequences.

### How we run regression tests
- Regression tests are simply rust integration tests without the
harnesses.
- They should only be compiled under the `subsystem-benchmarks` feature
to prevent them from running with other tests.
- This doesn't work when running tests with `nextest` in CI, so
additional filters have been added to the `nextest` runs.
- Each benchmark run takes a different time in the beginning, so we
"warm up" the tests until their CPU usage differs by only 1%.
- After the warm-up, we run the benchmarks a few more times and compare
the average with the exception using a precision.

### What is still wrong?
- I haven't managed to set up approval voting tests. The spread of their
results is too large and can't be narrowed down in a reasonable amount
of time in the warm-up phase.
- The tests start an unconfigurable prometheus endpoint inside, which
causes errors because they use the same 9999 port. I disable it with a
flag, but I think it's better to extract the endpoint launching outside
the test, as we already do with `valgrind` and `pyroscope`. But we still
use `prometheus` inside the tests.

### Future work
* https://github.com/paritytech/polkadot-sdk/issues/3528
* https://github.com/paritytech/polkadot-sdk/issues/3529
* https://github.com/paritytech/polkadot-sdk/issues/3530
* https://github.com/paritytech/polkadot-sdk/issues/3531

---------

Co-authored-by: Alexander Samusev <[email protected]>