* Introduce Coefficient of variation aggregate
I believe, it is much more useful / use to understand,
because it is already normalized by the mean,
so it is not affected by the duration of the benchmark,
unlike the standard deviation.
Example of real-world output:
```
raw.pixls.us-unique/GoPro/HERO6 Black$ ~/rawspeed/build-old/src/utilities/rsbench/rsbench GOPR9172.GPR --benchmark_repetitions=27 --benchmark_display_aggregates_only=true --benchmark_counters_tabular=true
2021-09-03T18:05:56+03:00
Running /home/lebedevri/rawspeed/build-old/src/utilities/rsbench/rsbench
Run on (32 X 3596.16 MHz CPU s)
CPU Caches:
L1 Data 32 KiB (x16)
L1 Instruction 32 KiB (x16)
L2 Unified 512 KiB (x16)
L3 Unified 32768 KiB (x2)
Load Average: 7.00, 2.99, 1.85
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Benchmark Time CPU Iterations CPUTime,s CPUTime/WallTime Pixels Pixels/CPUTime Pixels/WallTime Raws/CPUTime Raws/WallTime WallTime,s
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
GOPR9172.GPR/threads:32/process_time/real_time_mean 11.1 ms 353 ms 27 0.353122 31.9473 12M 33.9879M 1085.84M 2.83232 90.4864 0.0110535
GOPR9172.GPR/threads:32/process_time/real_time_median 11.0 ms 352 ms 27 0.351696 31.9599 12M 34.1203M 1090.11M 2.84336 90.8425 0.0110081
GOPR9172.GPR/threads:32/process_time/real_time_stddev 0.159 ms 4.60 ms 27 4.59539m 0.0462064 0 426.371k 14.9631M 0.0355309 1.24692 158.944u
GOPR9172.GPR/threads:32/process_time/real_time_cv 1.44 % 1.30 % 27 0.0130136 1.44633m 0 0.0125448 0.0137802 0.0125448 0.0137802 0.0143795
```
Fixes https://github.com/google/benchmark/issues/1146
* Be consistent, it's CV, not 'rel std dev'
This is related to @BaaMeow's work in https://github.com/google/benchmark/pull/616 but is not based on it.
Two new fields are tracked, and dumped into JSON:
* If the run is an aggregate, the aggregate's name is stored.
It can be RMS, BigO, mean, median, stddev, or any custom stat name.
* The aggregate-name-less run name is additionally stored.
I.e. not some name of the benchmark function, but the actual
name, but without the 'aggregate name' suffix.
This way one can group/filter all the runs,
and filter by the particular aggregate type.
I *might* need this for further tooling improvement.
Or maybe not.
But this is certainly worthwhile for custom tooling.
Roman Lebedev