This is a summary of what was discussed at the Performance Tracking and
Benchmarking Infrastructure BoF session last week at the LLVM dev meeting.
At the same time it contains a proposal on a few next steps to improve the
setup and use of buildbots to track performance changes in code generated by
The buildbots currently are very valuable in detecting correctness regressions,
and getting the community to quickly rectify those regressions. However,
performance regressions are hardly noted and it seems as a community, we don’t
really keep track of those well.
The goal for the BoF was to try and find a number of actions that could take us
closer to the point where as a community, we would at least notice some of the
performance regressions and take action to fix the regressions. Given that
this has been discussed already quite a few times at previous BoF sessions at
multiple developer meetings, we thought we should aim for a small, incremental,
but sure improvement over the current status. Ideally, we should initially aim
for getting to the point where at least some of the performance regressions are
detected and acted upon.
We already have a central database that stores benchmarking numbers, produced
for 2 boards, see
seems no-one monitors the produced results, nor is it easy to derive from those
numbers if a particular patch really introduced a significant regression.
At the BoF, we identified the following issues blocking us from being able to
detect significant regressions more easily:
- A lot of the Execution Time and Compile Time results are very noisy, because
the individual programs don’t run long enough and don’t take long enough to
compile (e.g. less than 0.1 seconds).
- The proposed actions to improve the execution time is, for the programs
under the Benchmarks sub-directories in the test-suite, to:
a) increase the run time of the benchmark so it runs long enough to avoid
noisy results. “Long enough” probably means roughly 10 seconds. We’d
probably need a number of different settings, or a parameter that can
be set per program, so that the running time on individual boards can
be tuned. E.g. on a faster board, more iterations would be run than on
a slower board.
b) evaluate if the main running time of the benchmark is caused by running
code compiled or by something else, e.g. file IO. Programs dominated by
file IO shouldn’t be used to track performance changes over time.
The proposal to resolve this is to create a way to run the test suite in
‘benchmark mode’, which includes only a subset of the test suite useful
for benchmarking. Hal Finkel volunteered to start this work.
- The identified action to improve the compile time measurements is to just
add up the compilation time for all benchmarks and measure that, instead
of the compile times of the individual benchmarks.
It seems this could be implemented by simply changing or adding a view
in the web interface, showing the trend of the compilation time for all
benchmarks over time, rather than trend graphs for individual programs.
- Furthermore, on each individual board, the noise introduced by the board
itself should be minimized. Each board should have a maintainer, who ensures
the board doesn’t produce a significant level of noise.
If the board starts producing a high level of noise, and the maintainer
doesn’t fix it quickly, the performance numbers coming from the board will
be ignored. It’s not clear what the best way would be to mark a board as
The suggestion was made that board maintainers could get a script to run
before each benchmarking run, to check whether the board seems in a
reasonable state, e.g. by checking the load on the board is near zero; “dd”
executes as fast as expected; … It’s expected that the checks in the
script might be somewhat dependent on the operating system the board
- To reduce the noise levels further, it would be nice if the execution time
of individual benchmarks could be averaged out over a number (e.g. 5)
consecutive runs. That way, each individual benchmark run remains
relatively fast, by having to run each program just once; while at the same
time the averaging should reduce some of the insignificant noise in the
I’d appreciate any feedback on the above proposals. We’re also looking for more
volunteers to implement the above improvements; so if you’re interested in
working on some of the above, please let us know.