This family of python scripts can be incredibly useful for fast iteration over different performance tweaks. The tools allow you to save performance data from a baseline commit, then quickly compare data from your working branch to that baseline data to see if you have made any performance wins.
The tools operate with three concrete steps, which can be invoked separately, or all together via the driver script, bm_main.py. This readme will describe the typical workflow for these scripts, then it will include sections on the details of every script for advanced usage.
Let's say you are working on a performance optimization for grpc_error. You have made some significant changes and want to see some data. From your branch, run (ensure everything is committed first):
tools/profiling/microbenchmarks/bm_diff/bm_main.py -b bm_error -l 5 -d master
This will build the bm_error binary on your branch, and then it will checkout master and build it there too. It will then run these benchmarks 5 times each. Lastly it will compute the statistically significant performance differences between the two branches. This should show the nice performance wins your changes have made.
If you have already invoked bm_main with -d master, you should instead use -o for subsequent runs. This allows the script to skip re-building and re-running the unchanged master branch. For example:
tools/profiling/microbenchmarks/bm_diff/bm_main.py -b bm_error -l 5 -o
This will only build and run bm_error on your branch. It will then compare the output to the saved runs from master.
If you have a deeper knowledge of these scripts, you can use them to do more fine tuned benchmark comparisons. For example, you could build, run, and save the benchmark output from two different base branches. Then you could diff both of these baselines against your working branch to see how the different metrics change. The rest of this doc goes over the details of what each of the individual modules accomplishes.
This scrips builds the benchmarks. It takes in a name parameter, and will store the binaries based on that. Both opt and counter configurations will be used. The opt is used to get cpu_time and real_time, and the counters build is used to track other metrics like allocs, atomic adds, etc etc etc.
For example, if you were to invoke (we assume everything is run from the root of the repo):
tools/profiling/microbenchmarks/bm_diff/bm_build.py -b bm_error -n baseline
then the microbenchmark binaries will show up under bm_diff_baseline/{opt,counters}/bm_error
This script runs the benchmarks. It takes a name parameter that must match the name that was passed to bm_build.py. The script then runs the benchmark multiple times (default is 20, can be toggled via the loops parameter). The output is saved as <benchmark name>.<config>.<name>.<loop idx>.json
For example, if you were to run:
tools/profiling/microbenchmarks/bm_diff/bm_run.py -b bm_error -b baseline -l 5
Then an example output file would be bm_error.opt.baseline.0.json
This script takes in the output from two benchmark runs, computes the diff between them, and prints any significant improvements or regressions. It takes in two name parameters, old and new. These must have previously been built and run.
For example, assuming you had already built and run a ‘baseline’ microbenchmark from master, and then you also built and ran a ‘current’ microbenchmark from the branch you were working on, you could invoke:
tools/profiling/microbenchmarks/bm_diff/bm_diff.py -b bm_error -o baseline -n current -l 5
This would output the percent difference between your branch and master.
This is the driver script. It uses the previous three modules and does everything for you. You pass in the benchmarks to be run, the number of loops, number of CPUs to use, and the commit to compare to. Then the script will:
For example, one might run:
tools/profiling/microbenchmarks/bm_diff/bm_main.py -b bm_error -l 5 -d master
This would compare the current branch's error benchmarks to master.
This script is invoked by our infrastructure on every PR to protect against regressions and demonstrate performance wins.
However, if you are iterating over different performance tweaks quickly, it is unnecessary to build and run the baseline commit every time. That is why we provide a different flag in case you are sure that the baseline benchmark has already been built and run. In that case use the --old flag to pass in the name of the baseline. This will only build and run the current branch. For example:
tools/profiling/microbenchmarks/bm_diff/bm_main.py -b bm_error -l 5 -o old