HarfBuzz text shaping engine http://harfbuzz.github.io/
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Behdad Esfahbod 8a7cfe1787 [perf/benchmark-shape] Test ft font backend as well 3 years ago
..
fonts [perf] Make subset benchmark data driven. 3 years ago
texts Rename HBGlyphID to HBGlyphID16 3 years ago
Makefile.am [perf] Add benchmark-ot 3 years ago
README.md [perf] Add missing ninja command in profiling instructions. 3 years ago
benchmark-font.cc [perf/benchmark-shape] Allow taking text-file/font-file args from cmdline 3 years ago
benchmark-map.cc [benchmark-map] Remove rand() overhead from benchmark 3 years ago
benchmark-ot.cc [perf/benchmark-ot] Add zh-hans 3 years ago
benchmark-set.cc [benchmark-set] Add benchmark for set copy 3 years ago
benchmark-shape.cc [perf/benchmark-shape] Test ft font backend as well 3 years ago
benchmark-subset.cc [perf/benchmark-subset] Minor cleanup 3 years ago
meson.build [perf/benchmark-shape] Test ft font backend as well 3 years ago
run.sh Merge pull request #2733 from astiob/buffer-context-doc 4 years ago

README.md

Building and Running

Benchmarks are implemented using Google Benchmark.

To build the benchmarks in this directory you need to set the benchmark option while configuring the build with meson:

meson configure build -Dbenchmark=enabled --buildtype=release

Then build the benchmark binaries with ninja:

ninja -Cbuild perf/benchmark-set

Finally, to run one of the benchmarks:

./build/perf/benchmark-set

It's possible to filter the benchmarks being run and customize the output via flags to the benchmark binary. See the Google Benchmark User Guide for more details.

Profiling

Configure the build to include debug information for profiling:

CXXFLAGS="-fno-omit-frame-pointer" meson --reconfigure build -Dbenchmark=enabled --buildtype=debug
ninja -Cbuild

Then run the benchmark with perf:

perf record -g -o ~/tmp/profiles/subset.prof ./build/perf/benchmark-subset --benchmark_filter="BM_subset_codepoints/subset_notocjk/100000" --benchmark_repetitions=5

You probably want to filter to a specific benchmark of interest and set the number of repititions high enough to get a good sampling of profile data.

Finally view the profile with:

perf report -i ~/tmp/profiles/subset.prof