b3418103e9
Move the SVG rendering code to modules/svg, and componentize.
Also split into include/src/utils.
As external clients still reference the old header locations,
introduce temporary forwarding headers to facilitate the migration.
This reverts commit
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| .. | ||
| __init__.py | ||
| _adb_path.py | ||
| _adb.py | ||
| _benchresult.py | ||
| _hardware_android.py | ||
| _hardware_nexus_6p.py | ||
| _hardware_pixel2.py | ||
| _hardware_pixel_c.py | ||
| _hardware_pixel.py | ||
| _hardware.py | ||
| _os_path.py | ||
| README.md | ||
| sheet.py | ||
| skiaperf.py | ||
| skpbench.cpp | ||
| skpbench.py | ||
skpbench
skpbench is a benchmarking tool for replaying skp or mksp files on android devices. it achieves a lower variance in framerate by controlling the clock speed and stopping all other processes that could cause interference.
Build
skpbench consists of the skpbench binary which must be built for the phone you intend to run on, and skpbench.py which runs on the machine the phone is connected to via ADB and is the entry point.
The to build skia for android are at https://skia.org/user/build#android and reproduced here.
Download the Android NDK
cipd auth-login
python2 infra/bots/assets/android_ndk_linux/download.py -t /tmp/ndk
After this is set up once, build skpbench for your target cpu (assumed to be arm64 here for a Pixel 3)
bin/gn gen out/arm64 --args='ndk="/tmp/ndk" target_cpu="arm64" is_debug=false'
ninja -C out/arm64 skpbench
Benchmark an SKP on a connected device.
First, copy the built skpbench binary and an example skp file to the device.
adb push out/arm64/skpbench /data/local/tmp
adb push /home/nifong/Downloads/foo.skp /data/local/tmp/skps/
Run skpbench.py (in my case on a Pixel 3)
python tools/skpbench/skpbench.py \
--adb \
--force \
--config gles \
/data/local/tmp/skpbench \
/data/local/tmp/skps/foo.skp
--adb specifies that it should use adb to the only connected device and run skpbench there.
--force is necessary because we don't yet have a configuration to monitor vitals on the Pixel 3.
--config gles specifies Open GL ES is the backend GPU config to use.
Additional documentation of arguments is printed by python tools/skpbench/skpbench.py --help
Output appears in the following format
accum median max min stddev samples sample_ms clock metric config bench
0.1834 0.1832 0.1897 0.1707 1.59% 101 50 cpu ms gles foo.skp
accum is the time taken to draw all frames, divided by the number of frames.
metric specifies that the unit is ms (milliseconds per frame)
Production
skpbench is run as a tryjob from gerrit, where it uploads the results to perf.skia.org. TODO(nifong, csmartdalton): elaborate on this section.