22ec1bc787
Allow the user to specify the range of instructions that are shown on the live ranges grid so as to ease performance issues. Bug: v8:7327 Change-Id: I431e4464155427f59adf3a2229806c6f11c471be Reviewed-on: https://chromium-review.googlesource.com/c/v8/v8/+/4110973 Commit-Queue: George Wort <george.wort@arm.com> Reviewed-by: Nico Hartmann <nicohartmann@chromium.org> Cr-Commit-Position: refs/heads/main@{#85186} |
||
|---|---|---|
| .. | ||
| css | ||
| img | ||
| src | ||
| test | ||
| deploy.sh | ||
| index.html | ||
| info-view.html | ||
| OWNERS | ||
| package-lock.json | ||
| package.json | ||
| README.md | ||
| rollup.config.js | ||
| tsconfig.json | ||
| tsconfig.test.json | ||
| tsfmt.json | ||
| tslint.json | ||
| turbolizer.png | ||
Turbolizer
Turbolizer is a HTML-based tool that visualizes optimized code along the various phases of Turbofan's optimization pipeline, allowing easy navigation between source code, Turbofan IR graphs, scheduled IR nodes and generated assembly code.
Turbolizer consumes .json files that are generated per-function by d8 by passing the '--trace-turbo' command-line flag.
Turbolizer is build using npm:
cd tools/turbolizer
npm i
npm run-script build
Afterwards, turbolizer can be hosted locally by starting a web server that serve the contents of the turbolizer directory, e.g.:
python -m SimpleHTTPServer 8000
To deploy to a directory that can be hosted the script deploy can be used. The
following command will deploy to the directory /www/turbolizer:
npm run deploy -- /www/turbolizer
Optionally, profiling data generated by the perf tools in linux can be merged with the .json files using the turbolizer-perf.py file included. The following command is an example of using the perf script:
perf script -i perf.data.jitted -s turbolizer-perf.py turbo-main.json
The output of the above command is a json object that can be piped to a file which, when uploaded to turbolizer, will display the event counts from perf next to each instruction in the disassembly. Further detail can be found in the bottom of this document under "Using Perf with Turbo."
Using the python interface in perf script requires python-dev to be installed and perf be recompiled with python support enabled. Once recompiled, the variable PERF_EXEC_PATH must be set to the location of the recompiled perf binaries.
Graph visualization and manipulation based on Mike Bostock's sample code for an interactive tool for creating directed graphs. Original source is at https://github.com/metacademy/directed-graph-creator and released under the MIT/X license.
Icons derived from the "White Olive Collection" created by Breezi released under the Creative Commons BY license.
Using Perf with Turbo
In order to generate perf data that matches exactly with the turbofan trace, you must use either a debug build of v8 or a release build with the flag 'disassembler=on'. This flag ensures that the '--trace-turbo' will output the necessary disassembly for linking with the perf profile.
The basic example of generating the required data is as follows:
perf record -k mono /path/to/d8 --trace-turbo --perf-prof main.js
perf inject -j -i perf.data -o perf.data.jitted
perf script -i perf.data.jitted -s turbolizer-perf.py turbo-main.json
These commands combined will run and profile d8, merge the output into a single 'perf.data.jitted' file, then take the event data from that and link them to the disassembly in the 'turbo-main.json'. Note that, as above, the output of the script command must be piped to a file for uploading to turbolizer.
There are many options that can be added to the first command, for example '-e' can be used to specify the counting of specific events (default: cycles), as well as '--cpu' to specify which CPU to sample.
Turbolizer build process
The typescript sources reside in tools/turbolizer/src, and the typescript compiler will put the JavaScript output into tools/turbolizer/build/. The index.html file is set up to load the JavaScript from that directory.