1Turbolizer 2========== 3 4Turbolizer is a HTML-based tool that visualizes optimized code along the various 5phases of Turbofan's optimization pipeline, allowing easy navigation between 6source code, Turbofan IR graphs, scheduled IR nodes and generated assembly code. 7 8Turbolizer consumes .json files that are generated per-function by d8 by passing 9the '--trace-turbo' command-line flag. 10 11Host the turbolizer locally by starting a web server that serves the contents of 12the turbolizer directory, e.g.: 13 14 cd src/tools/turbolizer 15 python -m SimpleHTTPServer 8000 16 17Optionally, profiling data generated by the perf tools in linux can be merged 18with the .json files using the turbolizer-perf.py file included. The following 19command is an example of using the perf script: 20 21 perf script -i perf.data.jitted -s turbolizer-perf.py turbo-main.json 22 23The output of the above command is a json object that can be piped to a file 24which, when uploaded to turbolizer, will display the event counts from perf next 25to each instruction in the disassembly. Further detail can be found in the 26bottom of this document under "Using Perf with Turbo." 27 28Using the python interface in perf script requires python-dev to be installed 29and perf be recompiled with python support enabled. Once recompiled, the 30variable PERF_EXEC_PATH must be set to the location of the recompiled perf 31binaries. 32 33Graph visualization and manipulation based on Mike Bostock's sample code for an 34interactive tool for creating directed graphs. Original source is at 35https://github.com/metacademy/directed-graph-creator and released under the 36MIT/X license. 37 38Icons derived from the "White Olive Collection" created by Breezi released under 39the Creative Commons BY license. 40 41Using Perf with Turbo 42--------------------- 43 44In order to generate perf data that matches exactly with the turbofan trace, you 45must use either a debug build of v8 or a release build with the flag 46'disassembler=on'. This flag ensures that the '--trace-turbo' will output the 47necessary disassembly for linking with the perf profile. 48 49The basic example of generating the required data is as follows: 50 51 perf record -k mono /path/to/d8 --turbo --trace-turbo --perf-prof main.js 52 perf inject -j -i perf.data -o perf.data.jitted 53 perf script -i perf.data.jitted -s turbolizer-perf.py turbo-main.json 54 55These commands combined will run and profile d8, merge the output into a single 56'perf.data.jitted' file, then take the event data from that and link them to the 57disassembly in the 'turbo-main.json'. Note that, as above, the output of the 58script command must be piped to a file for uploading to turbolizer. 59 60There are many options that can be added to the first command, for example '-e' 61can be used to specify the counting of specific events (default: cycles), as 62well as '--cpu' to specify which CPU to sample.