README.md
1 Turbolizer
2 ==========
3
4 Turbolizer is a HTML-based tool that visualizes optimized code along the various
5 phases of Turbofan's optimization pipeline, allowing easy navigation between
6 source code, Turbofan IR graphs, scheduled IR nodes and generated assembly code.
7
8 Turbolizer consumes .json files that are generated per-function by d8 by passing
9 the '--trace-turbo' command-line flag.
10
11 Turbolizer is build using npm:
12
13 npm i
14 npm run-script build
15
16 Afterwards, turbolizer can be hosted locally by starting a web server that serve
17 the contents of the turbolizer directory, e.g.:
18
19 cd src/tools/turbolizer
20 python -m SimpleHTTPServer 8000
21
22 Optionally, profiling data generated by the perf tools in linux can be merged
23 with the .json files using the turbolizer-perf.py file included. The following
24 command is an example of using the perf script:
25
26 perf script -i perf.data.jitted -s turbolizer-perf.py turbo-main.json
27
28 The output of the above command is a json object that can be piped to a file
29 which, when uploaded to turbolizer, will display the event counts from perf next
30 to each instruction in the disassembly. Further detail can be found in the
31 bottom of this document under "Using Perf with Turbo."
32
33 Using the python interface in perf script requires python-dev to be installed
34 and perf be recompiled with python support enabled. Once recompiled, the
35 variable PERF_EXEC_PATH must be set to the location of the recompiled perf
36 binaries.
37
38 Graph visualization and manipulation based on Mike Bostock's sample code for an
39 interactive tool for creating directed graphs. Original source is at
40 https://github.com/metacademy/directed-graph-creator and released under the
41 MIT/X license.
42
43 Icons derived from the "White Olive Collection" created by Breezi released under
44 the Creative Commons BY license.
45
46 Using Perf with Turbo
47 ---------------------
48
49 In order to generate perf data that matches exactly with the turbofan trace, you
50 must use either a debug build of v8 or a release build with the flag
51 'disassembler=on'. This flag ensures that the '--trace-turbo' will output the
52 necessary disassembly for linking with the perf profile.
53
54 The basic example of generating the required data is as follows:
55
56 perf record -k mono /path/to/d8 --trace-turbo --perf-prof main.js
57 perf inject -j -i perf.data -o perf.data.jitted
58 perf script -i perf.data.jitted -s turbolizer-perf.py turbo-main.json
59
60 These commands combined will run and profile d8, merge the output into a single
61 'perf.data.jitted' file, then take the event data from that and link them to the
62 disassembly in the 'turbo-main.json'. Note that, as above, the output of the
63 script command must be piped to a file for uploading to turbolizer.
64
65 There are many options that can be added to the first command, for example '-e'
66 can be used to specify the counting of specific events (default: cycles), as
67 well as '--cpu' to specify which CPU to sample.
68
69 Turbolizer build process
70 ------------------------
71
72 Turbolizer is currently migrating to TypeScript. The typescript sources reside in
73 tools/turbolizer/src, and the typescript compiler will put the JavaScript output
74 into tools/turbolizer/build/. The index.html file is set up to load the JavaScript
75 from that directory.
76