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trans_wasm_func_name.py: Correct function index during translation (#3232)

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Adding the N from "aot_func#N" with the import function count is the correct
wasm function index.
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liang.he 2024-03-18 10:32:55 +08:00 committed by GitHub
parent ff296c1a62
commit 8c1269d44d
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2 changed files with 22 additions and 14 deletions
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23
doc/perf_tune.md
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@ -98,17 +98,22 @@ You should only use this method for well tested wasm applications and make sure
Linux perf is a powerful tool to analyze the performance of a program, developer can use it to find the hot functions and optimize them. It is one profiler supported by WAMR. In order to use it, you need to add `--perf-profile` while running _iwasm_. By default, it is disabled.
> [!CAUTION]
> For now, only llvm-jit mode supports linux-perf.
> For now, only llvm-jit mode and aot mode supports linux-perf.
Here is a basic example, if there is a Wasm application _foo.wasm_, you'll execute.
```
$ perf record --output=perf.data.raw -- iwasm --perf-profile foo.wasm
$ perf record --output=perf.data.raw -- iwasm --enable-linux-perf foo.wasm
```
This will create a _perf.data_ and a _jit-xxx.dump_ under _~/.debug.jit/_ folder. This extra file is WAMR generated at runtime, and it contains the mapping between the JIT code and the original Wasm function names.
This will create a _perf.data_ and
- a _jit-xxx.dump_ under _~/.debug/jit/_ folder if running llvm-jit mode
- or _/tmp/perf-<pid>.map_ if running AOT mode
The next thing need to do is to merge _jit-xxx.dump_ file into the _perf.data_.
This file is WAMR generated. It contains information which includes jitted(precompiled) code addresses in memory, names of jitted (precompiled) functions which are named as *aot_func#N* and so on.
If running with llvm-jit mode, the next thing is to merge _jit-xxx.dump_ file into the _perf.data_.
```
$ perf inject --jit --input=perf.data.raw --output=perf.data
@ -141,28 +146,28 @@ $ perf report --input=perf.data
[Flamegraph](https://www.brendangregg.com/flamegraphs.html) is a powerful tool to visualize stack traces of profiled software so that the most frequent code-paths can be identified quickly and accurately. In order to use it, you need to [capture graphs](https://github.com/brendangregg/FlameGraph#1-capture-stacks) when running `perf record`
```
$ perf record -k mono --call-graph=fp --output=perf.data.raw -- iwasm --perf-profile foo.wasm
$ perf record -k mono --call-graph=fp --output=perf.data.raw -- iwasm --enable-linux-perf foo.wasm
```
merge the _jit-xxx.dump_ file into the _perf.data.raw_.
If running with llvm-jit mode, merge the _jit-xxx.dump_ file into the _perf.data.raw_.
```
$ perf inject --jit --input=perf.data.raw --output=perf.data
```
generate the stack trace file.
Generate the stack trace file.
```
$ perf script > out.perf
```
[fold stacks](https://github.com/brendangregg/FlameGraph#2-fold-stacks).
[Fold stacks](https://github.com/brendangregg/FlameGraph#2-fold-stacks).
```
$ ./FlameGraph/stackcollapse-perf.pl out.perf > out.folded
```
[render a flamegraph](https://github.com/brendangregg/FlameGraph#3-flamegraphpl)
[Render a flamegraph](https://github.com/brendangregg/FlameGraph#3-flamegraphpl)
```
$ ./FlameGraph/flamegraph.pl out.folded > perf.foo.wasm.svg

13
test-tools/trans-jitted-func-name/trans_wasm_func_name.py
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@ -68,6 +68,7 @@ def collect_import_section_content(wasm_objdump_bin: Path, wasm_file: Path) -> d
)
if p.stderr:
print("No content in import section")
return {}
import_section = {}
@ -77,17 +78,19 @@ def collect_import_section_content(wasm_objdump_bin: Path, wasm_file: Path) -> d
if not line:
continue
if line.startswith(" - func"):
import_section.update("function", import_section.get("function", 0) + 1)
if re.search(r"^-\s+func", line):
import_section.update(function=import_section.get("function", 0) + 1)
else:
pass
assert len(import_section) > 0, "failed to retrive content of import section"
return import_section
def collect_name_section_content(wasm_objdump_bin: Path, wasm_file: Path) -> dict:
"""
execute "wasm_objdump_bin -j name -x wasm_file" and store the output in a list
execute "wasm_objdump_bin -j name -x wasm_file" and store the output in a dict
{1: xxxx, 2: yyyy, 3: zzzz}
"""
assert wasm_objdump_bin.exists()
assert wasm_file.exists()
@ -117,7 +120,7 @@ def collect_name_section_content(wasm_objdump_bin: Path, wasm_file: Path) -> dic
assert m
func_index, func_name = m.groups()
name_section.update({func_index: func_name})
name_section.update({int(func_index): func_name})
assert name_section
return name_section
@ -162,7 +165,7 @@ def replace_function_name(
new_line.append(sym)
continue
func_idx = m.groups()[-1]
func_idx = int(m.groups()[-1]) + import_function_count
if func_idx in name_section:
wasm_func_name = f"[Wasm] {name_section[func_idx]}"
else: