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Serhiy Storchaka:
>> * json: scanstring_unicode()
>
> This doesn't look wise. This is specific to single extension module and perhaps to single particular benchmark. Most Python code don't use json at all.
Well, I tried different things to make these benchmarks more stable. I didn't say that we should merge hot3.patch as it is :-) It's just an attempt.
> What is the top of "perf report"?
For json_loads, it's:
 14.99% _json.cpython-37m-x86_64-linux-gnu.so scanstring_unicode
 8.34% python _PyUnicode_FromUCS1
 8.32% _json.cpython-37m-x86_64-linux-gnu.so scan_once_unicode
 8.01% python lookdict_unicode_nodummy
 6.72% python siphash24
 4.45% python PyDict_SetItem
 4.26% python _PyObject_Malloc
 3.38% python _PyEval_EvalFrameDefault
 3.16% python _Py_HashBytes
 2.72% python PyUnicode_New
 2.36% python PyLong_FromString
 2.25% python _PyObject_Free
 2.02% libc-2.19.so __memcpy_sse2_unaligned
 1.61% python PyDict_GetItem
 1.40% python dictresize
 1.24% python unicode_hash
 1.11% libc-2.19.so _int_malloc
 1.07% python unicode_dealloc
 1.00% python free_keys_object
Result produced with:
 $ perf record ./python ~/performance/performance/benchmarks/bm_json_loads.py --worker -v -l 128 -w0 -n 100 
 $ perf report 
> How this list intersects with the list of functions in .text.hot section of PGO build?
I checked which functions are considered as "hot" by a PGO build: I found more than 2,000 functions... I'm not interested to tag so many functions with _Py_HOT_FUNCTIONS. I would prefer to only tag something like the top 10 or top 25 functions.
I don't know the recommandations to tag functions as hot. I guess that what matters is the total size of hot functions. Should I be smaller than the L2 cache? Smaller than the L3 cache? I'm talking about instructions, but data share also these caches...
> Make several PGO builds (perhaps on different computers). Is .text.hot section stable?
In my experience PGO builds don't provide stable performances, but I was never able to write an article on that because of so many bugs :-)