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Use wmemchr
in stringlib if sizeof(STRINGLIB_CHAR) == sizeof(wchar_t)
#93033
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Labels
performance
Performance or resource usage
topic-unicode
type-feature
A feature request or enhancement
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Looks like @methane san will have interests in this issue :) |
goldsteinn
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May 21, 2022
This was brought up a bit in python#69009 but the larger issue is mostly different. Generally comparable perf for the "good" case where memchr doesn't return any collisions (false matches on lower byte) but clearly faster with collisions. Some notes on correctness: wchar_t being signed/unsigned shouldn't matter here BUT wmemchr (along with just about all the other wide-char string functions) can and often does (x86_64 for example) assume that the input is aligned relative to the sizeof(wchar_t). If this is not the case for Py_UCS{2|4} then this patch is broken. Also I think the way I implemented `#define STRINGLIB_FAST_MEMCHR` for ucs{2|4}lib break strict-aliasing. If this is an issue but otherwise the patch is fine, any suggestions for how to fix it? Test results: ``` $> ./python -m test -j4 ... == Tests result: SUCCESS == 406 tests OK. 30 tests skipped: test_bz2 test_curses test_dbm_gnu test_dbm_ndbm test_devpoll test_idle test_ioctl test_kqueue test_launcher test_msilib test_nis test_ossaudiodev test_readline test_smtpnet test_socketserver test_sqlite3 test_startfile test_tcl test_tix test_tk test_ttk_guionly test_ttk_textonly test_turtle test_urllib2net test_urllibnet test_winconsoleio test_winreg test_winsound test_xmlrpc_net test_zipfile64 ``` Benchmarked on: model name : 11th Gen Intel(R) Core(TM) i7-1165G7 @ 2.80GHz sizeof(wchar_t) == 4 GLIBC 2.35 ``` ./python -m timeit -s 's = "\U00010200\U00010201\U00010202\U00010203\U00010204\U00010205\U00010206\U00010207\U00010208\U00010209\U0001020a\U0001020b\U0001020c\U0001020d\U0001020e\U0001020f" * 200 + "\U00018200"' -- 's.find("\U00018210")' ## Long, No match, No collision No wmemchr : 1000 loops, best of 100: 127 nsec per loop With wmemchr: 1000 loops, best of 100: 123 nsec per loop ./python -m timeit -s 's = "\U00010200\U00010201\U00010202\U00010203\U00010204\U00010205\U00010206\U00010207\U00010208\U00010209\U0001020a\U0001020b\U0001020c\U0001020d\U0001020e\U0001020f" * 200 + "\U00018200"' -- 's.find("\U00018208")' ## Long, No match, High collision No wmemchr : 1000 loops, best of 100: 1.29 usec per loop With wmemchr: 1000 loops, best of 100: 123 nsec per loop ./python -m timeit -s 's = "\U00010200\U00010201\U00010202\U00010203\U00010204\U00010205\U00010206\U00010207\U00010208\U00010209\U0001020a\U0001020b\U0001020c\U0001020d\U0001020e\U0001020f" * 200 + "\U00018210"' -- 's.find("\U00018210")' ## Long, match, No collision No wmemchr : 1000 loops, best of 100: 136 nsec per loop With wmemchr: 1000 loops, best of 100: 130 nsec per loop ./python -m timeit -s 's = "\U00010200\U00010201\U00010202\U00010203\U00010204\U00010205\U00010206\U00010207\U00010208\U00010209\U0001020a\U0001020b\U0001020c\U0001020d\U0001020e\U0001020f" * 200 + "\U00018208"' -- 's.find("\U00018208")' ## Long, match, High collision No wmemchr : 1000 loops, best of 100: 1.35 usec per loop With wmemchr: 1000 loops, best of 100: 131 nsec per loop ./python -m timeit -s 's = "\U00010200\U00010201\U00010202\U00010203\U00010204\U00010205\U00010206\U00010207\U00010208\U00010209\U0001020a\U0001020b\U0001020c\U0001020d\U0001020e\U0001020f" * 3 + "\U00018200"' -- 's.find("\U00018210")' ## Short, No match, No collision No wmemchr : 1000 loops, best of 100: 50.2 nsec per loop With wmemchr: 1000 loops, best of 100: 52.9 nsec per loop ./python -m timeit -s 's = "\U00010200\U00010201\U00010202\U00010203\U00010204\U00010205\U00010206\U00010207\U00010208\U00010209\U0001020a\U0001020b\U0001020c\U0001020d\U0001020e\U0001020f" * 3 + "\U00018200"' -- 's.find("\U00018208")' ## Short, No match, High collision No wmemchr : 1000 loops, best of 100: 69.1 nsec per loop With wmemchr: 1000 loops, best of 100: 53.7 nsec per loop ./python -m timeit -s 's = "\U00010200\U00010201\U00010202\U00010203\U00010204\U00010205\U00010206\U00010207\U00010208\U00010209\U0001020a\U0001020b\U0001020c\U0001020d\U0001020e\U0001020f" * 3 + "\U00018210"' -- 's.find("\U00018210")' ## Short, match, No collision No wmemchr : 1000 loops, best of 100: 53.6 nsec per loop With wmemchr: 1000 loops, best of 100: 53.6 nsec per loop ./python -m timeit -s 's = "\U00010200\U00010201\U00010202\U00010203\U00010204\U00010205\U00010206\U00010207\U00010208\U00010209\U0001020a\U0001020b\U0001020c\U0001020d\U0001020e\U0001020f" * 3 + "\U00018208"' -- 's.find("\U00018208")' ## Short, match, High collision No wmemchr : 1000 loops, best of 100: 69 nsec per loop With wmemchr: 1000 loops, best of 100: 50.9 nsec per loop ```
methane
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May 24, 2022
Generally comparable perf for the "good" case where memchr doesn't return any collisions (false matches on lower byte) but clearly faster with collisions.
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Labels
performance
Performance or resource usage
topic-unicode
type-feature
A feature request or enhancement
Feature or enhancement
(A clear and concise description of your proposal.)
memchr
is currently used ifsizeof(STRINGLIB_CHAR) == sizeof(char)
because it fasterthan the standard C loops alternatives.
wmemchr
has often roughly the same performance asmemchr
and can be usedin the same way as
memchr
to speedup some of the string functionsSTRINGLIB(find_char)
and
STRINGLIB(replace_1char_inplace)
are the two easiest candidates.Pitch
(Explain why this feature or enhancement should be implemented and how it would be used.
Add examples, if applicable.)
It would, in some instances, make
wide_str.find(wide_str_of_len_one)
faster.Previous discussion
The idea was discussed a bit in #69009 but wasn't the main topic of the issue
or put into any patches.
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