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Add return const instruction #101632
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Execution counts for all instructions in the main branch
Name Count Self Cumulative Miss ratio LOAD_CONST 4,447,532,233 4.7% 24.4% RETURN_VALUE 3,241,585,933 3.4% 43.2% And execution counts for all instructions in my branch
Name Count Self Cumulative Miss ratio LOAD_CONST 3,477,437,602 3.7% 31.5% RETURN_VALUE 2,268,077,678 2.4% 47.3% RETURN_CONST 967,592,289 1.0% 69.3% I have executed pyperformance on my server, compare to commit d3e2dd6
python3 -m pyperf compare_to --table --min-speed 5 /python-3.12.0/results.json results.json +---------------------+---------------------------------------+-----------------------+ | Benchmark | python-3.12.0/results.json | results.json | +=====================+=======================================+=======================+ | coverage | 378 ms | 360 ms: 1.05x faster | +---------------------+---------------------------------------+-----------------------+ | crypto_pyaes | 87.2 ms | 82.5 ms: 1.06x faster | +---------------------+---------------------------------------+-----------------------+ | logging_silent | 108 ns | 94.3 ns: 1.15x faster | +---------------------+---------------------------------------+-----------------------+ | pickle_pure_python | 352 us | 330 us: 1.07x faster | +---------------------+---------------------------------------+-----------------------+ | regex_v8 | 26.8 ms | 23.8 ms: 1.12x faster | +---------------------+---------------------------------------+-----------------------+ | richards | 54.6 ms | 51.7 ms: 1.06x faster | +---------------------+---------------------------------------+-----------------------+ | scimark_lu | 125 ms | 133 ms: 1.07x slower | +---------------------+---------------------------------------+-----------------------+ | scimark_monte_carlo | 83.3 ms | 74.3 ms: 1.12x faster | +---------------------+---------------------------------------+-----------------------+ | spectral_norm | 118 ms | 112 ms: 1.06x faster | +---------------------+---------------------------------------+-----------------------+ | sqlglot_parse | 1.71 ms | 1.61 ms: 1.06x faster | +---------------------+---------------------------------------+-----------------------+ | sqlglot_transpile | 2.00 ms | 1.89 ms: 1.06x faster | +---------------------+---------------------------------------+-----------------------+ | unpickle_list | 4.73 us | 5.06 us: 1.07x slower | +---------------------+---------------------------------------+-----------------------+ | Geometric mean | (ref) | 1.01x faster | +---------------------+---------------------------------------+-----------------------+ Benchmark hidden because not significant (68): 2to3, async_generators, async_tree_none, async_tree_cpu_io_mixed, async_tree_io, async_tree_memoization, chameleon, chaos, bench_mp_pool, bench_thread_pool, coroutines, deepcopy, deepcopy_reduce, deepcopy_memo, deltablue, django_template, docutils, dulwich_log, fannkuch, float, generators, genshi_text, genshi_xml, go, hexiom, html5lib, json_dumps, json_loads, logging_format, logging_simple, mako, mdp, meteor_contest, nbody, nqueens, pathlib, pickle, pickle_dict, pickle_list, pidigits, pprint_safe_repr, pprint_pformat, pyflate, python_startup, python_startup_no_site, raytrace, regex_compile, regex_dna, regex_effbot, scimark_fft, scimark_sor, scimark_sparse_mat_mult, sqlglot_optimize, sqlglot_normalize, sqlite_synth, sympy_expand, sympy_integrate, sympy_sum, sympy_str, telco, tornado_http, unpack_sequence, unpickle, unpickle_pure_python, xml_etree_parse, xml_etree_iterparse, xml_etree_generate, xml_etree_processAlthough the performance gain may not be high, the side effects are minimal and should be a positive optimization.
Reacted by Frank Dana- added a commit that references this issue
on Feb 7, 2023
From the pystats doc (pystats-2023-02-05-python-5a2b984.md), I find that
LOAD_CONST + RETURN_VALUEis a very high frequency (Because the default return of the function is None).Successors for LOAD_CONST
And predecessors for RETURN_VALUE
This means that if we add a
RETURN_CONST, we can reduce theRETURN_VALUEinstruction by 30% and theLOAD_CONSTinstruction by 20%.From the microbenchmark that there is indeed a ~10% improvement (considering the interference of function calls, I think 10% should be there), which is not very high, but it should be an optimization without adverse effects.
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