[issue45367] Specialize BINARY_MULTIPLY

[Dennis Sweeney]

Change by Dennis Sweeney :


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resolution:  -> fixed
stage: patch review -> resolved
status: open -> closed

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[issue45367] Specialize BINARY_MULTIPLY

[Mark Shannon]

Mark Shannon  added the comment:


New changeset 3b3d30e8f78271a488965c9cd11136e1aa890757 by Dennis Sweeney in 
branch 'main':
bpo-45367: Specialize BINARY_MULTIPLY (GH-28727)
https://github.com/python/cpython/commit/3b3d30e8f78271a488965c9cd11136e1aa890757


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[issue45367] Specialize BINARY_MULTIPLY

[Mark Shannon]

Mark Shannon  added the comment:

If some misses are caused by mixed int/float operands, it might be worth 
investigating whether these occur in loops.

Most JIT compilers perform some sort of loop peeling to counter this form of 
type instability.

E.g.
x = 0
for ...
x += some_float()

`x` is an int for the first iteration, and a float for the others.


By unpeeling the first iteration, we get type stability in the loop

x = 0
#first iteration
x += some_float()
for ... #Remaining iterations
x += some_float()  # x is always a float here.

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nosy: +Mark.Shannon

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[issue45367] Specialize BINARY_MULTIPLY

[Dennis Sweeney]

Dennis Sweeney  added the comment:

Hm the above was not PGO. I tried again with PGO and it is not so good:

Mean +- std dev: [nbody_main_pgo] 177 ms +- 4 ms -> [nbody_specialized_pgo] 190 
ms +- 2 ms: 1.07x slower
Mean +- std dev: [pidigits_main_pgo] 208 ms +- 1 ms -> 
[pidigits_specialized_pgo] 210 ms +- 2 ms: 1.01x slower
Mean +- std dev: [chaos_main_pgo] 106 ms +- 1 ms -> [chaos_specialized_pgo] 110 
ms +- 1 ms: 1.04x slower
Mean +- std dev: [spectral_norm_main_pgo] 169 ms +- 7 ms -> 
[spectral_norm_specialized_pgo] 167 ms +- 1 ms: 1.02x faster
Benchmark hidden because not significant (1): raytrace

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[issue45367] Specialize BINARY_MULTIPLY

[Ken Jin]

Ken Jin  added the comment:

> (Windows doesn't want to install greenlet for pyperformance)

I had the *exact* same issues, I eventually found a workaround for it after 
many hours spent guessing.

Initially, setuptools complained that I needed MSVC++ 14.0 or later (even after 
I had the latest one installed). I found that for some strange reason, *only* 
14.0 worked, 14.2x etc. don't. After installing MSVC 14.0, there was then some 
strange complaint about missing some .exe/.dll. Searching that entire error 
message led me to a result on StackOverflow advising copying said files from 
the Windows SDK in Visual Studio over to the MSVC 14.0 folder. This finally 
allowed greenlet to compile. I've since lost the exact SO links, but I hope 
this leads you somewhere.

Anyways, I don't recommend benchmarking on Windows for stable results (trust 
me, I've tried ;-). `pyperf system tune` doesn't work on Windows. This leads to 
very inconsistent results unless you manually disable turbo boost, set core 
affinities, etc. Also, PGO for _PyEvalFrameDefaultEx might be broken on Windows 
on the main branch (see issue45116).

Eventually I gave up and just used Linux for stable benchmarking. pyperformance 
`compile_all` also works properly there, which allows you to automate your 
benchmarks 
https://pyperformance.readthedocs.io/usage.html#compile-python-to-run-benchmarks

PS. are your numbers with PGO and LTO? If so, they're spectacular!

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nosy: +kj

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[issue45367] Specialize BINARY_MULTIPLY

[Dennis Sweeney]

Change by Dennis Sweeney :


--
keywords: +patch
pull_requests: +27074
stage:  -> patch review
pull_request: https://github.com/python/cpython/pull/28727

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[issue45367] Specialize BINARY_MULTIPLY

[Dennis Sweeney]

New submission from Dennis Sweeney :

I'm having trouble setting up a rigorous benchmark (Windows doesn't want to 
install greenlet for pyperformance), but just running a couple of individual 
files, I got this:

Mean +- std dev: [nbody_main] 208 ms +- 2 ms -> [nbody_specialized] 180 ms +- 2 
ms: 1.16x faster
Benchmark hidden because not significant (1): pidigits
Mean +- std dev: [chaos_main] 127 ms +- 2 ms -> [chaos_specialized] 120 ms +- 1 
ms: 1.06x faster
Mean +- std dev: [spectral_norm_main] 190 ms +- 10 ms -> 
[spectral_norm_specialized] 175 ms +- 1 ms: 1.09x faster
Mean +- std dev: [raytrace_main] 588 ms +- 48 ms -> [raytrace_specialized] 540 
ms +- 4 ms: 1.09x faster

Hopefully those are accurate.

--
components: Interpreter Core
messages: 403189
nosy: Dennis Sweeney
priority: normal
severity: normal
status: open
title: Specialize BINARY_MULTIPLY
type: performance
versions: Python 3.11

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