[New-bugs-announce] [issue30919] Shared Array Memory Allocation Regression

[Dimitar Tasev]

New submission from Dimitar Tasev:

Hello, I have noticed a significant performance regression when allocating a large shared array in Python 3.x versus Python 2.7. The affected module seems to be `multiprocessing`.

The function I used for benchmarking:

from timeit import timeit
timeit('sharedctypes.Array(ctypes.c_float, 500*2048*2048)', 'from multiprocessing import sharedctypes; import ctypes', number=1)

And the results from executing it:

Python 3.5.2
Out[2]: 182.68500420999771

-------------------

Python 2.7.12
Out[6]: 2.124835968017578

I will try to provide any information you need. Right now I am looking at callgrind/cachegrind without Debug symbols, and can post that, in the meantime I am building Python with Debug and will re-run the callgrind/cachegrind.

Allocating the same-size array with numpy doesn't seem to have a difference between Python versions. The numpy command used was `numpy.full((500,2048,2048), 5.0)`. Allocating the same number of list members also doesn't have a difference - `arr = [5.0]*(500*2048*2048)`

----------
files: shared_array_alloc.py
messages: 298285
nosy: dtasev
priority: normal
severity: normal
status: open
title: Shared Array Memory Allocation Regression
type: performance
versions: Python 2.7, Python 3.5, Python 3.6
Added file: http://bugs.python.org/file47009/shared_array_alloc.py

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Python tracker <report at bugs.python.org>
<http://bugs.python.org/issue30919>
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