➜

This issue tracker has been migrated to GitHub, and is currently read-only.
For more information, see the GitHub FAQs in the Python's Developer Guide.

classification
Title: multiprocessing won't utilize all of platform resources
Type: behavior Stage:
Components: Windows Versions: Python 3.6
process
Status: open Resolution:
Dependencies: Superseder:
Assigned To: Nosy List: paul.moore, steve.dower, tim.golden, yanirh, zach.ware
Priority: normal Keywords:

Created on 2018-03-28 14:56 by yanirh, last changed 2022-04-11 14:58 by admin.

Messages (1)
msg314600 - (view) Author: yanir hainick (yanirh) Date: 2018-03-28 14:56 
I'm using either multiprocessing package or concurrent.futures for some embarrassingly parallel application.

I performed a simple test: basically making n_jobs calls for a simple function - 'sum(list(range(n)))', with n large enough so that the operation is a few seconds long - where n_jobs > n_logical_cores.

Tried it on two platforms:

first platform:
server with X4 Intel Xeon E5-4620 (8 physical, 16 logical), running 
a 64bit Windows Server 2012 R2 Standard.

***

second platform:
server with X2 Intel Xeon Gold 6138 (20 physical, 40 logical), running a 64bit Windows Server 2016 Standard.

***

first platform reaches 100% utilization.
second platform reaches 25% utilization.
History
Date User Action Args
2022-04-11 14:58:59adminsetgithub: 77352
2018-03-28 14:56:29yanirhcreate