[Python-Dev] Issue #11051: system calls per import

Jussi Enkovaara jussi.enkovaara at csc.fi
Mon Jan 31 11:50:27 CET 2011

On 2011-01-30 21:43, "Martin v. Löwis" wrote:
> Am 30.01.2011 17:54, schrieb Alexander Belopolsky:
>> On Sun, Jan 30, 2011 at 11:35 AM, Victor Stinner
>> <victor.stinner at haypocalc.com>  wrote:
>> ..
>>> We should find a compromise between speed (limit the number of system
>>> calls) and the usability of Python modules.
>> Do you have measurements that show python spending significant time on
>> failing open calls?
> No; past measurements always showed that this is insignificant, probably
> thanks to operating system caching the relevant directory blocks (so
> it doesn't really matter whether you make one or ten lookups per
> directory; my guess is that it matters more if you look into ten
> directories instead of one).

Dear Python-developers,
I would like you to be aware of one particular problem related to the system calls 
in massively parallel systems. We are developing a Python-based simulation software 
GPAW (https://wiki.fysik.dtu.dk/gpaw/) and tested it with up to tens of thousands 
of CPU cores. The program uses MPI, thus thousands of Python interpreters are 
launched at start-up time. As all these interpreters execute the same import 
statements, the huge amount of (IO-related) system calls puts extreme pressure to 
the file system, and as result just starting the Python interpreter(s) can take ~45 
minutes with ~30 000 CPU cores!

Currently, we have tried to work around the problem either by installing Python and 
required additional modules (NumPy and GPAW) to a ramdisk, or by modifying the 
CPython source (at the moment 2.6 version) in such a way that only single process 
performs the system calls and uses MPI to broadcast the results to other processes 
(preliminary work in progress).

As a related problem, dynamic linking can also be quite expensive (or even not 
available in some systems), and in some cases we have made a small hack to CPython 
for enabling statically linked packages (simple modules can of course be included 
relatively easily in static Python build.)

I am not expecting that the problems can be solved easily for the general CPython 
interpreter, especially as massively parallel supercomputers are quite small niche 
of Python usage. However, I think it would be good to be aware of problems with 
large amount of system calls in a more special Python usage.

Best regards,
Jussi Enkovaara, Application Scientist, High Performance Computing, CSC
PO. BOX 405 02101 Espoo, Finland, Tel +358 9 457 2935, fax +358 9 457 2302
CSC - IT Center for Science, www.csc.fi, e-mail: jussi.enkovaara at csc.fi

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