[Stackless] stackless python in a multicore environment

seun.osewa at gmail.com seun.osewa at gmail.com
Fri Aug 24 11:41:03 CEST 2007

Hello John,

Python doesn't take advantage of multiple CPUs unless you us os.fork()
on UNIX. The deadlock you experienced is probably just the two threads
struggling for the Global Interpreter Lock.  Another (painful) way to
achieve concurrency is to store all your data in a mmaped file
accessible from multiple Python processes.

But there's one other way to speed up your software on a single core:  Psyco!

Seun OSewa

On 8/24/07, Chris Lee <c.j.lee at tnw.utwente.nl> wrote:
> Hi Everyone,
> I suspect that this question has come up before, but a search of the
> archive revealed nothing so please forgive me if you are tired of answering.
> Basically I need some hints on using python (or stackless python) on a
> multi core CPU.
> Let me give some details of the project:
> I am running simulations on light traveling through a very disordered
> medium. I do this using a ballistic approximation, which essentially
> means that I assume the light consists of particles and then generate a
> bunch of random numbers for each particle. I use the random numbers to
> determine the path taken by the particle.
> In practice, I simulate between 1e4 and 1e6 particles at a time taking
> advantage of numpy and python to keep the code clean while still getting
> good speed from a single CPU core. However, the simulations are becoming
> more sophisticated and I would like to be able to take advantage of
> multiple core CPUs and maybe even multiple computers.
> My first attempt was a disaster. I used the threading module and simple
> split the task into two threads. The interpreter put each thread on a
> separate CPU and bus deadlock ensued (each CPU was trying to access
> 136*5e5 bytes of memory simultaneously).
> I realized that I would need finer grained control over how the data was
> apportioned between threads, but doing this using the python queue and
> events starts to look a bit messy again. That was when I happened about
> stackless python and tasklets. With tasklets I get the finegrained
> control over data access that allows to me to ease the bus contention
> ... but all the tasklets run on a single core. Even if I take the
> trouble to spawn python threads and the threads run method invokes a
> tasklet, they all run on the same core.
> Can someone give me some advice towards making use of multicores,
> preferable with stackless--the code is sooo much nicer--but I'll take
> any python based solution at this point.
> Cheers
> Chris
> --
> **********************************************
> *  Chris Lee                                 *
> *  Laser physics and nonlinear optics group  *
> *  MESA+ Institute                           *
> *  University of Twente                      *
> *  Phone: ++31 (0)53 489 3968                *
> *  fax: ++31 (0) 53 489 1102                 *
> **********************************************
> _______________________________________________
> Stackless mailing list
> Stackless at stackless.com
> http://stackless.com/cgi-bin/mailman/listinfo/stackless

Seun Osewa
http://www.nairaland.com [vast Nigerian forum]

Stackless mailing list
Stackless at stackless.com

More information about the Stackless mailing list