Dear Xing Feng,

there are different algorithms to implement collective communication
patterns. Next to general Big-O complexity the concrete complexity
also depends on the network topology, message length, etc..

Therefore many MPI implementations switch between different algorithms
depending on the concrete communication parameters in a call.

A colleague of mine investigated some MPI implementations (though not
OpenMPI) [1]. There you can see how different MPI implementations
(IBM, ParaStation, Cray) scale differently for a selection of
collective calls. Maybe that helps a little in understanding the
performance of your application.

Cheers,
Marc-Andre

[1] http://dl.acm.org/citation.cfm?doid=2751205.2751216


On 30.09.15 07:53, XingFENG wrote:
> Hi, every one,
> 
> I am working with open-mpi. When I tried to analyse performance of my
> programs, I find it is hard to understand the communication complexity
> of MPI routines.
> 
> I have found some page on Internet such as
> http://stackoverflow.com/questions/10625643/mpi-communication-complexity
> 
> 
> This indicates that communication complexity of broadcasting an
> integer is O(log P) where P is the number of processes. But is it
> correct on different MPI implementations( OMPI, MPICH, etc.)? Is there
> an official document discussing such complexity?
> 
> 
> -- 
> Best Regards.
> ---
> Xing FENG
> PhD Candidate
> Database Research Group
> 
> School of Computer Science and Engineering
> University of New South Wales
> NSW 2052, Sydney
> 
> Phone: (+61) 413 857 288
> 
> 
> _______________________________________________
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> Link to this post: 
> http://www.open-mpi.org/community/lists/users/2015/09/27719.php
> 

-- 
Marc-Andre Hermanns
Jülich Aachen Research Alliance,
High Performance Computing (JARA-HPC)
German Research School for Simulation Sciences GmbH

Schinkelstrasse 2
52062 Aachen
Germany

Phone: +49 2461 61 2509
Fax: +49 241 80 6 99753
www.grs-sim.de/parallel
email: m.a.herma...@grs-sim.de

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