Dear Derek,

Because of the adaptive mesh evolution, the dimension of the final matrix is
~360,000*360,000 (sparse matrix).
However, I am wondering why the cost time of the parallel_sort() increases
very quickly. Thanks.

Regards,
Yujie

On Thu, Feb 11, 2010 at 4:07 PM, Derek Gaston <[email protected]> wrote:

> How large is your problem??  If libMesh is dominating your solve time...
> then you're problem probably isn't large enough to be distributed over so
> many processors.
>
> Derek
>
> On Feb 11, 2010, at 2:53 PM, Yujie wrote:
>
> > Hi, Libmesh Developers,
> >
> > When I run the codes in parallel mode, I found the performance is not
> always
> > improved with the increase of the CPU number. I tried to find the
> bottleneck
> > using the libmesh performance table. I found the problem is from Mesh
> > Communication::parallel_sort().
> > At the beginning (from 2 to 14 CPUs), the cost time of Mesh Communication
> > takes a small percentage of the total time (Check the following table).
> > However, when the CPU number changes larger than 14, the performance of
> Mesh
> > Communication becomes worse, especially parallel_sort().  I don't know
> > whether it is normal. Could you give me some advice? Thanks a lot.
> >
> > Although there are 8 CPUs in one node of the cluster, each CPU added  is
> > from different nodes compared with previous one by using "-machinefile "
> in
> > MPI when I add the CPU.
> >
> >          CPUs               Mesh Communication
> > 1
> > 0  2
> > 2.6  3
> > 2.6  4
> > 2.7  5
> > 2.7  6
> > 2.7  8
> > 2.9  10
> > 2.6  12
> > 3.4  14
> > 4.2  16
> > 7.2  18
> > 7.2  20
> > 8.7  22
> > 9.5  24
> > 13.8  26
> > 15.3  28
> > 19.4  30
> > 24.2  32
> > 34.6  34
> > 32.4  36
> > 36.6  38
> > 39.1  40
> > 46.9
> > Regards,
> > Yujie
> >
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