As I said, the degree of impact depends on the messaging pattern. If rank A 
typically sends/recvs with rank A+!, then you won't see much difference. 
However, if rank A typically sends/recvs with rank N-A, where N=#ranks in job, 
then you'll see a very large difference.

You might try simply changing the mapping pattern - e.g., add -bynode to your 
cmd line. This would make it run faster if it followed the latter example.


On Nov 2, 2013, at 12:40 AM, San B <forum....@gmail.com> wrote:

> Yes MM...  But here a single node has 16cores not 64 cores. 
> The 1st two jobs were with OMPI-1.4.5.
>       16 cores of single node - 3692.403
>       16 cores on two nodes (8 cores per node) - 12338.809
> 
> The 1st two jobs were with OMPI-1.6.5.
>       16 cores of single node - 3547.879
>       16 cores on two nodes (8 cores per node) - 5527.320 
> 
>       As others said, due to shared memory communication the single node job 
> is running faster, but I was expecting a slight difference between 1 & 2 
> nodes - which is taking 60% more time here.
> 
> 
> 
> On Thu, Oct 31, 2013 at 8:19 PM, Ralph Castain <r...@open-mpi.org> wrote:
> Yes, though the degree of impact obviously depends on the messaging pattern 
> of the app. 
> 
> On Oct 31, 2013, at 2:50 AM, MM <finjulh...@gmail.com> wrote:
> 
>> Of course, by this you mean, with the same total number of nodes, for e.g. 
>> 64 process on 1 node using shared mem, vs 64 processes spread over 2 nodes 
>> (32 each for e.g.)?
>> 
>> 
>> On 29 October 2013 14:37, Ralph Castain <r...@open-mpi.org> wrote:
>> As someone previously noted, apps will always run slower on multiple nodes 
>> vs everything on a single node due to the shared memory vs IB differences. 
>> Nothing you can do about that one.
>> _______________________________________________
>> 
>> users mailing list
>> us...@open-mpi.org
>> http://www.open-mpi.org/mailman/listinfo.cgi/users
> 
> 
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