That's one possible way of achieving the overlap. However, it's not a portable solution as right now from all open source libraries, only Open MPI propose this "helper" thread (as far as I know).

Another way of achieving the same goal, it's to have a truly thread safe MPI library and the user will have a thread blocked in a MPI_Recv that will eventually complete at the end of the application. This approach, seems more user friendly, as the user is in control of when the overlap will occur.

  george.

On Oct 15, 2007, at 2:56 PM, Eric Thibodeau wrote:

George,

For completedness's sake, from what I understand here, the only way to get "true" communications and computation overlap is to have and "MPI broker" thread which would take care of all communications in the form of sync MPI calls. It is that thread which you call asynchronously and then let it manage the communications in the back... correct?

Eric

Le October 15, 2007, George Bosilca a écrit :
Eric,

No there is no documentation about this on Open MPI. However, what I
described here, is not related to Open MPI, it's a general problem
with most/all MPI libraries. There are multiple scenarios where non
blocking communications can improve the overall performance of a
parallel application. But, in general, the reason is related to
overlapping communications with computations, or communications with
communications.

The problem is that using non blocking will increase the critical
path compared with blocking, which usually never help at improving
performance. Now I'll explain the real reason behind that. The REAL
problem is that usually a MPI library cannot make progress while the
application is not in an MPI call. Therefore, as soon as the MPI
library return after posting the non-blocking send, no progress is
possible on that send until the user goes back in the MPI library. If
you compare this with the case of a blocking send, there the library
do not return until the data is pushed on the network buffers, i.e.
the library is the one in control until the send is completed.

   Thanks,
     george.

On Oct 15, 2007, at 2:23 PM, Eric Thibodeau wrote:

Hello George,

        What you're saying here is very interesting. I am presently
profiling communication patterns for Parallel Genetic Algorithms
and could not figure out why the async versions tended to be worst
than the sync counterpart (imho, that was counter-intuitive). What
you're basically saying here is that the async communications
actually add some sychronization overhead that can only be
compensated if the application overlaps computation with the async
communications? Is there some "official" reference/documentation to
this behaviour from OpenMPI (I know the MPI standard doesn't define
the actual implementation of the communications and therefore lets
the implementer do as he pleases).

Thanks,

Eric

Le October 15, 2007, George Bosilca a écrit :
Your conclusion is not necessarily/always true. The MPI_Isend is just the non blocking version of the send operation. As one can imagine, a
MPI_Isend + MPI_Wait increase the execution path [inside the MPI
library] compared with any blocking point-to-point communication,
leading to worst performances. The main interest of the MPI_Isend
operation is the possible overlap of computation with communications,
or the possible overlap between multiple communications.

However, depending on the size of the message this might not be true. For large messages, in order to keep the memory usage on the receiver
at a reasonable level, a rendezvous protocol is used. The sender
[after sending a small packet] wait until the receiver confirm the
message exchange (i.e. the corresponding receive operation has been
posted) to send the large data. Using MPI_Isend can lead to longer
execution times, as the real transfer will be delayed until the
program enter in the next MPI call.

In general, using non-blocking operations can improve the performance
of the application, if and only if the application is carefully
crafted.

   george.

On Oct 14, 2007, at 2:38 PM, Jeremias Spiegel wrote:

Hi,
I'm working with Open-Mpi on an infiniband-cluster and have some
strange
effect when using MPI_Isend(). To my understanding this should
always be
quicker than MPI_Send() and MPI_Ssend(), yet in my program both
MPI_Send()
and MPI_Ssend() reproducably perform quicker than SSend(). Is there
something
obvious I'm missing?

Regards,
Jeremias
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Eric Thibodeau
Neural Bucket Solutions Inc.
T. (514) 736-1436
C. (514) 710-0517





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Eric Thibodeau
Neural Bucket Solutions Inc.
T. (514) 736-1436
C. (514) 710-0517

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