Hi Pavan and Jeff, Thanks a lot for your answers. I feel there is something to tell about mpi standard expectations... Why does the knowledge (or ignorance) of MPI users about scalability of communications in MPI should be a requirement for them for developing high-performance MPI applications? Especially when we want to keep it simple by using high-level MPI functionalities, like MPI_gather, and let the library do the best work it can... In other words, why the complexity (then scalability) of MPI algorithms is not guaranteed by the standard? If every one that is familiar with performance of MPI communication have the burden to write MPI calls in a way that it is scaling/performing well, isn't all of us rewriting essentially the same "good" code that should be in the standard? Is the standard voluntarily blind to these (crucial) questions? I may be too naive too... tell me! :) (ie, the c++ standard guarantee the sort algorithm complexity: https://en.wikipedia.org/wiki/Sort_%28C%2B%2B%29) On 21/10/15 10:03 PM, Balaji, Pavan wrote:
You might want to join the collectives working group and voice your opinion over there.
Ok, where exactly do I do this? Btw, I don't want to blame anybody... I am just learning and discussing here!!! :) Thanks for reading! Eric On 21/10/15 11:56 PM, Jeff Hammond wrote:
Depending on the size of your data, you could pipeline a series of MPI_Igather calls and process all of the data associated with the partial buffer. Of course, this will change the layout of the buffer at the root unless you do something interesting with datatypes (e.g. struct with offset). This may or may not matter, if you are going to process it anyways.
In general, I think you may be able to do just fine with rolling your own. It's a myth that using higher-level functionality in MPI is _always_ better.
Jeff
On Wed, Oct 21, 2015 at 7:03 PM, Balaji, Pavan <[email protected] <mailto:[email protected]>> wrote:
Eric,
The concept of partial completion of collectives did come up in the Forum, but the Forum decided that it was rather unnatural to define Iallgather/Igather that way. So we decided to standardize it the way it is.
However, there is a separate proposal for streaming collectives, which is more along the lines of what you are thinking of. That's obviously not in MPI-3, but might be considered for a future MPI. You might want to join the collectives working group and voice your opinion over there.
With respect to writing your own igather implementation, as long as your implementation is logarithmic, it won't be too bad. However, a native implementation inside MPI would almost certainly do better because: (1) it can take advantage of platform-specific features to improve performance, and (2) if the platform doesn't give anything special, it'll anyway do exactly what you are doing above MPI.
So, apart from any performance bugs that the implementation might have, using MPI Igather would be the recommended mechanism for the best performance.
-- Pavan
On 10/21/15, 2:45 PM, "Eric Chamberland" <[email protected] <mailto:[email protected]>> wrote:
>Hi, > >A long time ago (in 2002) we programmed here a non-blocking MPI_Igather >with equivalent calls to MPI_Isend/MPI_Irecv (see the 2 attached files). > >A very convenient advantage of this version, is that I can do some work >on the root process as soon as it start receiving data... Then, it wait >for the next communication to terminate and process the received data. > >Now, I am looking at MPI_Igather (and all non-blocking collective MPI >calls), and I am somewhat surprised (or ignorant) that I cannot have the >root rank receive some data, then process it, then wait until the next >"MPI_irecv" terminate... > >In other words, a MPI_Igather generate only 1 MPI_Request but I would >like to have either "p" (with p = size of communicator) MPI_Request >generated or be able to call "p" times MPI_WaitAny with the same >MPI_Request... Am I normal? :) > >So my 3 questions are: > >#1- Is there a way to use MPI_Igather with MPI_WaitAny (or something >else?) to process data as it is received? > >#2- Big question: will our implementation with MPI_Isend/MPI_Irecv scale >to a large number of processes? What are the possible drawbacks of >doing it like we did? > >#3- Why should I replace our implementation by the native MPI_Igather? > >Thanks! > >Eric _______________________________________________ discuss mailing list [email protected] <mailto:[email protected]> To manage subscription options or unsubscribe: https://lists.mpich.org/mailman/listinfo/discuss
-- Jeff Hammond [email protected] <mailto:[email protected]> http://jeffhammond.github.io/
_______________________________________________ discuss mailing list [email protected] To manage subscription options or unsubscribe: https://lists.mpich.org/mailman/listinfo/discuss