Hi George,
First, let me note that the cost of q^(k-1)]*(q-1) communicators was fine
for the values of parameters q,k I am working with. Also, the whole point
of speeding up the shuffling phase is trying to reduce this number even
more (compared to already known implementations) which is a major concern
of my project. But thanks for pointing that out. Btw, do you know what is
the maximum such number in MPI?
Now to the main part of the question, let me clarify that I have 1 process
per machine. I don't know if this is important here but my way of thinking
is that we have a big text file and each process will have to work on some
chunks of it (like chapters of a book). But each process resides in an
machine with some RAM which is able to handle a specific amount of work so
if you generate many processes per machine you must have fewer book
chapters per process than before. Thus, I wanted to avoid thinking in the
process-level rather than machine-level with the RAM limitations.
Now to the actual shuffling, here is what I am currently doing (Option 1):
Let's denote the data that slave s has to send to the slaves in group G as
D(s,G).
*for each slave s in 1,2,...,K{*
* for each group G that s participates into{*
* if (my rank is s){*
* MPI_Bcast(send data D(s,G))*
* }else if(my rank is in group G)*
* MPI_Bcast(get data D(s,G))*
* }else{*
* Do nothing*
* }*
* }*
*MPI::COMM_WORLD.Barrier();*
*}*
What I suggested before to speedup things (Option 2) is:
*for each set {G(1),G(2),...,G(q-1)} of q-1 disjoint groups{ *
* for each slave s in G(1)*
* if (my rank is s){*
* MPI_Bcast(send data D(s,G(1)))*
* }else if(**my rank is in** group G(1))*
* MPI_Bcast(get data D(s,G(1)))*
* }else{*
* Do nothing*
* }*
* }*
* for each slave s in G(2)*
* if (my rank is s){*
* MPI_Bcast(send data D(s,G(2)))*
* }else if(**my rank is in** G(2))*
* MPI_Bcast(get data D(s,G(2)))*
* }else{*
* Do nothing*
* }*
* }*
* ...*
*for each slave s in G(q-1)*
* if (my rank is s){*
* MPI_Bcast(send data D(s,G(q-1)))*
* }else if(**my rank is in** G(q-1))*
* MPI_Bcast(get data D(s,G(q-1)))*
* }else{*
* Do nothing*
* }*
* }*
* MPI::COMM_WORLD.Barrier();*
*}*
My hope was that I could implement Option 2 (in some way without copying
and pasting the same code q-1 times every time I change q) and that this
could bring a speedup of q-1 compared to Option 1 by having these groups
communicate in parallel. Right, now I am trying to find a way to identify
these sets of groups based on my implementation, which involves some
abstract algebra but for now let's assume that I can find them in an
efficient manner.
Let me emphasize that each broadcast sends different actual data. There are
no two broadcasts that send the same D(s,G).
Finally, let's go to MPI_Allgather(): I am really confused since I have
never used this call but I have this image in my mind:
I am not sure what you meant but now I am thinking of this (let commG be
the intra-communicator of group G):
*for each possible group G{*
*if (my rank is in G){*
* commG.MPI_AllGather(**send data D(rank,G)**)*
* }**else{*
* Do nothing*
* }*
*MPI::COMM_WORLD.Barrier();*
*}*
I am not sure whether this makes sense since I am confused about the
correspodence of the data transmitted with Allgather() compared to the
notation D(s,G) I am currently using.
Thanks.
On Tue, Oct 31, 2017 at 11:11 PM, George Bosilca <bosi...@icl.utk.edu>
wrote:
> It really depends what are you trying to achieve. If the question is
> rhetorical: "can I write a code that does in parallel broadcasts on
> independent groups of processes ?" then the answer is yes, this is
> certainly possible. If however you add a hint of practicality in your
> question "can I write an efficient parallel broadcast between independent
> groups of processes?" then I'm afraid the answer will be a negative one.
>
> Let's not look at how you can write the multiple bcast code as the answer
> in the stackoverflow is correct, but instead look at what resources these
> collective operations are using. In general you can assume that nodes are
> connected by a network, able to move data at a rate B in both directions
> (full duplex). Assuming the implementation of the bcast algorithm is not
> entirely moronic, the bcast can saturate the network with a single process
> per node. Now, if you have multiple processes per node (P) then either you
> schedule them sequentially (so that each one has the full bandwidth B) or
> you let them progress in parallel in which case each participating process
> can claim a lower bandwidth B/P (as it is shared between all processes on
> the nore).
>
> So even if you are able to expose enough parallelism, physical resources
> will impose the real hard limit.
>
> That being said I have the impression you are trying to implement an
> MPI_Allgather(v) using a series of MPI_Bcast. Is that true ?
>
> George.
>
> PS: Few other constraints: the cost of creating the q^(k-1)]*(q-1)
> communicator might be prohibitive; the MPI library might support a limited
> number of communicators.
>
>
> On Tue, Oct 31, 2017 at 11:42 PM, Konstantinos Konstantinidis <
> kostas1...@gmail.com> wrote:
>
>> Assume that we have K=q*k nodes (slaves) where q,k are positive integers
>> >= 2.
>>
>> Based on the scheme that I am currently using I create [q^(k-1)]*(q-1)
>> groups (along with their communicators). Each group consists of k nodes and
>> within each group exactly k broadcasts take place (each node broadcasts
>> something to the rest of them). So in total [q^(k-1)]*(q-1)*k MPI
>> broadcasts take place. Let me skip the details of the above scheme.
>>
>> Now theoretically I figured out that there are q-1 groups that can
>> communicate in parallel at the same time i.e. groups that have no common
>> nodes and I would like to utilize that to speedup the shuffling. I have
>> seen here https://stackoverflow.com/questions/11372012/mpi-severa
>> l-broadcast-at-the-same-time that this is possible in MPI.
>>
>> In my case it's more complicated since q,k are parameters of the problem
>> and change between different experiments. If I get the idea about the 2nd
>> method that is proposed there and assume that we have only 3 groups within
>> which some communication takes places one can simply do:
>>
>> *if my rank belongs to group 1{*
>> * comm1.Bcast(..., ..., ..., rootId);*
>> *}else if my rank belongs to group 2{*
>> * comm2.Bcast(..., ..., ..., rootId);*
>> *}else if my rank belongs to group3{*
>> * comm3.Bcast(..., ..., ..., rootId);*
>> *} *
>>
>> where comm1, comm2, comm3 are the corresponding sub-communicators that
>> contain only the members of each group.
>>
>> But how can I generalize the above idea to arbitrary number of groups or
>> perhaps do something else?
>>
>> The code is in C++ and the MPI installed is described in the attached
>> file.
>>
>> Regards,
>> Kostas
>>
>>
>> _______________________________________________
>> users mailing list
>> users@lists.open-mpi.org
>> https://lists.open-mpi.org/mailman/listinfo/users
>>
>
>
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