Re: [Boost-users] hybrid parallelism

Subject: Re: [Boost-users] hybrid parallelism
From: Brian Budge (brian.budge_at_[hidden])
Date: 2010-11-03 22:14:13

Do these tasks share a lot of data?  If they are really lightwieght
memory-wise, heavy computationally, and don't require fine-grained
communication with each other, I'd go with David's suggestion, as it
will be easier to write, and the performance won't be much different.

If you use a lot of memory, need fine-grained chatter between tasks,
or the tasks are pretty cheap, threads may be (much) better.

  Brian

On Wed, Nov 3, 2010 at 5:19 PM, Hicham Mouline <hicham_at_[hidden]> wrote:
>> -----Original Message-----
>> From: boost-users-bounces_at_[hidden] [mailto:boost-users-
>> bounces_at_[hidden]] On Behalf Of Dave Abrahams
>> Sent: 03 November 2010 23:54
>> To: boost-users_at_[hidden]
>> Subject: Re: [Boost-users] hybrid parallelism
>>
>> On Thu, Nov 4, 2010 at 8:16 AM, Brian Budge <brian.budge_at_[hidden]>
>> wrote:
>> > Hi Hicham -
>> >
>> > Yes, you can use MPI (possibly through boost::mpi) to distribute
>> tasks
>> > to multiple machines, and then use threads on those machines to work
>> > on finer grained portions of those tasks.  From another thread on
>> this
>> > list, there are constructs in boost::asio that handle task queuing
>> for
>> > the thread tasks.
>>
>> If I were you I would start by trying to do this with N processes per
>> machine, rather than N threads, since you need the MPI communication
>> anyway.
>>
>> --
>> Dave Abrahams
>> BoostPro Computing
>> http://www.boostpro.com
>> _______________________________________________
>
> Just temporarily? You would still after that add a layer of multithreading
> to each process, and have only 1 process per machine, after that, no?
>
> A 1 process N threads in 1 machine is probably better total wall time than
> just N mono threaded processes because of the no need to duplicate the input
> memory to the tasks.
>
> The question I really wanted to ask about is that I expect to have M*N
> outstanding threads (M computers, N threads in each process) just sitting
> there waiting for jobs.
> Then from the user interface, I click and that starts 100000 tasks, then it
> is spread all over the M machines and N threads in each process. Then result
> comes back, displayed...
> Then user clicks again and same thing happens.
>
> You're saying this is doable with Boost.MPI + MPI impl?
>
> I wasn't expecting to divide the tasks into finer grained ones. All the
> tasks are atomic and have about the same exec time. It's rather pass
> 100000/M tasks to each machine, then divide this number by N for each thread
> in that process. This last bit is up to me to code.
> Ideally, the task is just a functor with operator() member and M machines
> and N threads are treated similarly. I guess it's up to me to write some
> abstraction layer to view the whole M*N in a flat way.
>
> Other questions, more architectural in nature, I'm not sure they are best
> asked here?
>
> Regards,
>
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