Richard,
The problem is that OpenMP is too large and has too many different
programming models imbedded in it (and it will get worse) to "support OpenMP"
from PETSc.
One way to use #pragma based optimization tools (which is one way to treat
OpenMP) is to run the application code in a realistic size problem, using the
number of threads/MPI process they prefer with profiling and begin adding
#pragmas to the most time consuming code fragments/routines, measuring the
(small) improvement in performance as they are added. This is the way I would
proceed. The branch generated will not have very many pragmas in it so would
likely be acceptable to be included into PETSc. It would also give a
quantitative measure of the possible performance with the #prama approach.
Note: that for BLAS 1 operations likely the correct thing to do is turn on
MKL BLAS threading (being careful to make sure the number of threads MKL uses
matches that used by other parts of the code). This way we don't need to OpenMP
optimize many parts of PETSc's vector operations (norm, dot, scale, axpy). In
fact, this is the first thing Mark should do, how much does it speed up the
vector operations?
The problem is how many ECP applications actually use OpenMP just as a
#pragma optimization tool, or do they use other features of OpenMP. For example
I remember Brian wanted to/did use OpenMP threads directly in BoxLib and didn't
just stick to the #pragma model. If they did this then we would need custom
PETSc to match their model.
Barry
> On Jul 6, 2018, at 3:07 PM, Mills, Richard Tran <rtmi...@anl.gov> wrote:
>
> True, Barry. But, unfortunately, I think Jed's argument has something to it
> because the hybrid MPI + OpenMP model has become so popular. I know of a few
> codes where adopting this model makes some sense, though I believe that, more
> often, the model has been adopted simply because it is the fashionable thing
> to do. Regardless of good or bad reasons for its adoption, I do have some
> real concern that codes that use this model have a difficult time using PETSc
> effectively because of the lack of thread support. Like many of us, I had
> hoped that endpoints would make it into the MPI standard and this would
> provide a reasonable mechanism for integrating PETSc with codes using
> MPI+threads, but progress on this seems to have stagnated. I hope that the
> MPI endpoints effort eventually goes somewhere, but what can we do in the
> meantime? Within the DOE ECP program, the MPI+threads approach is being
> pushed really hard, and many of the ECP subprojects have adopted it. I think
> it's mostly idiotic, but I think it's too late to turn the tide and convince
> most people that pure MPI is the way to go. Meanwhile, my understanding is
> that we need to be able to support more of the ECP application projects to
> justify the substantial funding we are getting from the program. Many of
> these projects are dead-set on using OpenMP. (I note that I believe that the
> folks Mark is trying to help with PETSc and OpenMP are people affiliated with
> Carl Steefel's ECP subsurface project.)
>
> Since it looks like MPI endpoints are going to be a long time (or possibly
> forever) in coming, I think we need (a) stopgap plan(s) to support this
> crappy MPI + OpenMP model in the meantime. One possible approach is to do
> what Mark is trying with to do with MKL: Use a third party library that
> provides optimized OpenMP implementations of computationally expensive
> kernels. It might make sense to also consider using Karl's ViennaCL library
> in this manner, which we already use to support GPUs, but which I believe
> (Karl, please let me know if I am off-base here) we could also use to provide
> OpenMP-ized linear algebra operations on CPUs as well. Such approaches won't
> use threads for lots of the things that a PETSc code will do, but might be
> able to provide decent resource utilization for the most expensive parts for
> some codes.
>
> Clever ideas from anyone on this list about how to use an adequate number of
> MPI ranks for PETSc while using only a subset of these ranks for the
> MPI+OpenMP application code will be appreciated, though I don't know if there
> are any good solutions.
>
> --Richard
>
> On Wed, Jul 4, 2018 at 11:38 PM, Smith, Barry F. <bsm...@mcs.anl.gov> wrote:
>
> Jed,
>
> You could use your same argument to argue PETSc should do "something" to
> help people who have (rightly or wrongly) chosen to code their application in
> High Performance Fortran or any other similar inane parallel programming
> model.
>
> Barry
>
>
>
> > On Jul 4, 2018, at 11:51 PM, Jed Brown <j...@jedbrown.org> wrote:
> >
> > Matthew Knepley <knep...@gmail.com> writes:
> >
> >> On Wed, Jul 4, 2018 at 4:51 PM Jeff Hammond <jeff.scie...@gmail.com> wrote:
> >>
> >>> On Wed, Jul 4, 2018 at 6:31 AM Matthew Knepley <knep...@gmail.com> wrote:
> >>>
> >>>> On Tue, Jul 3, 2018 at 10:32 PM Jeff Hammond <jeff.scie...@gmail.com>
> >>>> wrote:
> >>>>
> >>>>>
> >>>>>
> >>>>> On Tue, Jul 3, 2018 at 4:35 PM Mark Adams <mfad...@lbl.gov> wrote:
> >>>>>
> >>>>>> On Tue, Jul 3, 2018 at 1:00 PM Richard Tran Mills <rtmi...@anl.gov>
> >>>>>> wrote:
> >>>>>>
> >>>>>>> Hi Mark,
> >>>>>>>
> >>>>>>> I'm glad to see you trying out the AIJMKL stuff. I think you are the
> >>>>>>> first person trying to actually use it, so we are probably going to
> >>>>>>> expose
> >>>>>>> some bugs and also some performance issues. My somewhat limited
> >>>>>>> testing has
> >>>>>>> shown that the MKL sparse routines often perform worse than our own
> >>>>>>> implementations in PETSc.
> >>>>>>>
> >>>>>>
> >>>>>> My users just want OpenMP.
> >>>>>>
> >>>>>>
> >>>>>
> >>>>> Why not just add OpenMP to PETSc? I know certain developers hate it, but
> >>>>> it is silly to let a principled objection stand in the way of enabling
> >>>>> users
> >>>>>
> >>>>
> >>>> "if that would deliver the best performance for NERSC users."
> >>>>
> >>>> You have answered your own question.
> >>>>
> >>>
> >>> Please share the results of your experiments that prove OpenMP does not
> >>> improve performance for Mark’s users.
> >>>
> >>
> >> Oh God. I am supremely uninterested in minutely proving yet again that
> >> OpenMP is not better than MPI.
> >> There are already countless experiments. One more will not add anything of
> >> merit.
> >
> > Jeff assumes an absurd null hypothesis, Matt selfishly believes that
> > users should modify their code/execution environment to subscribe to a
> > more robust and equally performant approach, and the MPI forum abdicates
> > by stalling on endpoints. How do we resolve this?
> >
> >>> Also we are not in the habit of fucking up our codebase in order to follow
> >>>> some fad.
> >>>>
> >>>
> >>> If you can’t use OpenMP without messing up your code base, you probably
> >>> don’t know how to design software.
> >>>
> >>
> >> That is an interesting, if wrong, opinion. It might be your contention that
> >> sticking any random paradigm in a library should
> >> be alright if its "well designed"? I have never encountered such a
> >> well-designed library.
> >>
> >>
> >>> I guess if you refuse to use _Pragma because C99 is still a fad for you,
> >>> it is harder, but clearly _Complex is tolerated.
> >>>
> >>
> >> Yes, littering your code with preprocessor directives improves almost
> >> everything. Doing proper resource management
> >> using Pragmas, in an environment with several layers of libraries, is a
> >> dream.
> >>
> >>
> >>> More seriously, you’ve adopted OpenMP hidden behind MKL
> >>>
> >>
> >> Nope. We can use MKL with that crap shutoff.
> >>
> >>
> >>> so I see no reason why you can’t wrap OpenMP implementations of the PETSc
> >>> sparse kernels in a similar manner.
> >>>
> >>
> >> We could, its just a colossal waste of time and effort, as well as
> >> counterproductive for the codebase :)
> >
> > Endpoints either need to become a thing we can depend on or we need a
> > solution for users that insist on using threads (even if their decision
> > to use threads is objectively bad). The problem Matt harps on is
> > legitimate: OpenMP parallel regions cannot reliably cross module
> > boundaries except for embarrassingly parallel operations. This means
> > loop-level omp parallel which significantly increases overhead for small
> > problem sizes (e.g., slowing coarse grid solves and strong scaling
> > limits). It can be done and isn't that hard, but the Imperial group
> > discarded their branch after observing that it also provided no
> > performance benefit. However, I'm coming around to the idea that PETSc
> > should do it so that there is _a_ solution for users that insist on
> > using threads in a particular way. Unless Endpoints become available
> > and reliable, in which case we could do it right.
>
>
