[petsc-users] PETSc with modern C++

Tue Apr 4 15:40:32 CDT 2017

I had weird issues where gcc (that I am using for my tests right now)
wasn't vectorising properly (even enabling all flags, from tree-vectorize,
to mavx). According to my tests, I know the Intel compiler was a bit better
at that.

I actually did not know PETSc was doing some unrolling himself. On my
machine, PETSc aligns the memory to 16 bytes, that might also be a cause.
However, I have no idea on the ability of the different compilers to detect
and vectorize codes, even when those are manually unrolled by the user. I
see PETSc unrolls the loop for MAXPY up 4 right hand side vectors. Just by
coincidence, the numbers I reported are actually for this latter case.

I pushed my code to a public git repository. However let me stress that the
code is extremely ugly and buggy. I actually feel shame in showing you the
code :) :
https://bitbucket.org/FilippoL/petscxx/commits/branch/master

If you want to look at the API usage, you can find it in the file
"/src/benchmarks/bench_vector.cpp" after line 153.

If you want the expressions generating the kernels you have to look at the
file "/src/base/vectorexpression.hpp", specifically the "evalat" members.

On Tue, 4 Apr 2017 at 21:39 Matthew Knepley <knepley at gmail.com> wrote:

On Tue, Apr 4, 2017 at 1:19 PM, Filippo Leonardi <filippo.leon at gmail.com>
wrote:

You are in fact right, it is the same speedup  of approximatively 2.5x
(with 2 ranks), my brain rounded up to 3. (This was just a test done in 10
min on my Workstation, so no pretence to be definite, I just wanted to have
an indication).

Hmm, it seems like PetscKernelAXPY4() is just not vectorizing correctly
then. I would be interested to see your code.

As you say, I am using OpenBLAS, so I wouldn't be surprised of those
results. If/when I use MKL (or something similar), I really do not expect
such an improvement).

Since you seem interested (if you are interested, I can give you all the
details): the comparison I make, is with "petscxx" which is my template
code (which uses a single loop) using AVX (I force PETSc to align the
memory to 32 bit boundary and then I use packets of 4 doubles). Also notice
that I use vectors with nice lengths, so there is no need to "peel" the end
of the loop. The "PETSc" simulation is using PETSc's VecMAXPY.

Thanks,

   Matt

On Tue, 4 Apr 2017 at 19:12 Barry Smith <bsmith at mcs.anl.gov> wrote:

  MAXPY isn't really a BLAS 1 since it can reuse some data in certain
vectors.

> On Apr 4, 2017, at 10:25 AM, Filippo Leonardi <filippo.leon at gmail.com>
wrote:
>
> I really appreciate the feedback. Thanks.
>
> That of deadlock, when the order of destruction is not preserved, is a
point I hadn't thought of. Maybe it can be cleverly addressed.
>
> PS: If you are interested, I ran some benchmark on BLAS1 stuff and, for a
single processor, I obtain:
>
> Example for MAXPY, with expression templates:
> BM_Vector_petscxx_MAXPY/8 38 ns 38 ns 18369805
> BM_Vector_petscxx_MAXPY/64 622 ns 622 ns 1364335
> BM_Vector_petscxx_MAXPY/512 281 ns 281 ns 2477718
> BM_Vector_petscxx_MAXPY/4096 2046 ns 2046 ns 349954
> BM_Vector_petscxx_MAXPY/32768 18012 ns 18012 ns 38788
> BM_Vector_petscxx_MAXPY_BigO 0.55 N 0.55 N
> BM_Vector_petscxx_MAXPY_RMS 7 % 7 %
> Direct call to MAXPY:
> BM_Vector_PETSc_MAXPY/8 33 ns 33 ns 20973674
> BM_Vector_PETSc_MAXPY/64 116 ns 116 ns 5992878
> BM_Vector_PETSc_MAXPY/512 731 ns 731 ns 963340
> BM_Vector_PETSc_MAXPY/4096 5739 ns 5739 ns 122414
> BM_Vector_PETSc_MAXPY/32768 46346 ns 46346 ns 15312
> BM_Vector_PETSc_MAXPY_BigO 1.41 N 1.41 N
> BM_Vector_PETSc_MAXPY_RMS 0 % 0 %
>
> And 3x speedup on 2 MPI ranks (not much communication here, anyway). I am
now convinced that this warrants some further investigation/testing.
>
>
> On Tue, 4 Apr 2017 at 01:08 Jed Brown <jed at jedbrown.org> wrote:
> Matthew Knepley <knepley at gmail.com> writes:
>
> >> BLAS. (Here a interesting point opens: I assume an efficient BLAS
> >>
> >> implementation, but I am not so sure about how the different BLAS do
> >> things
> >>
> >> internally. I work from the assumption that we have a very well tuned
BLAS
> >>
> >> implementation at our disposal).
> >>
> >
> > The speed improvement comes from pulling vectors through memory fewer
> > times by merging operations (kernel fusion).
>
> Typical examples are VecMAXPY and VecMDot, but note that these are not
> xGEMV because the vectors are independent arrays rather than single
> arrays with a constant leading dimension.
>
> >> call VecGetArray. However I will inevitably foget to return the array
to
> >>
> >> PETSc. I could have my new VecArray returning an object that restores
the
> >>
> >> array
> >>
> >> when it goes out of scope. I can also flag the function with
[[nodiscard]]
> >> to
> >>
> >> prevent the user to destroy the returned object from the start.
> >>
> >
> > Jed claims that this pattern is no longer preferred, but I have
forgotten
> > his argument.
> > Jed?
>
> Destruction order matters and needs to be collective.  If an error
> condition causes destruction to occur in a different order on different
> processes, you can get deadlock.  I would much rather have an error
> leave some resources (for the OS to collect) than escalate into
> deadlock.
>
> > We have had this discussion for years on this list. Having separate
names
> > for each type
> > is really ugly and does not achieve what we want. We want smooth
> > interoperability between
> > objects with different backing types, but it is still not clear how to
do
> > this.
>
> Hide it internally and implicitly promote.  Only the *GetArray functions
> need to be parametrized on numeric type.  But it's a lot of work on the
> backend.

-- 
What most experimenters take for granted before they begin their
experiments is infinitely more interesting than any results to which their
experiments lead.
-- Norbert Wiener
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