[petsc-users] Explicit linking to OpenMP results in performance drop and wrong results

[Matthew Knepley]

On Thu, Feb 18, 2021 at 3:09 AM Roland Richter <roland.richter at ntnu.no>
wrote:

> Hei,
>
> that was the reason for increased run times. When removing #pragma omp
> parallel for, my loop took ~18 seconds. When changing it to #pragma omp
> parallel for num_threads(2) or #pragma omp parallel for num_threads(4) (on
> a i7-6700), the loop took ~16 s, but when increasing it to #pragma omp
> parallel for num_threads(8), the loop took 28 s.
>
> Editorial: This is a reason I think OpenMP is inappropriate as a  tool for
parallel computing (many people disagree). It makes resource management
difficult for the user and impossible for a library.

  Thanks,

     Matt

> Regards,
>
> Roland
> Am 17.02.21 um 18:51 schrieb Matthew Knepley:
>
> Jed, is it possible that this is an oversubscription penalty from bad
> OpenMP settings? <said by a person who knows less about OpenMP than
> cuneiform>
>
>   Thanks,
>
>      Matt
>
> On Wed, Feb 17, 2021 at 12:11 PM Roland Richter <roland.richter at ntnu.no>
> wrote:
>
>> My PetscScalar is complex double (i.e. even higher penalty), but my
>> matrix has a size of 8kk elements, so that should not an issue.
>> Regards,
>> Roland
>> ------------------------------
>> *Von:* Jed Brown <jed at jedbrown.org>
>> *Gesendet:* Mittwoch, 17. Februar 2021 17:49:49
>> *An:* Roland Richter; PETSc
>> *Betreff:* Re: [petsc-users] Explicit linking to OpenMP results in
>> performance drop and wrong results
>>
>> Roland Richter <roland.richter at ntnu.no> writes:
>>
>> > Hei,
>> >
>> > I replaced the linking line with
>> >
>> > //usr/lib64/mpi/gcc/openmpi3/bin/mpicxx  -march=native -fopenmp-simd
>> > -DMKL_LP64 -m64
>> > CMakeFiles/armadillo_with_PETSc.dir/Unity/unity_0_cxx.cxx.o -o
>> > bin/armadillo_with_PETSc
>> > -Wl,-rpath,/opt/boost/lib:/opt/fftw3/lib64:/opt/petsc_release/lib
>> > /usr/lib64/libgsl.so /usr/lib64/libgslcblas.so -lgfortran
>> > -L${MKLROOT}/lib/intel64 -Wl,--no-as-needed -lmkl_intel_lp64
>> > -lmkl_gnu_thread -lmkl_core -lgomp -lpthread -lm -ldl
>> > /opt/boost/lib/libboost_filesystem.so.1.72.0
>> > /opt/boost/lib/libboost_mpi.so.1.72.0
>> > /opt/boost/lib/libboost_program_options.so.1.72.0
>> > /opt/boost/lib/libboost_serialization.so.1.72.0
>> > /opt/fftw3/lib64/libfftw3.so /opt/fftw3/lib64/libfftw3_mpi.so
>> > /opt/petsc_release/lib/libpetsc.so
>> > /usr/lib64/gcc/x86_64-suse-linux/9/libgomp.so
>> > /
>> >
>> > and now the results are correct. Nevertheless, when comparing the loop
>> > in line 26-28 in file test_scaling.cpp
>> >
>> > /#pragma omp parallel for//
>> > //    for(int i = 0; i < r_0 * r_1; ++i)//
>> > //        *(out_mat_ptr + i) = (*(in_mat_ptr + i) * scaling_factor);/
>> >
>> > the version without /#pragma omp parallel/ for is significantly faster
>> > (i.e. 18 s vs 28 s) compared to the version with /omp./ Why is there
>> > still such a big difference?
>>
>> Sounds like you're using a profile to attribute time? Each `omp parallel`
>> region incurs a cost ranging from about a microsecond to 10 or more
>> microseconds depending on architecture, number of threads, and OpenMP
>> implementation. Your loop (for double precision) operates at around 8
>> entries per clock cycle (depending on architecture) if the operands are in
>> cache so the loop size r_0 * r_1 should be at least 10000 just to pay off
>> the cost of `omp parallel`.
>>
>
>
> --
> 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
>
> https://www.cse.buffalo.edu/~knepley/
> <http://www.cse.buffalo.edu/~knepley/>
>
>

-- 
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

https://www.cse.buffalo.edu/~knepley/ <http://www.cse.buffalo.edu/~knepley/>
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