It's entirely possible, especially if libgomp is being mixed with libiomp. Roland hasn't show us the compilation line (just linker), because `omp parallel` shouldn't do anything with just -fopenmp-simd and no -fopenmp.
Matthew Knepley <[email protected]> writes: > 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 <[email protected]> > 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 <[email protected]> >> *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 <[email protected]> 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/>
