No speedup with OpenMP when using Matlab MEX in Linux - linux

Question

I'm using OpenMP to speed up Fortran code in a Matlab MEX-file. However, I find that OpenMP seems not work on Linux, but actually works on Windows. I attach the code as follows:
1) Matlab Mex file:
clc; clear all; close all; tic
FLAG_SYS = 0; % 0 for Windows; 1 for Linux
%--------------------------------------------------------------------------
% Mex Fortran code
%--------------------------------------------------------------------------
if FLAG_SYS == 0
mex COMPFLAGS="-Qopenmp $COMPFLAGS"...
LINKFLAGS="/Qopenmp $LINKFLAGS"...
OPTIMFLAGS="/Qopenmp $OPTIMFLAGS"...
'-IC:\Program Files (x86)\IntelSWTools\compilers_and_libraries_2017.5.267\windows\mkl\include'...
'-LC:\Program Files (x86)\IntelSWTools\compilers_and_libraries_2017.5.267\windows\mkl\lib\intel64'...
-lmkl_intel_ilp64.lib -lmkl_intel_thread.lib -lmkl_core.lib libiomp5md.lib...
Test_OpenMP_Mex.f90...
-output Test_OpenMP_Mex
elseif FLAG_SYS == 1
mex COMPFLAGS="-fopenmp $COMPFLAGS"...
LINKFLAGS="-fopenmp $LINKFLAGS"...
FFLAGS='$FFLAGS -fdec-math -cpp' ...
'-I${MKLROOT}/include'...
'-L${MKLROOT}/lib'...
-lmkl_avx2 -lmkl_gf_ilp64 -lmkl_core -lmkl_intel_thread -liomp5 -lpthread -lm -ldl...
Test_OpenMP_Mex.f90...
-output Test_OpenMP_Mex
end
Test_OpenMP_Mex;
2) Fortran code
#include "fintrf.h"
!GATEWAY ROUTINE
SUBROUTINE MEXFUNCTION(NLHS, PLHS, NRHS, PRHS)
!DECLARATIONS
IMPLICIT NONE
!MEXFUNCTION ARGUMENTS:
MWPOINTER PLHS(*), PRHS(*)
INTEGER NLHS, NRHS
!FUNCTION DECLARATIONS:
MWPOINTER MXCREATEDOUBLEMATRIX
MWPOINTER MXGETM, MXGETN
INTEGER MXISNUMERIC
!POINTERS TO INPUT MXARRAYS:
MWPOINTER MIV1, MIV2
!POINTERS TO OUTPUT MXARRAYS:
MWPOINTER MOV1, MOV2
!CALL FORTRAN CODE
CALL TEST_OPENMP
RETURN
END
!-----------------------------------------------------------------------
SUBROUTINE TEST_OPENMP
USE OMP_LIB
IMPLICIT NONE
INTEGER I, J, K, STEP
REAL*8 STARTTIME, ENDTIME,Y
OPEN(1,FILE='1.TXT')
!COUNT ELAPSED TIME START
STARTTIME = OMP_GET_WTIME()
DO I = 1,1000000
DO J = 1,50000
DO K = 1,1000
Y=(I+10)*J-SQRT(789.1)+SQRT(789.1)-(I+10)*J
END DO
END DO
END DO
ENDTIME = OMP_GET_WTIME()
WRITE(1,*) ENDTIME-STARTTIME
!COUNT ELAPSED TIME START
STARTTIME = OMP_GET_WTIME()
!$OMP PARALLEL
!$OMP DO PRIVATE(I,J)
DO I = 1,1000000
DO J = 1,50000
DO K = 1,1000
Y=(I+10)*J-SQRT(789.1)+SQRT(789.1)-(I+10)*J
END DO
END DO
END DO
!$OMP END DO
!$OMP END PARALLEL
ENDTIME = OMP_GET_WTIME()
WRITE(1,*) ENDTIME-STARTTIME
!$OMP PARALLEL
! GET THE NUMBER OF THREADS
WRITE(1,*) OMP_GET_THREAD_NUM(), OMP_GET_NUM_THREADS()
!$OMP END PARALLEL
CLOSE(1)
RETURN
END SUBROUTINE TEST_OPENMP
The output on Windows is:
1.09620520001044
4.50355500000296
0 6
1 6
3 6
5 6
2 6
4 6
and the output on Linux is:
0.0000
0.0000
0 1
It's obvious that OpenMP works on Windows, since the calculation time reduces from 4.5s to 1.0s. I can find that there are 6 threads being used for calculation. However, on Linux, no calculation seems to be executed, and there are only 2 threads (the number of threads on Linux is 36, but only 2 of them are used).
Any suggestions are welcome!
You can directly download code from this link:
https://www.dropbox.com/sh/crkuwhu22407sjs/AAAQrtzAvTmFOmAxv_jpTCBaa?dl=0

Answer 1

When compiling MEX-files under Linux (and MacOS) the COMPFLAGS variable is ignored. It is a Windows-specific environment variable. You need to use CFLAGS for C, CXXFLAGS for C++, or FFLAGS for Fortran, and LDFLAGS for the linker. These are the standard Unix environment variables to control compilation.
Your compile command will look like this:
mex LDFLAGS='-fopenmp $LDFLAGS'...
FFLAGS='-fopenmp -fdec-math -cpp $FFLAGS' ...
'-I${MKLROOT}/include'...
'-L${MKLROOT}/lib'...
-lmkl_avx2 -lmkl_gf_ilp64 -lmkl_core -lmkl_intel_thread -liomp5 -lpthread -lm -ldl...
Test_OpenMP_Mex.f90...
-output Test_OpenMP_Mex
Reference:
MATLAB documentation
GCC environment variables

Answer 2

There is one note you shouldn't miss when lining against intel mkl ilp64 versions of libs:
you need to add -I4 compiler option, otherwise, you may see some kind of an unexpected segfault... Please refer to the mkl linker adviser to see more details: https://software.intel.com/content/www/us/en/develop/articles/intel-mkl-link-line-advisor.html