Performance decrease with OMP simd

I have some Fortran code out of a benchmark suite that uses OMP 4.0 features. Among them is the new "omp simd" to vectorize parallelized loop nests.

If I omit the "omp simd" the code actually runs faster (around 15% less runtime on a large dataset with ~25minutes runtime where the modified code causes approx. 25-40% of the total runtime) This was tested on an Intel MIC via omp target.

I checked with -vec-report1 comparing the outputs. I get "OpenMP SIMD LOOP WAS VECTORIZED" / "LOOP WAS VECTORIZED" on every one of the loops, so there should not be such a big difference in runtime.

I suppose this is most likely a bug in the compiler. Can you explain the behavior?

Typical usage is like following:

    !$omp do
    DO k=y_min,y_max+1
      !$omp simd
      DO j=x_min-1,x_max+2
        someArray(j,k)=someOtherArray(j,k)-foo(j-1,k)+bar(j,k)
      ENDDO
    ENDDO

    !$omp do
    DO k=y_min,y_max+1
      !$omp simd PRIVATE(xFoo) !!!! When removing the simd here, place the private clause in the "omp do"
      DO j=x_min-1,x_max+1
        IF(someCondition)THEN
          xFoo=1
        ELSE
          xFoo=j
        ENDIF
        ! Some more code
        someArray(j,k)=foo(xFoo,k)*bar(j,k)
      ENDDO
    ENDDO

Please note, that I cannot show the real code here in public, but be assured, the code is pretty much doing exactly that. I may send the actual code to Intel though for investigation purposes.