Fortran 在 for 循环内矢量化日志

Question

Here is the minimum working code.

program test
    implicit none

    double precision:: c1,c2,rate
    integer::ci,cj,cr,cm,i
    integer,parameter::max_iter=10000000 !10^7

    c1=0.0d+0

    CALL system_clock(count_rate=cr)
    CALL system_clock(count_max=cm)
    rate = REAL(cr)

    CALL SYSTEM_CLOCK(ci)
    do i=1,max_iter
        c1=c1+log(DBLE(i))
    end do
    CALL SYSTEM_CLOCK(cj)
    WRITE(*,*) "system_clock : ",(cj - ci)/rate

    print*, c1
end program test

When I compile with gfortran -Ofast -march=core-avx2 -fopt-info-vec-optimized the for loop with the log function does not get vectorized. I have also tried with -O3 but the result does not change.

But if I write the equivalent C++ code,

#include <iostream>
#include <chrono>
#include <cmath>
using namespace std;
using namespace std::chrono;

int main()
{
    double c1=0;
    const int max_iter=10000000; // 10^7

    auto start = high_resolution_clock::now();
    for(int i=1;i<=max_iter;i++)
    {
        c1 += log(i);
    }
    auto stop = high_resolution_clock::now();

    auto duration = duration_cast<milliseconds>(stop - start); 
    cout << duration.count() << " ms"<<'\n'; 

    printf("%0.15f\n",c1);

    return 0;
}

and compile it with g++ -Ofast -march=core-avx2 -fopt-info-vec-optimized , the for loop gets vectorized and runs almost 10 times faster.

What should I do to make the fortran loop vectorized?

Answer 1

The problem with vectorizing loops that include the math functions (like log ) is that the compiler has to be taught the semantics of the vectorized math functions (and you see if you look at the assembler output that the Fortran version calls the "normal" scalar function (a line like call log ) whereas your C++ version calls the vectorized version ( call _ZGVdN4v___log_finite )). There has been some work wrt making GFortran understand the glibc vector math library ( libmvec ), but I'm not sure what the current status is. See the thread starting at https://gcc.gnu.org/legacy-ml/gcc/2018-04/msg00062.html and continuing in June 2018 starting at https://gcc.gnu.org/legacy-ml/gcc/2018-06/msg00167.html for more details.