Why loops in inline function cannot be properly auto-vectorized?

Question

I am trying to vectorize some simple calculations for speed up from SIMD architecture. However, I also want to put them as inline function because function calls and non-vectorized codes also take computation time. However, I cannot always achieve them at the same time. In fact, most of my inline functions fail to get auto-vectorized. Here is a simple test code that works:

inline void add1(double *v, int Length) {
    for(int i=0; i < Length; i++) v[i] += 1;
}

void call_add1(double v[], int L) {
    add1(v, L);
}

int main(){return 0;}

On Mac OS X 10.12.3, compile it:

clang++ -O3 -Rpass=loop-vectorize -Rpass-analysis=loop-vectorize -std=c++11 -ffast-math test.cpp

test.cpp:2:5: remark: vectorized loop (vectorization width: 2, interleaved count: 2) [-Rpass=loop-vectorize]
    for(int i=0; i < Length; i++) v[i] += 1;
    ^

However, Something very similar (only moving arguments in call_add1) does not work:

inline void add1(double *v, int Length) {
    for(int i=0; i < Length; i++) v[i] += 1;
}

void call_add1() {
    double v[20]={0,1,3,4,5,6,7,8,9,10,1,2,3,4,5,6,7,8,9}; 
    int L=20;
    add1(v, L);
}

int main(){ return 0;}

Compiling with the same command produces no output. Why does this happen? How can I make sure that loops in inline functions always get auto-vectorized? I want to vectorize many function loops, so I hope the fix would not be to complex.

Answer 1

Compiling your code with -fsave-optimization-record shows that the loop was unrolled and then eliminated.

--- !Passed
Pass:            loop-unroll
Name:            FullyUnrolled
DebugLoc:        { File: main.cpp, Line: 2, Column: 5 }
Function:        _Z9call_add1v
Args:            
  - String:          'completely unrolled loop with '
  - UnrollCount:     '20'
  - String:          ' iterations'
...
--- !Passed
Pass:            gvn
Name:            LoadElim
DebugLoc:        { File: main.cpp, Line: 2, Column: 40 }
Function:        _Z9call_add1v
Args:            
  - String:          'load of type '
  - Type:            double
  - String:          ' eliminated'
  - String:          ' in favor of '
  - InfavorOfValue:  '0.000000e+00'

If you put 4000 elements to the array, it will exceed optimizer threshold and clang will enable vectorization.