llvm dev - Apr 2013 - [LLVMdev] Packed instructions generaetd by LoopVectorize?

Hi,

I have a question about LoopVectorize. I wrote a simple test case, a dot product
loop and found that packed instructions are generated when input arrays are
integer, but not when they are float or double.

If I modify the float example in http://llvm.org/docs/Vectorizers.html by adding
restrict to the input arrays packed instructions are generated. Although it
should not be required I tried doing the same to the input arrays of my dot
product example but it still doesn't generate packed float or double
instructions.

Is the loop vectorizer supposed to generate packed float and double
instructions? Is this a bug, or am I doing something wrong?

Tyler

float dotproduct(float *A, float *B, int n) {
  float sum = 0;
  for(int i = 0; i < n; ++i) {
    sum += A[i] * B[i];
  }
  return sum;
}

clang dotproduct.cpp -O3 -fvectorize -march=atom -S -o -

<loop body>
.LBB1_1:
        movss   (%rdi), %xmm1
        addq    $4, %rdi
        mulss   (%rsi), %xmm1
        addq    $4, %rsi
        decl    %edx
        addss   %xmm1, %xmm0
        jne     .LBB1_1
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Hi Tyler, 

Try adding -ffast-math.  We can only vectorize reduction variables if it is safe
to reorder floating point operations.

Thanks,
Nadav

On Apr 3, 2013, at 10:29 AM, "Nowicki, Tyler" <tyler.nowicki at
intel.com> wrote:
> Hi,
>  
> I have a question about LoopVectorize. I wrote a simple test case, a dot
product loop and found that packed instructions are generated when input arrays
are integer, but not when they are float or double.
>  
> If I modify the float example in http://llvm.org/docs/Vectorizers.html by
adding restrict to the input arrays packed instructions are generated. Although
it should not be required I tried doing the same to the input arrays of my dot
product example but it still doesn’t generate packed float or double
instructions.
>  
> Is the loop vectorizer supposed to generate packed float and double
instructions? Is this a bug, or am I doing something wrong?
>  
> Tyler
>  
> float dotproduct(float *A, float *B, int n) {
>   float sum = 0;
>   for(int i = 0; i < n; ++i) {
>     sum += A[i] * B[i];
>   }
>   return sum;
> }
>  
> clang dotproduct.cpp -O3 -fvectorize -march=atom -S -o -
>  
> <loop body>
> .LBB1_1:
>         movss   (%rdi), %xmm1
>         addq    $4, %rdi
>         mulss   (%rsi), %xmm1
>         addq    $4, %rsi
>         decl    %edx
>         addss   %xmm1, %xmm0
>         jne     .LBB1_1
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Thanks, that did it!

Are there any plans to enable the loop vectorizer by default?

From: Nadav Rotem [mailto:nrotem at apple.com]
Sent: Wednesday, April 03, 2013 13:33 PM
To: Nowicki, Tyler
Cc: LLVM Developers Mailing List
Subject: Re: Packed instructions generaetd by LoopVectorize?

Hi Tyler,

Try adding -ffast-math.  We can only vectorize reduction variables if it is safe
to reorder floating point operations.

Thanks,
Nadav

On Apr 3, 2013, at 10:29 AM, "Nowicki, Tyler" <tyler.nowicki at
intel.com<mailto:tyler.nowicki at intel.com>> wrote:


Hi,

I have a question about LoopVectorize. I wrote a simple test case, a dot product
loop and found that packed instructions are generated when input arrays are
integer, but not when they are float or double.

If I modify the float example in http://llvm.org/docs/Vectorizers.html by adding
restrict to the input arrays packed instructions are generated. Although it
should not be required I tried doing the same to the input arrays of my dot
product example but it still doesn't generate packed float or double
instructions.

Is the loop vectorizer supposed to generate packed float and double
instructions? Is this a bug, or am I doing something wrong?

Tyler

float dotproduct(float *A, float *B, int n) {
  float sum = 0;
  for(int i = 0; i < n; ++i) {
    sum += A[i] * B[i];
  }
  return sum;
}

clang dotproduct.cpp -O3 -fvectorize -march=atom -S -o -

<loop body>
.LBB1_1:
        movss   (%rdi), %xmm1
        addq    $4, %rdi
        mulss   (%rsi), %xmm1
        addq    $4, %rsi
        decl    %edx
        addss   %xmm1, %xmm0
        jne     .LBB1_1

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