[LLVMdev] Modifications to SLP

Tue Jul 7 14:40:42 PDT 2015

> On Jul 7, 2015, at 1:30 PM, Sanjay Patel <spatel at rotateright.com> wrote:
> 
> I forgot to update the SLP thread from last week. I have a patch up for review that would allow creating wider vectors as requested, but may increase SLP compile time:
> http://reviews.llvm.org/D10950 <http://reviews.llvm.org/D10950>
> 
> An audit of the trunk backends shows that only PowerPC + QPX and x86 + AVX / AVX512 would potentially get an extra round of store merging from the use of 'getRegisterBitWidth()'. 
> 
> As reported in the phab comments, I didn't see any compile time hit on test-suite for an AVX machine. I'm very curious to know if that patch causes further blowup in this example.
Thanks for the heads up, Sanjay! I think that effect from your patch wouldn’t be that big even in this case, because I don’t think that vectorizeStoreChain is a bottleneck here (disclaimer: that’s just my plain speculations). But it’s always good to check:)

Michael
> 
> Frank, what causes a 10^6 instruction function to be generated? Can this be rolled into a loop?
> 
> 
> On Tue, Jul 7, 2015 at 12:55 PM, Michael Zolotukhin <mzolotukhin at apple.com <mailto:mzolotukhin at apple.com>> wrote:
> Hi Frank,
> 
> The most time consuming part of SLP vectorizer (especially in cases like yours) is finding sets of consecutive stores. It's currently performed by a quadratic search (see routine SLPVectorizer::vectorizeStores) - we do pairwise comparisons between all pointers (but we do limit ourselves to look at at most 16 stores). I think it should be possible to group pointers with a common base, compute constant relative offset and just sort all of them - this way we’ll save a lot of expensive computations. However, I haven’t tried implementing this, and I guess there might be some hard corner cases too. Patches would be welcome here:)
> 
> Thanks,
> Michael
> 
> > On Jul 7, 2015, at 11:31 AM, Frank Winter <fwinter at jlab.org <mailto:fwinter at jlab.org>> wrote:
> >
> > Hi all!
> >
> > It takes the current SLP vectorizer too long to vectorize my scalar code. I am talking here about functions that have a single, huge basic block with O(10^6) instructions. Here's an example:
> >
> >  %0 = getelementptr float* %arg1, i32 49
> >  %1 = load float* %0
> >  %2 = getelementptr float* %arg1, i32 4145
> >  %3 = load float* %2
> >  %4 = getelementptr float* %arg2, i32 49
> >  %5 = load float* %4
> >  %6 = getelementptr float* %arg2, i32 4145
> >  %7 = load float* %6
> >  %8 = fmul float %7, %1
> >  %9 = fmul float %5, %3
> >  %10 = fadd float %9, %8
> >  %11 = fmul float %7, %3
> >  %12 = fmul float %5, %1
> >  %13 = fsub float %12, %11
> >  %14 = getelementptr float* %arg3, i32 16
> >  %15 = load float* %14
> >  %16 = getelementptr float* %arg3, i32 4112
> >  %17 = load float* %16
> >  %18 = getelementptr float* %arg4, i32 0
> >  %19 = load float* %18
> >  %20 = getelementptr float* %arg4, i32 4096
> >  %21 = load float* %20
> >  %22 = fmul float %21, %15
> >  %23 = fmul float %19, %17
> >  %24 = fadd float %23, %22
> >  %25 = fmul float %21, %17
> >  %26 = fmul float %19, %15
> >  %27 = fsub float %26, %25
> >  %28 = fadd float %24, %10
> >  %29 = fadd float %27, %13
> >  %30 = getelementptr float* %arg0, i32 0
> >  store float %29, float* %30
> >  %31 = getelementptr float* %arg0, i32 4096
> >  store float %28, float* %31
> > ... and so on ...
> >
> > The SLP vectorizer would create some code like this:
> >
> >  %219 = insertelement <4 x float> %218, float %185, i32 2
> >  %220 = insertelement <4 x float> %219, float %197, i32 3
> >  %221 = fmul <4 x float> %216, %220
> >  %222 = fadd <4 x float> %221, %212
> >  %223 = fmul <4 x float> %207, %220
> > ..
> >  %234 = bitcast float* %165 to <4 x float>*
> >  store <4 x float> %233, <4 x float>* %234, align 4
> >
> >
> > With the current SLP implementation 99.5% of the time is spent in the SLP vectorizer and I have the impression that this can be improved for my case. I believe that the SLP vectorizer has far more capabilities than I would need for these simple (but huge) functions. And I was hoping that any of you have an idea how to remove functionality of the SLP vectorizer such that it still can vectorize those simple functions...?
> >
> > Thanks,
> > Frank
> >
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