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James Molloy

2014-Nov-10 15:43 UTC

[LLVMdev] [Vectorization] Mis match in code generated

Hi Suyog,

Thanks for looking at this. This has recently got itself onto my TODO list
too.
> I am not sure how much all this will improve the code quality for
horizontal reduction> (donno how frequently such pattern of horizontal reduction from samearray occurs in real world/SPECS).

Actually the main loop of 470.lbm can be SLP vectorized like this. We have
three parts to it: A fully unrolled reduction, a scatter/gather part (not
really vectorizable) and a contiguous-load-scatter-store part which should
be vectorized even when scatter stores are not available in HW.


Cheers,

James

On 10 November 2014 14:30, Arnold Schwaighofer <aschwaighofer at
apple.com>
wrote:
> Hi Suyog,
>
> the horizontal reduction code needs work. It was written long ago and was
> never enabled so it has bit rotted somewhat and has lurking bugs.
> For example, it could not handle reduction value nodes that were not
> binary operations.
>
> It could vectorize
>
> (+ (* x y) (*z a) (*b c) (*d e))
>
> but not
>
>
> (+ (load a) (load b) (load c) (load d))
>
>
> With the attached patches:
> 0001-Test-hor-redux.patch
> 0002-Print-out-tree.patch
>
> We would attempt to vectorize the tree stemming from your example:
>
>
> > float a[4], sum;
> > void foo() {
> >   sum = a[0]+a[1]+a[2]+a[3];
> > }
>
> but because we happen to end up with the vector tuple (a[1],
> a[0],a[2],a[3)) in need of gathering the existing code fails. Note, that I
> used fast-math because the horizontal reduction code assumes it can
> reassociate freely.
>
> > clang -O3 test_hor_redux.c -emit-llvm -S -o - -mllvm
> -slp-vectorize-hor-store  -debug-only=SLP -ffast-math -mllvm
-debug-only=SLP
>
> ...
>
>   Reduced val:   %1 = load float* getelementptr inbounds ([4 x float]* @a,
> i64 0, i64 1), align 4, !tbaa !1
>   Reduced val:   %0 = load float* getelementptr inbounds ([4 x float]* @a,
> i64 0, i64 0), align 16, !tbaa !1
>   Reduced val:   %2 = load float* getelementptr inbounds ([4 x float]* @a,
> i64 0, i64 2), align 8, !tbaa !1
>   Reduced val:   %3 = load float* getelementptr inbounds ([4 x float]* @a,
> i64 0, i64 3), align 4, !tbaa !1
>   Reduction ops:   %add = fadd fast float %1, %0
>   Reduction ops:   %add1 = fadd fast float %add, %2
>   Reduction ops:   %add2 = fadd fast float %add1, %3
> Assertion failed: (VectorizedValue && "Need to have a
vectorized tree
> node"), function emitReduction, file
> ../lib/Transforms/Vectorize/SLPVectorizer.cpp, line 3518.
>
> The reduction looks like
>
> (((a[1] + a[0]) + a[2]) + a[3])
>
> So we build a tree entry  (load a[1], load a[0], load a[2], load a[3]) and
> end up with a vectorized tree entry of one who needs gathering.
>
> The code does not handle this case correctly (in normal slp mode there is
> no point in "vectorizing" a single entry tree that needs
gathering).
> The patch
> 0003-We-don-t-correctly-vectorize-single-entry-gather-nod.patch fixes this
> by disabling vectorization in such a case but then we don't vectorize.
> As you can see this needs more work.
>
> * We could reassociate reductions like the one above.
>
> (((a[1] + a[0]) + a[2]) + a[3])
>
> =>
>
> (((a[0] + a[1]) + a[2]) + a[3])
>
> Then the reduction tree builder code would not have to be clever. That
> will only work if your initial reduction values are loads. If the loads are
> hidden behind a deeper tree that won't help. In such a case the next
> solution would not be so bad though.
>
> * We could teach the tree code to do a vector load + permute operation if
> applicable. This will no generate the best code though. But for deeper
> trees the overhead of the permute probably does not matter much.
>
>
> Best,
> Arnold
>
> On 11/09/14, suyog sarda   wrote:
> > Hi Arnold, Nadav, Hal,
> > all,
> >
> >
> > Restarting this thread with few more observations on horizontal
> reduction store
> > (after using flags - slp-vectorize-hor-store and -slp-vectorize-hor,
> thanks Arnold for pointing out earlier).
> >
> >
> > The SLP vectorizer does vectorize straight line code :
> >
> >
> > (this code may result as part of loop unrolling as stated earlier in
the
> thread.
> > Though for loop vectorization , trip count should be atleast 16,
taking
> smaller
> > code here to put some findings.)
> >
> >
> > float a[4], sum;
> >
> > void foo() {
> >
> >  int i;
> >
> >  for(i=0;i<4;i++);
> >
> >    sum += a[i];
> > }
> >
> > after loop unrolling -
> >
> > float a[4], sum;
> > void foo() {
> >   sum = a[0]+a[1]+a[2]+a[3];
> > }
> >
> >
> > This code gets vectorized depending on how we organize the code, and
> subsequently
> >
> > how the expression tree is formed.
> >
> >
> > case 1:
> >
> > float a[4], sum;
> > void foo() {
> >   sum = a[0]+a[1]+a[2]+a[3];
> > }
> >
> >
> > The expression tree for this will be
> >
> >
> >     a[0]    a[1]
> >
> >        \       /
> >         \     /
> >
> >            +      a[2]
> >
> >             \     /
> >              \   /
> >
> >                +       a[3]
> >
> >                  \      /
> >                   \    /
> >                     +
> >                      |
> >                      |
> >                      ↓
> >
> >                      sum
> >
> >
> > This doesn't vectorize, because in function tryToVectorizeList(),
we
> check if the
> >
> > scalar instruction are of the same type. In above case, it will be
fadd
> and load,
> >
> > and hence no vectorization takes place.
> >
> >
> >
> > case 2:
> >
> > float a[4], sum;
> > void foo() {
> >   sum = (a[0]+a[1])+(a[2]+a[3]);
> > }
> >
> >
> > The expression tree for this will be (notice brackets above):
> >
> >
> > a[0]    a[1]      a[2]    a[3]
> >
> >    \       /            \        /
> >     \     /              \      /
> >        +                   +
> >          \                /
> >           \              /
> >            \            /
> >                  +
> >                    |
> >                   |
> >                   ↓
> >                  sum
> >
> >
> > In this case, in function tryToVectorizeList(), both the scalar
> instructions are
> >
> > same i.e. fadd. Hence we proceed for vectorization ahead.
> >
> > But this still doesn't vectorizes the code. Ahead, while trying to
> schedule bundle of code,
> >
> > it checks whether the loads are for consecutive memory access across
two
> subtrees from
> > same base pointer.
> >
> >
> > For above code, it checks if (a[0],a[2]) and (a[1],a[3]) are
consecutive
> memory
> > access (which, obviously, they are not). This cancels scheduling of
> bundle of loads,
> > and hence calculated cost for non-consecutive loads comes greater
> increasing overall
> >
> > cost of vectorization (and hence no vectorization).
> >
> >
> > Seems this check for consecutive memory access was written keeping in
> mind following sort of code :
> >
> > sum = (a[0] + b[0]) + (a[1] + b[1]);
> >
> >
> >
> > Finally,
> >
> > case 3:
> >
> > float a[4], sum;
> > void foo() {
> >   sum = (a[0]+a[2])+(a[1]+a[3]);
> > }
> >
> >
> > The expression tree for this will be (notice brackets above):
> >
> >
> > a[0]    a[2]      a[1]    a[3]
> >
> >    \       /            \        /
> >     \     /              \      /
> >        +                   +
> >          \                /
> >           \              /
> >            \            /
> >                  +
> >                    |
> >                   |
> >                   ↓
> >                  sum
> >
> >
> >
> > This code gets vectorized, as tryToVectorizeList() gets both scalar
> operation as fadd,
> >
> > as well as there is a consecutive memory access across subtress rooted
> at both fadd.
> >
> >
> > case 1 IR after SLP vectorization :
> >
> > define void @foo() #0 {
> > entry:
> >   %0 = load float* getelementptr inbounds ([8 x float]* @a, i64 0, i64
> 0), align 16, !tbaa !1
> >   %1 = load float* getelementptr inbounds ([8 x float]* @a, i64 0, i64
> 1), align 4, !tbaa !1
> >   %add = fadd float %0, %1
> >   %2 = load float* getelementptr inbounds ([8 x float]* @a, i64 0, i64
> 2), align 8, !tbaa !1
> >   %add1 = fadd float %add, %2
> >   %3 = load float* getelementptr inbounds ([8 x float]* @a, i64 0, i64
> 3), align 4, !tbaa !1
> >   %add2 = fadd float %add1, %3
> >   store float %add2, float* @sum, align 4, !tbaa !1
> >   ret void
> > }
> >
> >
> > case 2 IR after SLP vectorization :
> >
> > define void @foo() #0 {
> > entry:
> >   %0 = load float* getelementptr inbounds ([8 x float]* @a, i64 0, i64
> 0), align 16, !tbaa !1
> >   %1 = load float* getelementptr inbounds ([8 x float]* @a, i64 0, i64
> 1), align 4, !tbaa !1
> >   %add = fadd float %0, %1
> >   %2 = load float* getelementptr inbounds ([8 x float]* @a, i64 0, i64
> 2), align 8, !tbaa !1
> >   %3 = load float* getelementptr inbounds ([8 x float]* @a, i64 0, i64
> 3), align 4, !tbaa !1
> >   %add1 = fadd float %2, %3
> >   %add2 = fadd float %add, %add1
> >   store float %add2, float* @sum, align 4, !tbaa !1
> >   ret void
> > }
> >
> >
> > case 3 IR after SLP vectorization :
> >
> >
> > define void @foo() #0 {
> > entry:
> >   %0 = load <2 x float>* bitcast ([4 x float]* @a to <2 x
float>*),
> align 16, !tbaa !1
> >   %1 = load <2 x float>* bitcast (float* getelementptr inbounds
([4 x
> float]* @a, i64 0, i64 2) to <2 x float>*), align 8, !tbaa !1
> >   %2 = fadd <2 x float> %0, %1
> >   %3 = extractelement <2 x float> %2, i32 0
> >   %4 = extractelement <2 x float> %2, i32 1
> >   %add2 = fadd float %3, %4
> >   store float %add2, float* @sum, align 4, !tbaa !1
> >   ret void
> > }
> >
> >
> >
> > Few cases of improvements, as visible from above (noting down roughly,
> didn't give detail thought on it yet):
> >
> > 1. The IR expression tree can be re-organized to cater above need
(some
> kind of balancing like AVL tree).
> >
> >     Alternatively, parse the expression tree without changing it and
> look upward tree if we encounter a
> >
> >     load instruction.
> >
> > 2. Seems, there is a case for improvement in checking if memory access
> are consecutive.
> >     This needs to take into consideration all the loads of all the
> subtree .
> >      If all the loads are from same base pointer, then are the memory
> access in same subtree as
> >      well as across the subtree consecutive. (i will try to write some
> code on this, any suggestions are welcomed)
> >
> >
> >
> > I am not sure how much all this will improve the code quality for
> horizontal reduction
> > (donno how frequently such pattern of horizontal reduction from same
> array occurs in real world/SPECS).
> >
> > Perhaps the best case i can think of is when loops are unrolled as
noted
> earlier in the thread.
> >
> >
> > Adding few more people to pitch in !!
> >
> >
> > Comments/Suggestions are most welcomed.
> >
> >
> > Regards,
> >
> > Suyog
> >
> >
> >
> >
> >
> >
> >
> >
> >
> >
> >
> >
> > On Sat, Sep 20, 2014 at 12:05 AM, suyog sarda <sardask01 at
gmail.com <
> sardask01 at gmail.com>> wrote:
> >
> > > Hi Arnold,
> > >
> > >
> > > Thanks for your reply.
> > >
> > >
> > > I tried test case as suggested by you.
> > >
> > > void foo(int *a, int *sum) {
> > > *sum >
a[0]+a[1]+a[2]+a[3]+a[4]+a[5]+a[6]+a[7]+a[8]+a[9]+a[10]+a[11]+a[12]+a[13]+a[14]+a[15];
> > > }
> > >
> > >
> > > so that it has a 'store' in its IR.
> > >
> > >
> > > IR before vectorization :
> > >
> > > target datalayout =
"e-m:e-p:32:32-f64:32:64-f80:32-n8:16:32-S128"
> > > target triple = "x86_64-pc-linux-gnu"
> > >
> > > ; Function Attrs: nounwind
> > > define void @foo(i32* nocapture readonly %a, i32* nocapture %sum)
#0 {
> > > entry:
> > >   %0 = load i32* %a, align 4, !tbaa !1
> > >   %arrayidx1 = getelementptr inbounds i32* %a, i32 1
> > >   %1 = load i32* %arrayidx1, align 4, !tbaa !1
> > >   %add = add nsw i32 %1, %0
> > >   %arrayidx2 = getelementptr inbounds i32* %a, i32 2
> > >   %2 = load i32* %arrayidx2, align 4, !tbaa !1
> > >   %add3 = add nsw i32 %add, %2
> > >   %arrayidx4 = getelementptr inbounds i32* %a, i32 3
> > >   %3 = load i32* %arrayidx4, align 4, !tbaa !1
> > >   %add5 = add nsw i32 %add3, %3
> > >   %arrayidx6 = getelementptr inbounds i32* %a, i32 4
> > >   %4 = load i32* %arrayidx6, align 4, !tbaa !1
> > >   %add7 = add nsw i32 %add5, %4
> > >   %arrayidx8 = getelementptr inbounds i32* %a, i32 5
> > >   %5 = load i32* %arrayidx8, align 4, !tbaa !1
> > >   %add9 = add nsw i32 %add7, %5
> > >   %arrayidx10 = getelementptr inbounds i32* %a, i32 6
> > >   %6 = load i32* %arrayidx10, align 4, !tbaa !1
> > >   %add11 = add nsw i32 %add9, %6
> > >   %arrayidx12 = getelementptr inbounds i32* %a, i32 7
> > >   %7 = load i32* %arrayidx12, align 4, !tbaa !1
> > >   %add13 = add nsw i32 %add11, %7
> > >   %arrayidx14 = getelementptr inbounds i32* %a, i32 8
> > >   %8 = load i32* %arrayidx14, align 4, !tbaa !1
> > >   %add15 = add nsw i32 %add13, %8
> > >   %arrayidx16 = getelementptr inbounds i32* %a, i32 9
> > >   %9 = load i32* %arrayidx16, align 4, !tbaa !1
> > >   %add17 = add nsw i32 %add15, %9
> > >   %arrayidx18 = getelementptr inbounds i32* %a, i32 10
> > >   %10 = load i32* %arrayidx18, align 4, !tbaa !1
> > >   %add19 = add nsw i32 %add17, %10
> > >   %arrayidx20 = getelementptr inbounds i32* %a, i32 11
> > >   %11 = load i32* %arrayidx20, align 4, !tbaa !1
> > >   %add21 = add nsw i32 %add19, %11
> > >   %arrayidx22 = getelementptr inbounds i32* %a, i32 12
> > >   %12 = load i32* %arrayidx22, align 4, !tbaa !1
> > >   %add23 = add nsw i32 %add21, %12
> > >   %arrayidx24 = getelementptr inbounds i32* %a, i32 13
> > >   %13 = load i32* %arrayidx24, align 4, !tbaa !1
> > >   %add25 = add nsw i32 %add23, %13
> > >   %arrayidx26 = getelementptr inbounds i32* %a, i32 14
> > >   %14 = load i32* %arrayidx26, align 4, !tbaa !1
> > >   %add27 = add nsw i32 %add25, %14
> > >   %arrayidx28 = getelementptr inbounds i32* %a, i32 15
> > >   %15 = load i32* %arrayidx28, align 4, !tbaa !1
> > >   %add29 = add nsw i32 %add27, %15
> > >
> > >
> > >   store i32 %add29, i32* %sum, align 4, !tbaa !1
> > >   ret void
> > > }
> > >
> > >
> > >
> > > IR after SLP vectorization with appropriate flags :
> > >
> > > $ opt -S -slp-vectorizer -slp-vectorize-hor=1
> -slp-vectorize-hor-store=1 test.ll -debug
> > >
> > >
> > > (I hope i am passing the args correctly to opt)
> > >
> > > Subtarget features: SSELevel 3, 3DNowLevel 0, 64bit 1
> > > SLP: Analyzing blocks in foo.
> > > SLP: Found 1 stores to vectorize.
> > > SLP: Vectorizing a list of length = 2.
> > > ; ModuleID = 'test.ll'
> > > target datalayout =
"e-m:e-p:32:32-f64:32:64-f80:32-n8:16:32-S128"
> > > target triple = "x86_64-pc-linux-gnu"
> > >
> > > ; Function Attrs: nounwind
> > > define void @foo(i32* nocapture readonly %a, i32* nocapture %sum)
#0 {
> > > entry:
> > >   %0 = load i32* %a, align 4, !tbaa !1
> > >   %arrayidx1 = getelementptr inbounds i32* %a, i32 1
> > >   %1 = load i32* %arrayidx1, align 4, !tbaa !1
> > >   %add = add nsw i32 %1, %0
> > >   %arrayidx2 = getelementptr inbounds i32* %a, i32 2
> > >   %2 = load i32* %arrayidx2, align 4, !tbaa !1
> > >   %add3 = add nsw i32 %add, %2
> > >   %arrayidx4 = getelementptr inbounds i32* %a, i32 3
> > >   %3 = load i32* %arrayidx4, align 4, !tbaa !1
> > >   %add5 = add nsw i32 %add3, %3
> > >   %arrayidx6 = getelementptr inbounds i32* %a, i32 4
> > >   %4 = load i32* %arrayidx6, align 4, !tbaa !1
> > >   %add7 = add nsw i32 %add5, %4
> > >   %arrayidx8 = getelementptr inbounds i32* %a, i32 5
> > >   %5 = load i32* %arrayidx8, align 4, !tbaa !1
> > >   %add9 = add nsw i32 %add7, %5
> > >   %arrayidx10 = getelementptr inbounds i32* %a, i32 6
> > >   %6 = load i32* %arrayidx10, align 4, !tbaa !1
> > >   %add11 = add nsw i32 %add9, %6
> > >   %arrayidx12 = getelementptr inbounds i32* %a, i32 7
> > >   %7 = load i32* %arrayidx12, align 4, !tbaa !1
> > >   %add13 = add nsw i32 %add11, %7
> > >   %arrayidx14 = getelementptr inbounds i32* %a, i32 8
> > >   %8 = load i32* %arrayidx14, align 4, !tbaa !1
> > >   %add15 = add nsw i32 %add13, %8
> > >   %arrayidx16 = getelementptr inbounds i32* %a, i32 9
> > >   %9 = load i32* %arrayidx16, align 4, !tbaa !1
> > >   %add17 = add nsw i32 %add15, %9
> > >   %arrayidx18 = getelementptr inbounds i32* %a, i32 10
> > >   %10 = load i32* %arrayidx18, align 4, !tbaa !1
> > >   %add19 = add nsw i32 %add17, %10
> > >   %arrayidx20 = getelementptr inbounds i32* %a, i32 11
> > >   %11 = load i32* %arrayidx20, align 4, !tbaa !1
> > >   %add21 = add nsw i32 %add19, %11
> > >   %arrayidx22 = getelementptr inbounds i32* %a, i32 12
> > >   %12 = load i32* %arrayidx22, align 4, !tbaa !1
> > >   %add23 = add nsw i32 %add21, %12
> > >   %arrayidx24 = getelementptr inbounds i32* %a, i32 13
> > >   %13 = load i32* %arrayidx24, align 4, !tbaa !1
> > >   %add25 = add nsw i32 %add23, %13
> > >   %arrayidx26 = getelementptr inbounds i32* %a, i32 14
> > >   %14 = load i32* %arrayidx26, align 4, !tbaa !1
> > >   %add27 = add nsw i32 %add25, %14
> > >   %arrayidx28 = getelementptr inbounds i32* %a, i32 15
> > >   %15 = load i32* %arrayidx28, align 4, !tbaa !1
> > >   %add29 = add nsw i32 %add27, %15
> > >
> > >
> > >   store i32 %add29, i32* %sum, align 4, !tbaa !1
> > >   ret void
> > > }
> > >
> > >
> > > As observed above, SLP vectorization doesn't vectorize this
code.
> > >
> > >
> > > I tried debugging, just mentioning what i found -
> > > the code hits vectorizeChainsInBlock() ->
> if(ShouldStartVectorizeHorAtStore) ->
> > > tryToVectorize() -> tryToVectorizePair() ->
tryToVectorizeList() -
> inside this function, it iterates in the
> > >
> > > for loop for checking if scalar instructions are of same type. It
> exits for 2nd iteration in the loop as
> > >
> > > OpCode does not match , one opcode is 'add' and second is
'load'. So
> it exits from function
> > > 'tryToVectorizeList()', and comes back to function
'tryToVectorize()',
> but fails to satisfy any of the
> > >
> > > further 'if' in that function and returns back without
vectorizing any
> of the code.
> > >
> > >
> > > I will try to dig more into it and try to understand where the
code
> can be implemented.
> > >
> > >
> > > Comments/suggestions/explanations are always welcomed !!
> > >
> > >
> > >
> > >
> > >
> > >
> > > On Fri, Sep 19, 2014 at 1:49 AM, Arnold <aschwaighofer at
apple.com <
> aschwaighofer at apple.com>> wrote:
> > >
> > > > There is experimental code to handle horizontal reductions
hidden
> behind a flag "slp-vectorize-hor" you could try to enable that.
It won't
> currently work for your example though because we only start to look for
> reductions at phis and stores "slp-vectorize-hor-stores".
> > > >
> > > >
> > > > You could start off by rewriting your example with a store
and see
> whether the tree match works after using both flags.
> > > >
> > > > F(int *sum ...){
> > > > *sum >
a[0]+a[1]+a[2]+a[3]+a[4]+a[5]+a[6]+a[7]+a[8]+a[9]+a[10]+a[11]+a[12]+a[13]+a[14]+a[15];
> > > > }
> > > >
> > > >
> > > > If it works we would only need to look for horizontal
reductions at
> returns.
> > > >
> > > >
> > > >
> > > >
> > > >
> > > >
> > > > Sent from my iPhone
> > > >
> > > > On Sep 18, 2014, at 12:24 PM, suyog sarda <sardask01 at
gmail.com <
> sardask01 at gmail.com>> wrote:
> > > >
> > > >
> > > >
> > > > > Hi Nadav,
> > > > >
> > > > >
> > > > > Thanks for the quick reply !!
> > > > >
> > > > >
> > > > > Ok, so as of now we are lacking capability to handle
flat large
> reductions.
> > > > >
> > > > >
> > > > > I did go through function vectorizeChainsInBlock()
(line number
> 2862). In this function,
> > > > >
> > > > > we try to vectorize if we have phi nodes in the IR
(several if's
> check for phi nodes) i.e we try to
> > > > >
> > > > > construct tree that starts at chains.
> > > > >
> > > > >
> > > > > Any pointers on how to join multiple trees? I will also
try to dig
> more into it.
> > > > >
> > > > >
> > > > > Comments/Suggestions are most welcomed !!
> > > > >
> > > > >
> > > > > On Fri, Sep 19, 2014 at 12:23 AM, Nadav Rotem
<nrotem at apple.com <
> nrotem at apple.com>> wrote:
> > > > >
> > > > > >
> > > > > >
> > > > > > > On Sep 18, 2014, at 11:48 AM, suyog sarda
<sardask01 at gmail.com
> <sardask01 at gmail.com>> wrote:
> > > > > > >
> > > > > > > Hi,
> > > > > > >
> > > > > > >
> > > > > > > I am trying to understand LLVM vectorization
implementation
> and was looking into both loop and SLP vectorization.
> > > > > > >
> > > > > > >
> > > > > > > test case 1:
> > > > > > >
> > > > > > >
> > > > > > > int foo(int *a) {
> > > > > > > int sum = 0,i;
> > > > > > > for(i=0; i<16; i++)
> > > > > > >   sum += a[i];
> > > > > > > return sum;
> > > > > > > }
> > > > > > >
> > > > > > >
> > > > > > > This code is vectorized by loop vectorizer
where we calculate
> scalar loop cost as 4 and vector loop cost as 2.
> > > > > > >
> > > > > > > Since vector loop cost is less and above
reduction is legal to
> vectorize, loop vectorizer produces vectorized code :
> > > > > > >
> > > > > > >
> > > > > > > IR without vectorization:
> > > > > > >
> > > > > > > target datalayout >
"e-m:e-p:32:32-f64:32:64-f80:32-n8:16:32-S128"
> > > > > > > target triple =
"x86_64-pc-linux-gnu"
> > > > > > >
> > > > > > > ; Function Attrs: nounwind readonly
> > > > > > > define i32 @foo(i32* nocapture readonly %a,
i32 %n) #0 {
> > > > > > > entry:
> > > > > > >   br label %for.body
> > > > > > >
> > > > > > > for.body:                                    
; preds > %for.body, %entry
> > > > > > >   %i.05 = phi i32 [ 0, %entry ], [ %inc,
%for.body ]
> > > > > > >   %sum.04 = phi i32 [ 0, %entry ], [ %add,
%for.body ]
> > > > > > >   %arrayidx = getelementptr inbounds i32* %a,
i32 %i.05
> > > > > > >   %0 = load i32* %arrayidx, align 4, !tbaa !1
> > > > > > >   %add = add nsw i32 %0, %sum.04
> > > > > > >   %inc = add nsw i32 %i.05, 1
> > > > > > >   %exitcond = icmp eq i32 %i.05, 15
> > > > > > >   br i1 %exitcond, label %for.end, label
%for.body
> > > > > > >
> > > > > > > for.end:                                     
; preds > %for.body
> > > > > > >   ret i32 %add
> > > > > > > }
> > > > > > >
> > > > > > >
> > > > > > > IR after vectorization:
> > > > > > >
> > > > > > > target datalayout >
"e-m:e-p:32:32-f64:32:64-f80:32-n8:16:32-S128"
> > > > > > > target triple =
"x86_64-pc-linux-gnu"
> > > > > > >
> > > > > > > ; Function Attrs: nounwind readonly
> > > > > > > define i32 @foo(i32* nocapture readonly %a,
i32 %n) #0 {
> > > > > > > entry:
> > > > > > >   %backedge.overflow = icmp eq i32 15, -1
> > > > > > >   %overflow.check.anchor = add i32 0, 0
> > > > > > >   br i1 %backedge.overflow, label
%scalar.ph(http://scalar.ph/),
> label %overflow.checked
> > > > > > >
> > > > > > > overflow.checked:                            
; preds > %entry
> > > > > > >   br i1 false, label %middle.block, label
%vector.ph(
> http://vector.ph/)
> > > > > > >
> > > > > > > vector.ph(http://vector.ph/):
> ; preds = %overflow.checked
> > > > > > >   br label %vector.body
> > > > > > >
> > > > > > > vector.body:                                 
; preds > %vector.body, %vector.ph(http://vector.ph/)
> > > > > > >   %index = phi i32 [ 0,
%vector.ph(http://vector.ph/) ], [
> %index.next, %vector.body ]
> > > > > > >   %vec.phi = phi <4 x i32> [
zeroinitializer, %vector.ph(
> http://vector.ph/) ], [ %14, %vector.body ]
> > > > > > >   %broadcast.splatinsert = insertelement
<4 x i32> undef, i32
> %index, i32 0
> > > > > > >   %broadcast.splat = shufflevector <4 x
i32>
> %broadcast.splatinsert, <4 x i32> undef, <4 x i32>
zeroinitializer
> > > > > > >   %induction = add <4 x i32>
%broadcast.splat, <i32 0, i32 1,
> i32 2, i32 3>
> > > > > > >   %0 = extractelement <4 x i32>
%induction, i32 0
> > > > > > >   %1 = getelementptr inbounds i32* %a, i32 %0
> > > > > > >   %2 = insertelement <4 x i32*> undef,
i32* %1, i32 0
> > > > > > >   %3 = extractelement <4 x i32>
%induction, i32 1
> > > > > > >   %4 = getelementptr inbounds i32* %a, i32 %3
> > > > > > >   %5 = insertelement <4 x i32*> %2,
i32* %4, i32 1
> > > > > > >   %6 = extractelement <4 x i32>
%induction, i32 2
> > > > > > >   %7 = getelementptr inbounds i32* %a, i32 %6
> > > > > > >   %8 = insertelement <4 x i32*> %5,
i32* %7, i32 2
> > > > > > >   %9 = extractelement <4 x i32>
%induction, i32 3
> > > > > > >   %10 = getelementptr inbounds i32* %a, i32
%9
> > > > > > >   %11 = insertelement <4 x i32*> %8,
i32* %10, i32 3
> > > > > > >   %12 = getelementptr i32* %1, i32 0
> > > > > > >   %13 = bitcast i32* %12 to <4 x i32>*
> > > > > > >   %wide.load = load <4 x i32>* %13,
align 4, !tbaa !1
> > > > > > >   %14 = add nsw <4 x i32> %wide.load,
%vec.phi
> > > > > > >   %15 = add nsw <4 x i32> %induction,
<i32 1, i32 1, i32 1,
> i32 1>
> > > > > > >   %16 = icmp eq <4 x i32> %induction,
<i32 15, i32 15, i32 15,
> i32 15>
> > > > > > >   %index.next = add i32 %index, 4
> > > > > > >   %17 = icmp eq i32 %index.next, 16
> > > > > > >   br i1 %17, label %middle.block, label
%vector.body,
> !llvm.loop !5
> > > > > > >
> > > > > > > middle.block:                                
; preds > %vector.body, %overflow.checked
> > > > > > >   %resume.val = phi i32 [ 0,
%overflow.checked ], [ 16,
> %vector.body ]
> > > > > > >   %trunc.resume.val = phi i32 [ 0,
%overflow.checked ], [ 16,
> %vector.body ]
> > > > > > >   %rdx.vec.exit.phi = phi <4 x i32> [
zeroinitializer,
> %overflow.checked ], [ %14, %vector.body ]
> > > > > > >   %rdx.shuf = shufflevector <4 x i32>
%rdx.vec.exit.phi, <4 x
> i32> undef, <4 x i32> <i32 2, i32 3, i32 undef, i32 undef>
> > > > > > >   %bin.rdx = add <4 x i32>
%rdx.vec.exit.phi, %rdx.shuf
> > > > > > >   %rdx.shuf1 = shufflevector <4 x i32>
%bin.rdx, <4 x i32>
> undef, <4 x i32> <i32 1, i32 undef, i32 undef, i32 undef>
> > > > > > >   %bin.rdx2 = add <4 x i32> %bin.rdx,
%rdx.shuf1
> > > > > > >   %18 = extractelement <4 x i32>
%bin.rdx2, i32 0
> > > > > > >   %cmp.n = icmp eq i32 16, %resume.val
> > > > > > >   br i1 %cmp.n, label %for.end, label
%scalar.ph(
> http://scalar.ph/)
> > > > > > >
> > > > > > > scalar.ph(http://scalar.ph/):
> ; preds = %middle.block, %entry
> > > > > > >   %bc.resume.val = phi i32 [ %resume.val,
%middle.block ], [
> 0, %entry ]
> > > > > > >   %bc.trunc.resume.val = phi i32 [
%trunc.resume.val,
> %middle.block ], [ 0, %entry ]
> > > > > > >   %bc.merge.rdx = phi i32 [ 0, %entry ], [
%18, %middle.block ]
> > > > > > >   br label %for.body
> > > > > > >
> > > > > > > for.body:                                    
; preds > %for.body, %scalar.ph(http://scalar.ph/)
> > > > > > >   %i.05 = phi i32 [ %bc.trunc.resume.val,
%scalar.ph(
> http://scalar.ph/) ], [ %inc, %for.body ]
> > > > > > >   %sum.04 = phi i32 [ %bc.merge.rdx,
%scalar.ph(
> http://scalar.ph/) ], [ %add, %for.body ]
> > > > > > >   %arrayidx = getelementptr inbounds i32* %a,
i32 %i.05
> > > > > > >   %19 = load i32* %arrayidx, align 4, !tbaa
!1
> > > > > > >   %add = add nsw i32 %19, %sum.04
> > > > > > >   %inc = add nsw i32 %i.05, 1
> > > > > > >   %exitcond = icmp eq i32 %i.05, 15
> > > > > > >   br i1 %exitcond, label %for.end, label
%for.body, !llvm.loop
> !8
> > > > > > >
> > > > > > > for.end:                                     
; preds > %middle.block, %for.body
> > > > > > >   %add.lcssa = phi i32 [ %add, %for.body ], [
%18,
> %middle.block ]
> > > > > > >   ret i32 %add.lcssa
> > > > > > > }
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > > Now for test case 2, where we unroll the loop
totally :
> > > > > > >
> > > > > > > int foo(int *a) {
> > > > > > > int sum = 0;
> > > > > > > sum >
a[0]+a[1]+a[2]+a[3]+a[4]+a[5]+a[6]+a[7]+a[8]+a[9]+a[10]+a[11]+a[12]+a[13]+a[14]+a[15];
> > > > > > > return sum;
> > > > > > > }
> > > > > > >
> > > > > > >
> > > > > > > This code is not vectorized by SLP
vectorization.
> > > > > > >
> > > > > > >
> > > > > > > IR before vectorization:
> > > > > > >
> > > > > > >
> > > > > > > test.ll
> > > > > > >
> > > > > > >
> > > > > > > target datalayout >
"e-m:e-p:32:32-f64:32:64-f80:32-n8:16:32-S128"
> > > > > > > target triple =
"x86_64-pc-linux-gnu"
> > > > > > >
> > > > > > > ; Function Attrs: nounwind readonly
> > > > > > > define i32 @foo(i32* nocapture readonly %a,
i32 %n) #0 {
> > > > > > > entry:
> > > > > > >   %0 = load i32* %a, align 4, !tbaa !1
> > > > > > >   %arrayidx1 = getelementptr inbounds i32*
%a, i32 1
> > > > > > >   %1 = load i32* %arrayidx1, align 4, !tbaa
!1
> > > > > > >   %add = add nsw i32 %1, %0
> > > > > > >   %arrayidx2 = getelementptr inbounds i32*
%a, i32 2
> > > > > > >   %2 = load i32* %arrayidx2, align 4, !tbaa
!1
> > > > > > >   %add3 = add nsw i32 %add, %2
> > > > > > >   %arrayidx4 = getelementptr inbounds i32*
%a, i32 3
> > > > > > >   %3 = load i32* %arrayidx4, align 4, !tbaa
!1
> > > > > > >   %add5 = add nsw i32 %add3, %3
> > > > > > >   %arrayidx6 = getelementptr inbounds i32*
%a, i32 4
> > > > > > >   %4 = load i32* %arrayidx6, align 4, !tbaa
!1
> > > > > > >   %add7 = add nsw i32 %add5, %4
> > > > > > >   %arrayidx8 = getelementptr inbounds i32*
%a, i32 5
> > > > > > >   %5 = load i32* %arrayidx8, align 4, !tbaa
!1
> > > > > > >   %add9 = add nsw i32 %add7, %5
> > > > > > >   %arrayidx10 = getelementptr inbounds i32*
%a, i32 6
> > > > > > >   %6 = load i32* %arrayidx10, align 4, !tbaa
!1
> > > > > > >   %add11 = add nsw i32 %add9, %6
> > > > > > >   %arrayidx12 = getelementptr inbounds i32*
%a, i32 7
> > > > > > >   %7 = load i32* %arrayidx12, align 4, !tbaa
!1
> > > > > > >   %add13 = add nsw i32 %add11, %7
> > > > > > >   %arrayidx14 = getelementptr inbounds i32*
%a, i32 8
> > > > > > >   %8 = load i32* %arrayidx14, align 4, !tbaa
!1
> > > > > > >   %add15 = add nsw i32 %add13, %8
> > > > > > >   %arrayidx16 = getelementptr inbounds i32*
%a, i32 9
> > > > > > >   %9 = load i32* %arrayidx16, align 4, !tbaa
!1
> > > > > > >   %add17 = add nsw i32 %add15, %9
> > > > > > >   %arrayidx18 = getelementptr inbounds i32*
%a, i32 10
> > > > > > >   %10 = load i32* %arrayidx18, align 4, !tbaa
!1
> > > > > > >   %add19 = add nsw i32 %add17, %10
> > > > > > >   %arrayidx20 = getelementptr inbounds i32*
%a, i32 11
> > > > > > >   %11 = load i32* %arrayidx20, align 4, !tbaa
!1
> > > > > > >   %add21 = add nsw i32 %add19, %11
> > > > > > >   %arrayidx22 = getelementptr inbounds i32*
%a, i32 12
> > > > > > >   %12 = load i32* %arrayidx22, align 4, !tbaa
!1
> > > > > > >   %add23 = add nsw i32 %add21, %12
> > > > > > >   %arrayidx24 = getelementptr inbounds i32*
%a, i32 13
> > > > > > >   %13 = load i32* %arrayidx24, align 4, !tbaa
!1
> > > > > > >   %add25 = add nsw i32 %add23, %13
> > > > > > >   %arrayidx26 = getelementptr inbounds i32*
%a, i32 14
> > > > > > >   %14 = load i32* %arrayidx26, align 4, !tbaa
!1
> > > > > > >   %add27 = add nsw i32 %add25, %14
> > > > > > >   %arrayidx28 = getelementptr inbounds i32*
%a, i32 15
> > > > > > >   %15 = load i32* %arrayidx28, align 4, !tbaa
!1
> > > > > > >   %add29 = add nsw i32 %add27, %15
> > > > > > >   ret i32 %add29
> > > > > > > }
> > > > > > >
> > > > > > > $ opt -S -slp-vectorizer -slp-vectorize-hor
test.ll -debug -o
> test2.ll
> > > > > > >
> > > > > > > Features:+64bit,+sse2
> > > > > > > CPU:generic
> > > > > > >
> > > > > > > Subtarget features: SSELevel 3, 3DNowLevel 0,
64bit 1
> > > > > > > SLP: Analyzing blocks in foo.
> > > > > > >
> > > > > > >
> > > > > > > test2.ll (IR after SLP vectorization) :
> > > > > > >
> > > > > > > target datalayout >
"e-m:e-p:32:32-f64:32:64-f80:32-n8:16:32-S128"
> > > > > > > target triple =
"x86_64-pc-linux-gnu"
> > > > > > >
> > > > > > > ; Function Attrs: nounwind readonly
> > > > > > > define i32 @foo(i32* nocapture readonly %a,
i32 %n) #0 {
> > > > > > > entry:
> > > > > > >   %0 = load i32* %a, align 4, !tbaa !1
> > > > > > >   %arrayidx1 = getelementptr inbounds i32*
%a, i32 1
> > > > > > >   %1 = load i32* %arrayidx1, align 4, !tbaa
!1
> > > > > > >   %add = add nsw i32 %1, %0
> > > > > > >   %arrayidx2 = getelementptr inbounds i32*
%a, i32 2
> > > > > > >   %2 = load i32* %arrayidx2, align 4, !tbaa
!1
> > > > > > >   %add3 = add nsw i32 %add, %2
> > > > > > >   %arrayidx4 = getelementptr inbounds i32*
%a, i32 3
> > > > > > >   %3 = load i32* %arrayidx4, align 4, !tbaa
!1
> > > > > > >   %add5 = add nsw i32 %add3, %3
> > > > > > >   %arrayidx6 = getelementptr inbounds i32*
%a, i32 4
> > > > > > >   %4 = load i32* %arrayidx6, align 4, !tbaa
!1
> > > > > > >   %add7 = add nsw i32 %add5, %4
> > > > > > >   %arrayidx8 = getelementptr inbounds i32*
%a, i32 5
> > > > > > >   %5 = load i32* %arrayidx8, align 4, !tbaa
!1
> > > > > > >   %add9 = add nsw i32 %add7, %5
> > > > > > >   %arrayidx10 = getelementptr inbounds i32*
%a, i32 6
> > > > > > >   %6 = load i32* %arrayidx10, align 4, !tbaa
!1
> > > > > > >   %add11 = add nsw i32 %add9, %6
> > > > > > >   %arrayidx12 = getelementptr inbounds i32*
%a, i32 7
> > > > > > >   %7 = load i32* %arrayidx12, align 4, !tbaa
!1
> > > > > > >   %add13 = add nsw i32 %add11, %7
> > > > > > >   %arrayidx14 = getelementptr inbounds i32*
%a, i32 8
> > > > > > >   %8 = load i32* %arrayidx14, align 4, !tbaa
!1
> > > > > > >   %add15 = add nsw i32 %add13, %8
> > > > > > >   %arrayidx16 = getelementptr inbounds i32*
%a, i32 9
> > > > > > >   %9 = load i32* %arrayidx16, align 4, !tbaa
!1
> > > > > > >   %add17 = add nsw i32 %add15, %9
> > > > > > >   %arrayidx18 = getelementptr inbounds i32*
%a, i32 10
> > > > > > >   %10 = load i32* %arrayidx18, align 4, !tbaa
!1
> > > > > > >   %add19 = add nsw i32 %add17, %10
> > > > > > >   %arrayidx20 = getelementptr inbounds i32*
%a, i32 11
> > > > > > >   %11 = load i32* %arrayidx20, align 4, !tbaa
!1
> > > > > > >   %add21 = add nsw i32 %add19, %11
> > > > > > >   %arrayidx22 = getelementptr inbounds i32*
%a, i32 12
> > > > > > >   %12 = load i32* %arrayidx22, align 4, !tbaa
!1
> > > > > > >   %add23 = add nsw i32 %add21, %12
> > > > > > >   %arrayidx24 = getelementptr inbounds i32*
%a, i32 13
> > > > > > >   %13 = load i32* %arrayidx24, align 4, !tbaa
!1
> > > > > > >   %add25 = add nsw i32 %add23, %13
> > > > > > >   %arrayidx26 = getelementptr inbounds i32*
%a, i32 14
> > > > > > >   %14 = load i32* %arrayidx26, align 4, !tbaa
!1
> > > > > > >   %add27 = add nsw i32 %add25, %14
> > > > > > >   %arrayidx28 = getelementptr inbounds i32*
%a, i32 15
> > > > > > >   %15 = load i32* %arrayidx28, align 4, !tbaa
!1
> > > > > > >   %add29 = add nsw i32 %add27, %15
> > > > > > >   ret i32 %add29
> > > > > > > }
> > > > > > >
> > > > > > >
> > > > > > > Shouldn't the SLP vectorizer vectorize
above code? Am I
> missing out something?
> > > > > > >
> > > > > > > How does loop unrolling affect the final
vectorization of code?
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > >
> > > > > >
> > > > > >
> > > > > >
> > > > > > Hi Suyog,
> > > > > >
> > > > > >
> > > > > > Thank you for taking the time to investigate the
performance of
> the vectorizers. You are correct that the SLP-vectorizer should be able to
> do something about the second case (the unrolled one).  Please look into
> line 2861 in the SLP-vectorizer. This is where we try to analyze reductions
> and vectorize them. At the moment we don’t have support for a flat yet
> large reduction that is the result of unrolled loops because the current
> algorithm tries to construct trees that start at the chains, and it does
> not support joining multiple trees.
> > > > > >
> > > > > >
> > > > > >
> http://llvm.org/docs/doxygen/html/SLPVectorizer_8cpp_source.html#l02861
> > > > > >
> > > > > >
> > > > > > Thanks,
> > > > > > Nadav
> > > > > >
> > > > > >
> > > > > >
> > > > > >
> > > > > > > I tried to debug above IR. Since there is no
store in above
> IR, SLP vectorization doesn't call
> > > > > > > vectorizeStoreChains(). In
vectorizeChainsInBlock(), as there
> is no phi node in above IR, it
> > > > > > > also fails to vectorize the IR.
> > > > > > >
> > > > > > >
> > > > > > > If it is perfectly legal to vectorize above
IR, are we lacking
> code for it right now? Or its not
> > > > > > >
> > > > > > > possible to vectorize above code (as far as i
know, it is
> perfectly possible to vectorize above code)?
> > > > > > >
> > > > > > > If its possible, can someone help me/point
out specifics how
> to start for implementing vectorization for such code?
> > > > > > >
> > > > > > > (We do have function calls
isConsecutiveAccess() to identify
> it. Is it a case for horizontal reduction, though the term
> > > > > > > 'reduction' is associated with
loops/phi nodes.)
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > > This brings to me another question - if we
perform aggressive
> loop unrolling, we might loose opportunity for
> > > > > > >
> > > > > > > vectorization as visible above !!
> > > > > > >
> > > > > > >
> > > > > > > (I was looking into bug 20035, when i
encountered above issue.
> Though both are not related.)
> > > > > > >
> > > > > > >
> > > > > > > Your comments/suggestions are most awaited.
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > > --
> > > > > > > With regards,
> > > > > > > Suyog Sarda
> > > > > > >
> >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> >
> > > > > > >
> > > > > > >
> > > > > >
> > > > > >
> > > > > >
> > > > > >
> > > > >
> > > > >
> > > > >
> > > > >
> > > > > --
> > > > > With regards,
> > > > > Suyog Sarda
> > > > >
> >
> > > > >
> > > > >
> >
> > > > >
> > > > >
> > > >
> > > >
> > > >
> > > >
> > >
> > >
> > >
> > >
> > > --
> > > With regards,
> > > Suyog Sarda
> > >
> >
> > >
> > >
> >
> > >
> > >
> > >
> >
> >
> >
> >
> > --
> > With regards,
> > Suyog Sarda
> >
> >
> >
> >
> >
> >
>-------------- next part --------------
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suyog sarda

2014-Nov-11 18:28 UTC

head link

[LLVMdev] [Vectorization] Mis match in code generated

Hi Arnold, James

Thanks for getting back on this. Arnold i will look into patches provided
by you
and get back on it. Thanks for it.

Adding few more observations :

The expression tree is like

sum = (a[0] + a[2]) + (a[1] + a[3]); --> which is vectorizable with current
code.

If the array a[] if of type float/double then there is no
disturbance/canonicalization
(precision issues??) in formed tree and we get a vectorized code.

However, if the array a[] is of type int, then re-associate pass (runs in
O1)
re-organizes this into

sum = (((a[0] + a[2]) + a[1]) + a[3]).

This results in loss of vectorization opportunity as we do not vectorize
this type
of tree in current code stated earlier in the thread.

Also, we do not build vectorization tree on return in current code
(PR20035),
which does not vectorizes code like this :

return a[0] + a[1] + a[2] + a[3];

I will try to work on vectorization on return statement. Inputs are always
welcomed.

Regards,
Suyog

On Mon, Nov 10, 2014 at 9:13 PM, James Molloy <james at jamesmolloy.co.uk>
wrote:
> Hi Suyog,
>
> Thanks for looking at this. This has recently got itself onto my TODO list
> too.
>
> > I am not sure how much all this will improve the code quality for
> horizontal reduction
> > (donno how frequently such pattern of horizontal reduction from same
> array occurs in real world/SPECS).
>
> Actually the main loop of 470.lbm can be SLP vectorized like this. We have
> three parts to it: A fully unrolled reduction, a scatter/gather part (not
> really vectorizable) and a contiguous-load-scatter-store part which should
> be vectorized even when scatter stores are not available in HW.
>
>
> Cheers,
>
> James
>
> On 10 November 2014 14:30, Arnold Schwaighofer <aschwaighofer at
apple.com>
> wrote:
>
>> Hi Suyog,
>>
>> the horizontal reduction code needs work. It was written long ago and
was
>> never enabled so it has bit rotted somewhat and has lurking bugs.
>> For example, it could not handle reduction value nodes that were not
>> binary operations.
>>
>> It could vectorize
>>
>> (+ (* x y) (*z a) (*b c) (*d e))
>>
>> but not
>>
>>
>> (+ (load a) (load b) (load c) (load d))
>>
>>
>> With the attached patches:
>> 0001-Test-hor-redux.patch
>> 0002-Print-out-tree.patch
>>
>> We would attempt to vectorize the tree stemming from your example:
>>
>>
>> > float a[4], sum;
>> > void foo() {
>> >   sum = a[0]+a[1]+a[2]+a[3];
>> > }
>>
>> but because we happen to end up with the vector tuple (a[1],
>> a[0],a[2],a[3)) in need of gathering the existing code fails. Note,
that I
>> used fast-math because the horizontal reduction code assumes it can
>> reassociate freely.
>>
>> > clang -O3 test_hor_redux.c -emit-llvm -S -o - -mllvm
>> -slp-vectorize-hor-store  -debug-only=SLP -ffast-math -mllvm
-debug-only=SLP
>>
>> ...
>>
>>   Reduced val:   %1 = load float* getelementptr inbounds ([4 x float]*
>> @a, i64 0, i64 1), align 4, !tbaa !1
>>   Reduced val:   %0 = load float* getelementptr inbounds ([4 x float]*
>> @a, i64 0, i64 0), align 16, !tbaa !1
>>   Reduced val:   %2 = load float* getelementptr inbounds ([4 x float]*
>> @a, i64 0, i64 2), align 8, !tbaa !1
>>   Reduced val:   %3 = load float* getelementptr inbounds ([4 x float]*
>> @a, i64 0, i64 3), align 4, !tbaa !1
>>   Reduction ops:   %add = fadd fast float %1, %0
>>   Reduction ops:   %add1 = fadd fast float %add, %2
>>   Reduction ops:   %add2 = fadd fast float %add1, %3
>> Assertion failed: (VectorizedValue && "Need to have a
vectorized tree
>> node"), function emitReduction, file
>> ../lib/Transforms/Vectorize/SLPVectorizer.cpp, line 3518.
>>
>> The reduction looks like
>>
>> (((a[1] + a[0]) + a[2]) + a[3])
>>
>> So we build a tree entry  (load a[1], load a[0], load a[2], load a[3])
>> and end up with a vectorized tree entry of one who needs gathering.
>>
>> The code does not handle this case correctly (in normal slp mode there
is
>> no point in "vectorizing" a single entry tree that needs
gathering).
>> The patch
>> 0003-We-don-t-correctly-vectorize-single-entry-gather-nod.patch fixes
this
>> by disabling vectorization in such a case but then we don't
vectorize.
>> As you can see this needs more work.
>>
>> * We could reassociate reductions like the one above.
>>
>> (((a[1] + a[0]) + a[2]) + a[3])
>>
>> =>
>>
>> (((a[0] + a[1]) + a[2]) + a[3])
>>
>> Then the reduction tree builder code would not have to be clever. That
>> will only work if your initial reduction values are loads. If the loads
are
>> hidden behind a deeper tree that won't help. In such a case the
next
>> solution would not be so bad though.
>>
>> * We could teach the tree code to do a vector load + permute operation
if
>> applicable. This will no generate the best code though. But for deeper
>> trees the overhead of the permute probably does not matter much.
>>
>>
>> Best,
>> Arnold
>>
>> On 11/09/14, suyog sarda   wrote:
>> > Hi Arnold, Nadav, Hal,
>> > all,
>> >
>> >
>> > Restarting this thread with few more observations on horizontal
>> reduction store
>> > (after using flags - slp-vectorize-hor-store and
-slp-vectorize-hor,
>> thanks Arnold for pointing out earlier).
>> >
>> >
>> > The SLP vectorizer does vectorize straight line code :
>> >
>> >
>> > (this code may result as part of loop unrolling as stated earlier
in
>> the thread.
>> > Though for loop vectorization , trip count should be atleast 16,
taking
>> smaller
>> > code here to put some findings.)
>> >
>> >
>> > float a[4], sum;
>> >
>> > void foo() {
>> >
>> >  int i;
>> >
>> >  for(i=0;i<4;i++);
>> >
>> >    sum += a[i];
>> > }
>> >
>> > after loop unrolling -
>> >
>> > float a[4], sum;
>> > void foo() {
>> >   sum = a[0]+a[1]+a[2]+a[3];
>> > }
>> >
>> >
>> > This code gets vectorized depending on how we organize the code,
and
>> subsequently
>> >
>> > how the expression tree is formed.
>> >
>> >
>> > case 1:
>> >
>> > float a[4], sum;
>> > void foo() {
>> >   sum = a[0]+a[1]+a[2]+a[3];
>> > }
>> >
>> >
>> > The expression tree for this will be
>> >
>> >
>> >     a[0]    a[1]
>> >
>> >        \       /
>> >         \     /
>> >
>> >            +      a[2]
>> >
>> >             \     /
>> >              \   /
>> >
>> >                +       a[3]
>> >
>> >                  \      /
>> >                   \    /
>> >                     +
>> >                      |
>> >                      |
>> >                      ↓
>> >
>> >                      sum
>> >
>> >
>> > This doesn't vectorize, because in function
tryToVectorizeList(), we
>> check if the
>> >
>> > scalar instruction are of the same type. In above case, it will be
fadd
>> and load,
>> >
>> > and hence no vectorization takes place.
>> >
>> >
>> >
>> > case 2:
>> >
>> > float a[4], sum;
>> > void foo() {
>> >   sum = (a[0]+a[1])+(a[2]+a[3]);
>> > }
>> >
>> >
>> > The expression tree for this will be (notice brackets above):
>> >
>> >
>> > a[0]    a[1]      a[2]    a[3]
>> >
>> >    \       /            \        /
>> >     \     /              \      /
>> >        +                   +
>> >          \                /
>> >           \              /
>> >            \            /
>> >                  +
>> >                    |
>> >                   |
>> >                   ↓
>> >                  sum
>> >
>> >
>> > In this case, in function tryToVectorizeList(), both the scalar
>> instructions are
>> >
>> > same i.e. fadd. Hence we proceed for vectorization ahead.
>> >
>> > But this still doesn't vectorizes the code. Ahead, while
trying to
>> schedule bundle of code,
>> >
>> > it checks whether the loads are for consecutive memory access
across
>> two subtrees from
>> > same base pointer.
>> >
>> >
>> > For above code, it checks if (a[0],a[2]) and (a[1],a[3]) are
>> consecutive memory
>> > access (which, obviously, they are not). This cancels scheduling
of
>> bundle of loads,
>> > and hence calculated cost for non-consecutive loads comes greater
>> increasing overall
>> >
>> > cost of vectorization (and hence no vectorization).
>> >
>> >
>> > Seems this check for consecutive memory access was written keeping
in
>> mind following sort of code :
>> >
>> > sum = (a[0] + b[0]) + (a[1] + b[1]);
>> >
>> >
>> >
>> > Finally,
>> >
>> > case 3:
>> >
>> > float a[4], sum;
>> > void foo() {
>> >   sum = (a[0]+a[2])+(a[1]+a[3]);
>> > }
>> >
>> >
>> > The expression tree for this will be (notice brackets above):
>> >
>> >
>> > a[0]    a[2]      a[1]    a[3]
>> >
>> >    \       /            \        /
>> >     \     /              \      /
>> >        +                   +
>> >          \                /
>> >           \              /
>> >            \            /
>> >                  +
>> >                    |
>> >                   |
>> >                   ↓
>> >                  sum
>> >
>> >
>> >
>> > This code gets vectorized, as tryToVectorizeList() gets both
scalar
>> operation as fadd,
>> >
>> > as well as there is a consecutive memory access across subtress
rooted
>> at both fadd.
>> >
>> >
>> > case 1 IR after SLP vectorization :
>> >
>> > define void @foo() #0 {
>> > entry:
>> >   %0 = load float* getelementptr inbounds ([8 x float]* @a, i64 0,
i64
>> 0), align 16, !tbaa !1
>> >   %1 = load float* getelementptr inbounds ([8 x float]* @a, i64 0,
i64
>> 1), align 4, !tbaa !1
>> >   %add = fadd float %0, %1
>> >   %2 = load float* getelementptr inbounds ([8 x float]* @a, i64 0,
i64
>> 2), align 8, !tbaa !1
>> >   %add1 = fadd float %add, %2
>> >   %3 = load float* getelementptr inbounds ([8 x float]* @a, i64 0,
i64
>> 3), align 4, !tbaa !1
>> >   %add2 = fadd float %add1, %3
>> >   store float %add2, float* @sum, align 4, !tbaa !1
>> >   ret void
>> > }
>> >
>> >
>> > case 2 IR after SLP vectorization :
>> >
>> > define void @foo() #0 {
>> > entry:
>> >   %0 = load float* getelementptr inbounds ([8 x float]* @a, i64 0,
i64
>> 0), align 16, !tbaa !1
>> >   %1 = load float* getelementptr inbounds ([8 x float]* @a, i64 0,
i64
>> 1), align 4, !tbaa !1
>> >   %add = fadd float %0, %1
>> >   %2 = load float* getelementptr inbounds ([8 x float]* @a, i64 0,
i64
>> 2), align 8, !tbaa !1
>> >   %3 = load float* getelementptr inbounds ([8 x float]* @a, i64 0,
i64
>> 3), align 4, !tbaa !1
>> >   %add1 = fadd float %2, %3
>> >   %add2 = fadd float %add, %add1
>> >   store float %add2, float* @sum, align 4, !tbaa !1
>> >   ret void
>> > }
>> >
>> >
>> > case 3 IR after SLP vectorization :
>> >
>> >
>> > define void @foo() #0 {
>> > entry:
>> >   %0 = load <2 x float>* bitcast ([4 x float]* @a to <2 x
float>*),
>> align 16, !tbaa !1
>> >   %1 = load <2 x float>* bitcast (float* getelementptr
inbounds ([4 x
>> float]* @a, i64 0, i64 2) to <2 x float>*), align 8, !tbaa !1
>> >   %2 = fadd <2 x float> %0, %1
>> >   %3 = extractelement <2 x float> %2, i32 0
>> >   %4 = extractelement <2 x float> %2, i32 1
>> >   %add2 = fadd float %3, %4
>> >   store float %add2, float* @sum, align 4, !tbaa !1
>> >   ret void
>> > }
>> >
>> >
>> >
>> > Few cases of improvements, as visible from above (noting down
roughly,
>> didn't give detail thought on it yet):
>> >
>> > 1. The IR expression tree can be re-organized to cater above need
(some
>> kind of balancing like AVL tree).
>> >
>> >     Alternatively, parse the expression tree without changing it
and
>> look upward tree if we encounter a
>> >
>> >     load instruction.
>> >
>> > 2. Seems, there is a case for improvement in checking if memory
access
>> are consecutive.
>> >     This needs to take into consideration all the loads of all the
>> subtree .
>> >      If all the loads are from same base pointer, then are the
memory
>> access in same subtree as
>> >      well as across the subtree consecutive. (i will try to write
some
>> code on this, any suggestions are welcomed)
>> >
>> >
>> >
>> > I am not sure how much all this will improve the code quality for
>> horizontal reduction
>> > (donno how frequently such pattern of horizontal reduction from
same
>> array occurs in real world/SPECS).
>> >
>> > Perhaps the best case i can think of is when loops are unrolled as
>> noted earlier in the thread.
>> >
>> >
>> > Adding few more people to pitch in !!
>> >
>> >
>> > Comments/Suggestions are most welcomed.
>> >
>> >
>> > Regards,
>> >
>> > Suyog
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> > On Sat, Sep 20, 2014 at 12:05 AM, suyog sarda <sardask01 at
gmail.com <
>> sardask01 at gmail.com>> wrote:
>> >
>> > > Hi Arnold,
>> > >
>> > >
>> > > Thanks for your reply.
>> > >
>> > >
>> > > I tried test case as suggested by you.
>> > >
>> > > void foo(int *a, int *sum) {
>> > > *sum >>
a[0]+a[1]+a[2]+a[3]+a[4]+a[5]+a[6]+a[7]+a[8]+a[9]+a[10]+a[11]+a[12]+a[13]+a[14]+a[15];
>> > > }
>> > >
>> > >
>> > > so that it has a 'store' in its IR.
>> > >
>> > >
>> > > IR before vectorization :
>> > >
>> > > target datalayout =
"e-m:e-p:32:32-f64:32:64-f80:32-n8:16:32-S128"
>> > > target triple = "x86_64-pc-linux-gnu"
>> > >
>> > > ; Function Attrs: nounwind
>> > > define void @foo(i32* nocapture readonly %a, i32* nocapture
%sum) #0 {
>> > > entry:
>> > >   %0 = load i32* %a, align 4, !tbaa !1
>> > >   %arrayidx1 = getelementptr inbounds i32* %a, i32 1
>> > >   %1 = load i32* %arrayidx1, align 4, !tbaa !1
>> > >   %add = add nsw i32 %1, %0
>> > >   %arrayidx2 = getelementptr inbounds i32* %a, i32 2
>> > >   %2 = load i32* %arrayidx2, align 4, !tbaa !1
>> > >   %add3 = add nsw i32 %add, %2
>> > >   %arrayidx4 = getelementptr inbounds i32* %a, i32 3
>> > >   %3 = load i32* %arrayidx4, align 4, !tbaa !1
>> > >   %add5 = add nsw i32 %add3, %3
>> > >   %arrayidx6 = getelementptr inbounds i32* %a, i32 4
>> > >   %4 = load i32* %arrayidx6, align 4, !tbaa !1
>> > >   %add7 = add nsw i32 %add5, %4
>> > >   %arrayidx8 = getelementptr inbounds i32* %a, i32 5
>> > >   %5 = load i32* %arrayidx8, align 4, !tbaa !1
>> > >   %add9 = add nsw i32 %add7, %5
>> > >   %arrayidx10 = getelementptr inbounds i32* %a, i32 6
>> > >   %6 = load i32* %arrayidx10, align 4, !tbaa !1
>> > >   %add11 = add nsw i32 %add9, %6
>> > >   %arrayidx12 = getelementptr inbounds i32* %a, i32 7
>> > >   %7 = load i32* %arrayidx12, align 4, !tbaa !1
>> > >   %add13 = add nsw i32 %add11, %7
>> > >   %arrayidx14 = getelementptr inbounds i32* %a, i32 8
>> > >   %8 = load i32* %arrayidx14, align 4, !tbaa !1
>> > >   %add15 = add nsw i32 %add13, %8
>> > >   %arrayidx16 = getelementptr inbounds i32* %a, i32 9
>> > >   %9 = load i32* %arrayidx16, align 4, !tbaa !1
>> > >   %add17 = add nsw i32 %add15, %9
>> > >   %arrayidx18 = getelementptr inbounds i32* %a, i32 10
>> > >   %10 = load i32* %arrayidx18, align 4, !tbaa !1
>> > >   %add19 = add nsw i32 %add17, %10
>> > >   %arrayidx20 = getelementptr inbounds i32* %a, i32 11
>> > >   %11 = load i32* %arrayidx20, align 4, !tbaa !1
>> > >   %add21 = add nsw i32 %add19, %11
>> > >   %arrayidx22 = getelementptr inbounds i32* %a, i32 12
>> > >   %12 = load i32* %arrayidx22, align 4, !tbaa !1
>> > >   %add23 = add nsw i32 %add21, %12
>> > >   %arrayidx24 = getelementptr inbounds i32* %a, i32 13
>> > >   %13 = load i32* %arrayidx24, align 4, !tbaa !1
>> > >   %add25 = add nsw i32 %add23, %13
>> > >   %arrayidx26 = getelementptr inbounds i32* %a, i32 14
>> > >   %14 = load i32* %arrayidx26, align 4, !tbaa !1
>> > >   %add27 = add nsw i32 %add25, %14
>> > >   %arrayidx28 = getelementptr inbounds i32* %a, i32 15
>> > >   %15 = load i32* %arrayidx28, align 4, !tbaa !1
>> > >   %add29 = add nsw i32 %add27, %15
>> > >
>> > >
>> > >   store i32 %add29, i32* %sum, align 4, !tbaa !1
>> > >   ret void
>> > > }
>> > >
>> > >
>> > >
>> > > IR after SLP vectorization with appropriate flags :
>> > >
>> > > $ opt -S -slp-vectorizer -slp-vectorize-hor=1
>> -slp-vectorize-hor-store=1 test.ll -debug
>> > >
>> > >
>> > > (I hope i am passing the args correctly to opt)
>> > >
>> > > Subtarget features: SSELevel 3, 3DNowLevel 0, 64bit 1
>> > > SLP: Analyzing blocks in foo.
>> > > SLP: Found 1 stores to vectorize.
>> > > SLP: Vectorizing a list of length = 2.
>> > > ; ModuleID = 'test.ll'
>> > > target datalayout =
"e-m:e-p:32:32-f64:32:64-f80:32-n8:16:32-S128"
>> > > target triple = "x86_64-pc-linux-gnu"
>> > >
>> > > ; Function Attrs: nounwind
>> > > define void @foo(i32* nocapture readonly %a, i32* nocapture
%sum) #0 {
>> > > entry:
>> > >   %0 = load i32* %a, align 4, !tbaa !1
>> > >   %arrayidx1 = getelementptr inbounds i32* %a, i32 1
>> > >   %1 = load i32* %arrayidx1, align 4, !tbaa !1
>> > >   %add = add nsw i32 %1, %0
>> > >   %arrayidx2 = getelementptr inbounds i32* %a, i32 2
>> > >   %2 = load i32* %arrayidx2, align 4, !tbaa !1
>> > >   %add3 = add nsw i32 %add, %2
>> > >   %arrayidx4 = getelementptr inbounds i32* %a, i32 3
>> > >   %3 = load i32* %arrayidx4, align 4, !tbaa !1
>> > >   %add5 = add nsw i32 %add3, %3
>> > >   %arrayidx6 = getelementptr inbounds i32* %a, i32 4
>> > >   %4 = load i32* %arrayidx6, align 4, !tbaa !1
>> > >   %add7 = add nsw i32 %add5, %4
>> > >   %arrayidx8 = getelementptr inbounds i32* %a, i32 5
>> > >   %5 = load i32* %arrayidx8, align 4, !tbaa !1
>> > >   %add9 = add nsw i32 %add7, %5
>> > >   %arrayidx10 = getelementptr inbounds i32* %a, i32 6
>> > >   %6 = load i32* %arrayidx10, align 4, !tbaa !1
>> > >   %add11 = add nsw i32 %add9, %6
>> > >   %arrayidx12 = getelementptr inbounds i32* %a, i32 7
>> > >   %7 = load i32* %arrayidx12, align 4, !tbaa !1
>> > >   %add13 = add nsw i32 %add11, %7
>> > >   %arrayidx14 = getelementptr inbounds i32* %a, i32 8
>> > >   %8 = load i32* %arrayidx14, align 4, !tbaa !1
>> > >   %add15 = add nsw i32 %add13, %8
>> > >   %arrayidx16 = getelementptr inbounds i32* %a, i32 9
>> > >   %9 = load i32* %arrayidx16, align 4, !tbaa !1
>> > >   %add17 = add nsw i32 %add15, %9
>> > >   %arrayidx18 = getelementptr inbounds i32* %a, i32 10
>> > >   %10 = load i32* %arrayidx18, align 4, !tbaa !1
>> > >   %add19 = add nsw i32 %add17, %10
>> > >   %arrayidx20 = getelementptr inbounds i32* %a, i32 11
>> > >   %11 = load i32* %arrayidx20, align 4, !tbaa !1
>> > >   %add21 = add nsw i32 %add19, %11
>> > >   %arrayidx22 = getelementptr inbounds i32* %a, i32 12
>> > >   %12 = load i32* %arrayidx22, align 4, !tbaa !1
>> > >   %add23 = add nsw i32 %add21, %12
>> > >   %arrayidx24 = getelementptr inbounds i32* %a, i32 13
>> > >   %13 = load i32* %arrayidx24, align 4, !tbaa !1
>> > >   %add25 = add nsw i32 %add23, %13
>> > >   %arrayidx26 = getelementptr inbounds i32* %a, i32 14
>> > >   %14 = load i32* %arrayidx26, align 4, !tbaa !1
>> > >   %add27 = add nsw i32 %add25, %14
>> > >   %arrayidx28 = getelementptr inbounds i32* %a, i32 15
>> > >   %15 = load i32* %arrayidx28, align 4, !tbaa !1
>> > >   %add29 = add nsw i32 %add27, %15
>> > >
>> > >
>> > >   store i32 %add29, i32* %sum, align 4, !tbaa !1
>> > >   ret void
>> > > }
>> > >
>> > >
>> > > As observed above, SLP vectorization doesn't vectorize
this code.
>> > >
>> > >
>> > > I tried debugging, just mentioning what i found -
>> > > the code hits vectorizeChainsInBlock() ->
>> if(ShouldStartVectorizeHorAtStore) ->
>> > > tryToVectorize() -> tryToVectorizePair() ->
tryToVectorizeList() -
>> inside this function, it iterates in the
>> > >
>> > > for loop for checking if scalar instructions are of same
type. It
>> exits for 2nd iteration in the loop as
>> > >
>> > > OpCode does not match , one opcode is 'add' and
second is 'load'. So
>> it exits from function
>> > > 'tryToVectorizeList()', and comes back to function
>> 'tryToVectorize()', but fails to satisfy any of the
>> > >
>> > > further 'if' in that function and returns back
without vectorizing
>> any of the code.
>> > >
>> > >
>> > > I will try to dig more into it and try to understand where
the code
>> can be implemented.
>> > >
>> > >
>> > > Comments/suggestions/explanations are always welcomed !!
>> > >
>> > >
>> > >
>> > >
>> > >
>> > >
>> > > On Fri, Sep 19, 2014 at 1:49 AM, Arnold <aschwaighofer at
apple.com <
>> aschwaighofer at apple.com>> wrote:
>> > >
>> > > > There is experimental code to handle horizontal
reductions hidden
>> behind a flag "slp-vectorize-hor" you could try to enable
that. It won't
>> currently work for your example though because we only start to look
for
>> reductions at phis and stores "slp-vectorize-hor-stores".
>> > > >
>> > > >
>> > > > You could start off by rewriting your example with a
store and see
>> whether the tree match works after using both flags.
>> > > >
>> > > > F(int *sum ...){
>> > > > *sum >>
a[0]+a[1]+a[2]+a[3]+a[4]+a[5]+a[6]+a[7]+a[8]+a[9]+a[10]+a[11]+a[12]+a[13]+a[14]+a[15];
>> > > > }
>> > > >
>> > > >
>> > > > If it works we would only need to look for horizontal
reductions at
>> returns.
>> > > >
>> > > >
>> > > >
>> > > >
>> > > >
>> > > >
>> > > > Sent from my iPhone
>> > > >
>> > > > On Sep 18, 2014, at 12:24 PM, suyog sarda <sardask01
at gmail.com <
>> sardask01 at gmail.com>> wrote:
>> > > >
>> > > >
>> > > >
>> > > > > Hi Nadav,
>> > > > >
>> > > > >
>> > > > > Thanks for the quick reply !!
>> > > > >
>> > > > >
>> > > > > Ok, so as of now we are lacking capability to
handle flat large
>> reductions.
>> > > > >
>> > > > >
>> > > > > I did go through function vectorizeChainsInBlock()
(line number
>> 2862). In this function,
>> > > > >
>> > > > > we try to vectorize if we have phi nodes in the IR
(several if's
>> check for phi nodes) i.e we try to
>> > > > >
>> > > > > construct tree that starts at chains.
>> > > > >
>> > > > >
>> > > > > Any pointers on how to join multiple trees? I will
also try to
>> dig more into it.
>> > > > >
>> > > > >
>> > > > > Comments/Suggestions are most welcomed !!
>> > > > >
>> > > > >
>> > > > > On Fri, Sep 19, 2014 at 12:23 AM, Nadav Rotem
<nrotem at apple.com <
>> nrotem at apple.com>> wrote:
>> > > > >
>> > > > > >
>> > > > > >
>> > > > > > > On Sep 18, 2014, at 11:48 AM, suyog sarda
<
>> sardask01 at gmail.com <sardask01 at gmail.com>> wrote:
>> > > > > > >
>> > > > > > > Hi,
>> > > > > > >
>> > > > > > >
>> > > > > > > I am trying to understand LLVM
vectorization implementation
>> and was looking into both loop and SLP vectorization.
>> > > > > > >
>> > > > > > >
>> > > > > > > test case 1:
>> > > > > > >
>> > > > > > >
>> > > > > > > int foo(int *a) {
>> > > > > > > int sum = 0,i;
>> > > > > > > for(i=0; i<16; i++)
>> > > > > > >   sum += a[i];
>> > > > > > > return sum;
>> > > > > > > }
>> > > > > > >
>> > > > > > >
>> > > > > > > This code is vectorized by loop
vectorizer where we calculate
>> scalar loop cost as 4 and vector loop cost as 2.
>> > > > > > >
>> > > > > > > Since vector loop cost is less and above
reduction is legal
>> to vectorize, loop vectorizer produces vectorized code :
>> > > > > > >
>> > > > > > >
>> > > > > > > IR without vectorization:
>> > > > > > >
>> > > > > > > target datalayout >>
"e-m:e-p:32:32-f64:32:64-f80:32-n8:16:32-S128"
>> > > > > > > target triple =
"x86_64-pc-linux-gnu"
>> > > > > > >
>> > > > > > > ; Function Attrs: nounwind readonly
>> > > > > > > define i32 @foo(i32* nocapture readonly
%a, i32 %n) #0 {
>> > > > > > > entry:
>> > > > > > >   br label %for.body
>> > > > > > >
>> > > > > > > for.body:                                
; preds >> %for.body, %entry
>> > > > > > >   %i.05 = phi i32 [ 0, %entry ], [ %inc,
%for.body ]
>> > > > > > >   %sum.04 = phi i32 [ 0, %entry ], [
%add, %for.body ]
>> > > > > > >   %arrayidx = getelementptr inbounds i32*
%a, i32 %i.05
>> > > > > > >   %0 = load i32* %arrayidx, align 4,
!tbaa !1
>> > > > > > >   %add = add nsw i32 %0, %sum.04
>> > > > > > >   %inc = add nsw i32 %i.05, 1
>> > > > > > >   %exitcond = icmp eq i32 %i.05, 15
>> > > > > > >   br i1 %exitcond, label %for.end, label
%for.body
>> > > > > > >
>> > > > > > > for.end:                                 
; preds >> %for.body
>> > > > > > >   ret i32 %add
>> > > > > > > }
>> > > > > > >
>> > > > > > >
>> > > > > > > IR after vectorization:
>> > > > > > >
>> > > > > > > target datalayout >>
"e-m:e-p:32:32-f64:32:64-f80:32-n8:16:32-S128"
>> > > > > > > target triple =
"x86_64-pc-linux-gnu"
>> > > > > > >
>> > > > > > > ; Function Attrs: nounwind readonly
>> > > > > > > define i32 @foo(i32* nocapture readonly
%a, i32 %n) #0 {
>> > > > > > > entry:
>> > > > > > >   %backedge.overflow = icmp eq i32 15, -1
>> > > > > > >   %overflow.check.anchor = add i32 0, 0
>> > > > > > >   br i1 %backedge.overflow, label
%scalar.ph(
>> http://scalar.ph/), label %overflow.checked
>> > > > > > >
>> > > > > > > overflow.checked:                        
; preds >> %entry
>> > > > > > >   br i1 false, label %middle.block, label
%vector.ph(
>> http://vector.ph/)
>> > > > > > >
>> > > > > > > vector.ph(http://vector.ph/):
>> ; preds = %overflow.checked
>> > > > > > >   br label %vector.body
>> > > > > > >
>> > > > > > > vector.body:                             
; preds >> %vector.body, %vector.ph(http://vector.ph/)
>> > > > > > >   %index = phi i32 [ 0,
%vector.ph(http://vector.ph/) ], [
>> %index.next, %vector.body ]
>> > > > > > >   %vec.phi = phi <4 x i32> [
zeroinitializer, %vector.ph(
>> http://vector.ph/) ], [ %14, %vector.body ]
>> > > > > > >   %broadcast.splatinsert = insertelement
<4 x i32> undef, i32
>> %index, i32 0
>> > > > > > >   %broadcast.splat = shufflevector <4
x i32>
>> %broadcast.splatinsert, <4 x i32> undef, <4 x i32>
zeroinitializer
>> > > > > > >   %induction = add <4 x i32>
%broadcast.splat, <i32 0, i32 1,
>> i32 2, i32 3>
>> > > > > > >   %0 = extractelement <4 x i32>
%induction, i32 0
>> > > > > > >   %1 = getelementptr inbounds i32* %a,
i32 %0
>> > > > > > >   %2 = insertelement <4 x i32*>
undef, i32* %1, i32 0
>> > > > > > >   %3 = extractelement <4 x i32>
%induction, i32 1
>> > > > > > >   %4 = getelementptr inbounds i32* %a,
i32 %3
>> > > > > > >   %5 = insertelement <4 x i32*> %2,
i32* %4, i32 1
>> > > > > > >   %6 = extractelement <4 x i32>
%induction, i32 2
>> > > > > > >   %7 = getelementptr inbounds i32* %a,
i32 %6
>> > > > > > >   %8 = insertelement <4 x i32*> %5,
i32* %7, i32 2
>> > > > > > >   %9 = extractelement <4 x i32>
%induction, i32 3
>> > > > > > >   %10 = getelementptr inbounds i32* %a,
i32 %9
>> > > > > > >   %11 = insertelement <4 x i32*>
%8, i32* %10, i32 3
>> > > > > > >   %12 = getelementptr i32* %1, i32 0
>> > > > > > >   %13 = bitcast i32* %12 to <4 x
i32>*
>> > > > > > >   %wide.load = load <4 x i32>* %13,
align 4, !tbaa !1
>> > > > > > >   %14 = add nsw <4 x i32>
%wide.load, %vec.phi
>> > > > > > >   %15 = add nsw <4 x i32>
%induction, <i32 1, i32 1, i32 1,
>> i32 1>
>> > > > > > >   %16 = icmp eq <4 x i32>
%induction, <i32 15, i32 15, i32
>> 15, i32 15>
>> > > > > > >   %index.next = add i32 %index, 4
>> > > > > > >   %17 = icmp eq i32 %index.next, 16
>> > > > > > >   br i1 %17, label %middle.block, label
%vector.body,
>> !llvm.loop !5
>> > > > > > >
>> > > > > > > middle.block:                            
; preds >> %vector.body, %overflow.checked
>> > > > > > >   %resume.val = phi i32 [ 0,
%overflow.checked ], [ 16,
>> %vector.body ]
>> > > > > > >   %trunc.resume.val = phi i32 [ 0,
%overflow.checked ], [ 16,
>> %vector.body ]
>> > > > > > >   %rdx.vec.exit.phi = phi <4 x i32>
[ zeroinitializer,
>> %overflow.checked ], [ %14, %vector.body ]
>> > > > > > >   %rdx.shuf = shufflevector <4 x
i32> %rdx.vec.exit.phi, <4 x
>> i32> undef, <4 x i32> <i32 2, i32 3, i32 undef, i32
undef>
>> > > > > > >   %bin.rdx = add <4 x i32>
%rdx.vec.exit.phi, %rdx.shuf
>> > > > > > >   %rdx.shuf1 = shufflevector <4 x
i32> %bin.rdx, <4 x i32>
>> undef, <4 x i32> <i32 1, i32 undef, i32 undef, i32 undef>
>> > > > > > >   %bin.rdx2 = add <4 x i32>
%bin.rdx, %rdx.shuf1
>> > > > > > >   %18 = extractelement <4 x i32>
%bin.rdx2, i32 0
>> > > > > > >   %cmp.n = icmp eq i32 16, %resume.val
>> > > > > > >   br i1 %cmp.n, label %for.end, label
%scalar.ph(
>> http://scalar.ph/)
>> > > > > > >
>> > > > > > > scalar.ph(http://scalar.ph/):
>> ; preds = %middle.block, %entry
>> > > > > > >   %bc.resume.val = phi i32 [ %resume.val,
%middle.block ], [
>> 0, %entry ]
>> > > > > > >   %bc.trunc.resume.val = phi i32 [
%trunc.resume.val,
>> %middle.block ], [ 0, %entry ]
>> > > > > > >   %bc.merge.rdx = phi i32 [ 0, %entry ],
[ %18, %middle.block
>> ]
>> > > > > > >   br label %for.body
>> > > > > > >
>> > > > > > > for.body:                                
; preds >> %for.body, %scalar.ph(http://scalar.ph/)
>> > > > > > >   %i.05 = phi i32 [ %bc.trunc.resume.val,
%scalar.ph(
>> http://scalar.ph/) ], [ %inc, %for.body ]
>> > > > > > >   %sum.04 = phi i32 [ %bc.merge.rdx,
%scalar.ph(
>> http://scalar.ph/) ], [ %add, %for.body ]
>> > > > > > >   %arrayidx = getelementptr inbounds i32*
%a, i32 %i.05
>> > > > > > >   %19 = load i32* %arrayidx, align 4,
!tbaa !1
>> > > > > > >   %add = add nsw i32 %19, %sum.04
>> > > > > > >   %inc = add nsw i32 %i.05, 1
>> > > > > > >   %exitcond = icmp eq i32 %i.05, 15
>> > > > > > >   br i1 %exitcond, label %for.end, label
%for.body,
>> !llvm.loop !8
>> > > > > > >
>> > > > > > > for.end:                                 
; preds >> %middle.block, %for.body
>> > > > > > >   %add.lcssa = phi i32 [ %add, %for.body
], [ %18,
>> %middle.block ]
>> > > > > > >   ret i32 %add.lcssa
>> > > > > > > }
>> > > > > > >
>> > > > > > >
>> > > > > > >
>> > > > > > > Now for test case 2, where we unroll the
loop totally :
>> > > > > > >
>> > > > > > > int foo(int *a) {
>> > > > > > > int sum = 0;
>> > > > > > > sum >>
a[0]+a[1]+a[2]+a[3]+a[4]+a[5]+a[6]+a[7]+a[8]+a[9]+a[10]+a[11]+a[12]+a[13]+a[14]+a[15];
>> > > > > > > return sum;
>> > > > > > > }
>> > > > > > >
>> > > > > > >
>> > > > > > > This code is not vectorized by SLP
vectorization.
>> > > > > > >
>> > > > > > >
>> > > > > > > IR before vectorization:
>> > > > > > >
>> > > > > > >
>> > > > > > > test.ll
>> > > > > > >
>> > > > > > >
>> > > > > > > target datalayout >>
"e-m:e-p:32:32-f64:32:64-f80:32-n8:16:32-S128"
>> > > > > > > target triple =
"x86_64-pc-linux-gnu"
>> > > > > > >
>> > > > > > > ; Function Attrs: nounwind readonly
>> > > > > > > define i32 @foo(i32* nocapture readonly
%a, i32 %n) #0 {
>> > > > > > > entry:
>> > > > > > >   %0 = load i32* %a, align 4, !tbaa !1
>> > > > > > >   %arrayidx1 = getelementptr inbounds
i32* %a, i32 1
>> > > > > > >   %1 = load i32* %arrayidx1, align 4,
!tbaa !1
>> > > > > > >   %add = add nsw i32 %1, %0
>> > > > > > >   %arrayidx2 = getelementptr inbounds
i32* %a, i32 2
>> > > > > > >   %2 = load i32* %arrayidx2, align 4,
!tbaa !1
>> > > > > > >   %add3 = add nsw i32 %add, %2
>> > > > > > >   %arrayidx4 = getelementptr inbounds
i32* %a, i32 3
>> > > > > > >   %3 = load i32* %arrayidx4, align 4,
!tbaa !1
>> > > > > > >   %add5 = add nsw i32 %add3, %3
>> > > > > > >   %arrayidx6 = getelementptr inbounds
i32* %a, i32 4
>> > > > > > >   %4 = load i32* %arrayidx6, align 4,
!tbaa !1
>> > > > > > >   %add7 = add nsw i32 %add5, %4
>> > > > > > >   %arrayidx8 = getelementptr inbounds
i32* %a, i32 5
>> > > > > > >   %5 = load i32* %arrayidx8, align 4,
!tbaa !1
>> > > > > > >   %add9 = add nsw i32 %add7, %5
>> > > > > > >   %arrayidx10 = getelementptr inbounds
i32* %a, i32 6
>> > > > > > >   %6 = load i32* %arrayidx10, align 4,
!tbaa !1
>> > > > > > >   %add11 = add nsw i32 %add9, %6
>> > > > > > >   %arrayidx12 = getelementptr inbounds
i32* %a, i32 7
>> > > > > > >   %7 = load i32* %arrayidx12, align 4,
!tbaa !1
>> > > > > > >   %add13 = add nsw i32 %add11, %7
>> > > > > > >   %arrayidx14 = getelementptr inbounds
i32* %a, i32 8
>> > > > > > >   %8 = load i32* %arrayidx14, align 4,
!tbaa !1
>> > > > > > >   %add15 = add nsw i32 %add13, %8
>> > > > > > >   %arrayidx16 = getelementptr inbounds
i32* %a, i32 9
>> > > > > > >   %9 = load i32* %arrayidx16, align 4,
!tbaa !1
>> > > > > > >   %add17 = add nsw i32 %add15, %9
>> > > > > > >   %arrayidx18 = getelementptr inbounds
i32* %a, i32 10
>> > > > > > >   %10 = load i32* %arrayidx18, align 4,
!tbaa !1
>> > > > > > >   %add19 = add nsw i32 %add17, %10
>> > > > > > >   %arrayidx20 = getelementptr inbounds
i32* %a, i32 11
>> > > > > > >   %11 = load i32* %arrayidx20, align 4,
!tbaa !1
>> > > > > > >   %add21 = add nsw i32 %add19, %11
>> > > > > > >   %arrayidx22 = getelementptr inbounds
i32* %a, i32 12
>> > > > > > >   %12 = load i32* %arrayidx22, align 4,
!tbaa !1
>> > > > > > >   %add23 = add nsw i32 %add21, %12
>> > > > > > >   %arrayidx24 = getelementptr inbounds
i32* %a, i32 13
>> > > > > > >   %13 = load i32* %arrayidx24, align 4,
!tbaa !1
>> > > > > > >   %add25 = add nsw i32 %add23, %13
>> > > > > > >   %arrayidx26 = getelementptr inbounds
i32* %a, i32 14
>> > > > > > >   %14 = load i32* %arrayidx26, align 4,
!tbaa !1
>> > > > > > >   %add27 = add nsw i32 %add25, %14
>> > > > > > >   %arrayidx28 = getelementptr inbounds
i32* %a, i32 15
>> > > > > > >   %15 = load i32* %arrayidx28, align 4,
!tbaa !1
>> > > > > > >   %add29 = add nsw i32 %add27, %15
>> > > > > > >   ret i32 %add29
>> > > > > > > }
>> > > > > > >
>> > > > > > > $ opt -S -slp-vectorizer
-slp-vectorize-hor test.ll -debug -o
>> test2.ll
>> > > > > > >
>> > > > > > > Features:+64bit,+sse2
>> > > > > > > CPU:generic
>> > > > > > >
>> > > > > > > Subtarget features: SSELevel 3,
3DNowLevel 0, 64bit 1
>> > > > > > > SLP: Analyzing blocks in foo.
>> > > > > > >
>> > > > > > >
>> > > > > > > test2.ll (IR after SLP vectorization) :
>> > > > > > >
>> > > > > > > target datalayout >>
"e-m:e-p:32:32-f64:32:64-f80:32-n8:16:32-S128"
>> > > > > > > target triple =
"x86_64-pc-linux-gnu"
>> > > > > > >
>> > > > > > > ; Function Attrs: nounwind readonly
>> > > > > > > define i32 @foo(i32* nocapture readonly
%a, i32 %n) #0 {
>> > > > > > > entry:
>> > > > > > >   %0 = load i32* %a, align 4, !tbaa !1
>> > > > > > >   %arrayidx1 = getelementptr inbounds
i32* %a, i32 1
>> > > > > > >   %1 = load i32* %arrayidx1, align 4,
!tbaa !1
>> > > > > > >   %add = add nsw i32 %1, %0
>> > > > > > >   %arrayidx2 = getelementptr inbounds
i32* %a, i32 2
>> > > > > > >   %2 = load i32* %arrayidx2, align 4,
!tbaa !1
>> > > > > > >   %add3 = add nsw i32 %add, %2
>> > > > > > >   %arrayidx4 = getelementptr inbounds
i32* %a, i32 3
>> > > > > > >   %3 = load i32* %arrayidx4, align 4,
!tbaa !1
>> > > > > > >   %add5 = add nsw i32 %add3, %3
>> > > > > > >   %arrayidx6 = getelementptr inbounds
i32* %a, i32 4
>> > > > > > >   %4 = load i32* %arrayidx6, align 4,
!tbaa !1
>> > > > > > >   %add7 = add nsw i32 %add5, %4
>> > > > > > >   %arrayidx8 = getelementptr inbounds
i32* %a, i32 5
>> > > > > > >   %5 = load i32* %arrayidx8, align 4,
!tbaa !1
>> > > > > > >   %add9 = add nsw i32 %add7, %5
>> > > > > > >   %arrayidx10 = getelementptr inbounds
i32* %a, i32 6
>> > > > > > >   %6 = load i32* %arrayidx10, align 4,
!tbaa !1
>> > > > > > >   %add11 = add nsw i32 %add9, %6
>> > > > > > >   %arrayidx12 = getelementptr inbounds
i32* %a, i32 7
>> > > > > > >   %7 = load i32* %arrayidx12, align 4,
!tbaa !1
>> > > > > > >   %add13 = add nsw i32 %add11, %7
>> > > > > > >   %arrayidx14 = getelementptr inbounds
i32* %a, i32 8
>> > > > > > >   %8 = load i32* %arrayidx14, align 4,
!tbaa !1
>> > > > > > >   %add15 = add nsw i32 %add13, %8
>> > > > > > >   %arrayidx16 = getelementptr inbounds
i32* %a, i32 9
>> > > > > > >   %9 = load i32* %arrayidx16, align 4,
!tbaa !1
>> > > > > > >   %add17 = add nsw i32 %add15, %9
>> > > > > > >   %arrayidx18 = getelementptr inbounds
i32* %a, i32 10
>> > > > > > >   %10 = load i32* %arrayidx18, align 4,
!tbaa !1
>> > > > > > >   %add19 = add nsw i32 %add17, %10
>> > > > > > >   %arrayidx20 = getelementptr inbounds
i32* %a, i32 11
>> > > > > > >   %11 = load i32* %arrayidx20, align 4,
!tbaa !1
>> > > > > > >   %add21 = add nsw i32 %add19, %11
>> > > > > > >   %arrayidx22 = getelementptr inbounds
i32* %a, i32 12
>> > > > > > >   %12 = load i32* %arrayidx22, align 4,
!tbaa !1
>> > > > > > >   %add23 = add nsw i32 %add21, %12
>> > > > > > >   %arrayidx24 = getelementptr inbounds
i32* %a, i32 13
>> > > > > > >   %13 = load i32* %arrayidx24, align 4,
!tbaa !1
>> > > > > > >   %add25 = add nsw i32 %add23, %13
>> > > > > > >   %arrayidx26 = getelementptr inbounds
i32* %a, i32 14
>> > > > > > >   %14 = load i32* %arrayidx26, align 4,
!tbaa !1
>> > > > > > >   %add27 = add nsw i32 %add25, %14
>> > > > > > >   %arrayidx28 = getelementptr inbounds
i32* %a, i32 15
>> > > > > > >   %15 = load i32* %arrayidx28, align 4,
!tbaa !1
>> > > > > > >   %add29 = add nsw i32 %add27, %15
>> > > > > > >   ret i32 %add29
>> > > > > > > }
>> > > > > > >
>> > > > > > >
>> > > > > > > Shouldn't the SLP vectorizer
vectorize above code? Am I
>> missing out something?
>> > > > > > >
>> > > > > > > How does loop unrolling affect the final
vectorization of
>> code?
>> > > > > > >
>> > > > > > >
>> > > > > > >
>> > > > > > >
>> > > > > > >
>> > > > > > >
>> > > > > > >
>> > > > > > >
>> > > > > > >
>> > > > > > >
>> > > > > > >
>> > > > > > >
>> > > > > > >
>> > > > > > >
>> > > > > > >
>> > > > > > >
>> > > > > >
>> > > > > >
>> > > > > >
>> > > > > >
>> > > > > > Hi Suyog,
>> > > > > >
>> > > > > >
>> > > > > > Thank you for taking the time to investigate
the performance of
>> the vectorizers. You are correct that the SLP-vectorizer should be able
to
>> do something about the second case (the unrolled one).  Please look
into
>> line 2861 in the SLP-vectorizer. This is where we try to analyze
reductions
>> and vectorize them. At the moment we don’t have support for a flat yet
>> large reduction that is the result of unrolled loops because the
current
>> algorithm tries to construct trees that start at the chains, and it
does
>> not support joining multiple trees.
>> > > > > >
>> > > > > >
>> > > > > >
>> http://llvm.org/docs/doxygen/html/SLPVectorizer_8cpp_source.html#l02861
>> > > > > >
>> > > > > >
>> > > > > > Thanks,
>> > > > > > Nadav
>> > > > > >
>> > > > > >
>> > > > > >
>> > > > > >
>> > > > > > > I tried to debug above IR. Since there is
no store in above
>> IR, SLP vectorization doesn't call
>> > > > > > > vectorizeStoreChains(). In
vectorizeChainsInBlock(), as there
>> is no phi node in above IR, it
>> > > > > > > also fails to vectorize the IR.
>> > > > > > >
>> > > > > > >
>> > > > > > > If it is perfectly legal to vectorize
above IR, are we
>> lacking code for it right now? Or its not
>> > > > > > >
>> > > > > > > possible to vectorize above code (as far
as i know, it is
>> perfectly possible to vectorize above code)?
>> > > > > > >
>> > > > > > > If its possible, can someone help
me/point out specifics how
>> to start for implementing vectorization for such code?
>> > > > > > >
>> > > > > > > (We do have function calls
isConsecutiveAccess() to identify
>> it. Is it a case for horizontal reduction, though the term
>> > > > > > > 'reduction' is associated with
loops/phi nodes.)
>> > > > > > >
>> > > > > > >
>> > > > > > >
>> > > > > > > This brings to me another question - if
we perform aggressive
>> loop unrolling, we might loose opportunity for
>> > > > > > >
>> > > > > > > vectorization as visible above !!
>> > > > > > >
>> > > > > > >
>> > > > > > > (I was looking into bug 20035, when i
encountered above
>> issue. Though both are not related.)
>> > > > > > >
>> > > > > > >
>> > > > > > > Your comments/suggestions are most
awaited.
>> > > > > > >
>> > > > > > >
>> > > > > > >
>> > > > > > >
>> > > > > > > --
>> > > > > > > With regards,
>> > > > > > > Suyog Sarda
>> > > > > > >
>> >
>> > > > > > >
>> > > > > > >
>> > > > > > >
>> > > > > > >
>> > > > > > >
>> > > > > > >
>> > > > > > >
>> > > > > > >
>> > > > > > >
>> > > > > > >
>> > > > > > >
>> > > > > > >
>> > > > > > >
>> >
>> > > > > > >
>> > > > > > >
>> > > > > >
>> > > > > >
>> > > > > >
>> > > > > >
>> > > > >
>> > > > >
>> > > > >
>> > > > >
>> > > > > --
>> > > > > With regards,
>> > > > > Suyog Sarda
>> > > > >
>> >
>> > > > >
>> > > > >
>> >
>> > > > >
>> > > > >
>> > > >
>> > > >
>> > > >
>> > > >
>> > >
>> > >
>> > >
>> > >
>> > > --
>> > > With regards,
>> > > Suyog Sarda
>> > >
>> >
>> > >
>> > >
>> >
>> > >
>> > >
>> > >
>> >
>> >
>> >
>> >
>> > --
>> > With regards,
>> > Suyog Sarda
>> >
>> >
>> >
>> >
>> >
>> >
>>
>
>

-- 
With regards,
Suyog Sarda
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Arnold Schwaighofer

2014-Nov-11 18:47 UTC

head link

[LLVMdev] [Vectorization] Mis match in code generated

> On Nov 11, 2014, at 10:28 AM, suyog sarda <sardask01 at gmail.com>
wrote:
> 
> Hi Arnold, James
> 
> Thanks for getting back on this. Arnold i will look into patches provided
by you
> and get back on it. Thanks for it.
> 
Note, that they were just quickly put together to support building a a
horizontal tree for your case. They definitely need testing and ironing out
bugs.
> Adding few more observations :
> 
> The expression tree is like
> 
> sum = (a[0] + a[2]) + (a[1] + a[3]); --> which is vectorizable with
current code.
> 
> If the array a[] if of type float/double then there is no
disturbance/canonicalization
> (precision issues??) in formed tree and we get a vectorized code.
> 
You can’t reassociate floating point without enabling fast-math.

We get vectorized code but it is not ideal for float. We should be doing <4 x
float> operations.
> However, if the array a[] is of type int, then re-associate pass (runs in
O1)
> re-organizes this into
>  
> sum = (((a[0] + a[2]) + a[1]) + a[3]).
> 
Right, the current code trys to build a vectorization tree at an add with the
add’s operands as the root, which will not work well for a reduction like (+ ( +
(+ a[0] a[1]) a[2]) a[3]),

Enabling recognizing horizontal reductions should recover this and improve
performance if your vector len > 2 once we have solved the sequential load
issue.

> This results in loss of vectorization opportunity as we do not vectorize
this type
> of tree in current code stated earlier in the thread.
> 
> Also, we do not build vectorization tree on return in current code
(PR20035),
> which does not vectorizes code like this :
> 
> return a[0] + a[1] + a[2] + a[3];
> 
> I will try to work on vectorization on return statement. Inputs are always
welcomed.
> 
I thought we had added ReturnInst and CallInst operands as starting points of
vectorization trees, … it seems not.


Thanks,
Arnold
> Regards, 
> Suyog
> 
> On Mon, Nov 10, 2014 at 9:13 PM, James Molloy <james at
jamesmolloy.co.uk <mailto:james at jamesmolloy.co.uk>> wrote:
> Hi Suyog,
> 
> Thanks for looking at this. This has recently got itself onto my TODO list
too.
> 
> > I am not sure how much all this will improve the code quality for
horizontal reduction
> > (donno how frequently such pattern of horizontal reduction from same
array occurs in real world/SPECS).
> 
> Actually the main loop of 470.lbm can be SLP vectorized like this. We have
three parts to it: A fully unrolled reduction, a scatter/gather part (not really
vectorizable) and a contiguous-load-scatter-store part which should be
vectorized even when scatter stores are not available in HW.
> 
> 
> Cheers,
> 
> James
> 
> On 10 November 2014 14:30, Arnold Schwaighofer <aschwaighofer at
apple.com <mailto:aschwaighofer at apple.com>> wrote:
> Hi Suyog,
> 
> the horizontal reduction code needs work. It was written long ago and was
never enabled so it has bit rotted somewhat and has lurking bugs.
> For example, it could not handle reduction value nodes that were not binary
operations.
> 
> It could vectorize
> 
> (+ (* x y) (*z a) (*b c) (*d e))
> 
> but not
> 
> 
> (+ (load a) (load b) (load c) (load d))
> 
> 
> With the attached patches:
> 0001-Test-hor-redux.patch
> 0002-Print-out-tree.patch
> 
> We would attempt to vectorize the tree stemming from your example:
> 
> 
> > float a[4], sum;
> > void foo() {
> >   sum = a[0]+a[1]+a[2]+a[3];
> > }
> 
> but because we happen to end up with the vector tuple (a[1],
a[0],a[2],a[3)) in need of gathering the existing code fails. Note, that I used
fast-math because the horizontal reduction code assumes it can reassociate
freely.
> 
> > clang -O3 test_hor_redux.c -emit-llvm -S -o - -mllvm
-slp-vectorize-hor-store  -debug-only=SLP -ffast-math -mllvm -debug-only=SLP
> 
> ...
> 
>   Reduced val:   %1 = load float* getelementptr inbounds ([4 x float]* @a,
i64 0, i64 1), align 4, !tbaa !1
>   Reduced val:   %0 = load float* getelementptr inbounds ([4 x float]* @a,
i64 0, i64 0), align 16, !tbaa !1
>   Reduced val:   %2 = load float* getelementptr inbounds ([4 x float]* @a,
i64 0, i64 2), align 8, !tbaa !1
>   Reduced val:   %3 = load float* getelementptr inbounds ([4 x float]* @a,
i64 0, i64 3), align 4, !tbaa !1
>   Reduction ops:   %add = fadd fast float %1, %0
>   Reduction ops:   %add1 = fadd fast float %add, %2
>   Reduction ops:   %add2 = fadd fast float %add1, %3
> Assertion failed: (VectorizedValue && "Need to have a
vectorized tree node"), function emitReduction, file
../lib/Transforms/Vectorize/SLPVectorizer.cpp, line 3518.
> 
> The reduction looks like
> 
> (((a[1] + a[0]) + a[2]) + a[3])
> 
> So we build a tree entry  (load a[1], load a[0], load a[2], load a[3]) and
end up with a vectorized tree entry of one who needs gathering.
> 
> The code does not handle this case correctly (in normal slp mode there is
no point in "vectorizing" a single entry tree that needs gathering).
> The patch 0003-We-don-t-correctly-vectorize-single-entry-gather-nod.patch
fixes this by disabling vectorization in such a case but then we don't
vectorize.
> As you can see this needs more work.
> 
> * We could reassociate reductions like the one above.
> 
> (((a[1] + a[0]) + a[2]) + a[3])
> 
> =>
> 
> (((a[0] + a[1]) + a[2]) + a[3])
> 
> Then the reduction tree builder code would not have to be clever. That will
only work if your initial reduction values are loads. If the loads are hidden
behind a deeper tree that won't help. In such a case the next solution would
not be so bad though.
> 
> * We could teach the tree code to do a vector load + permute operation if
applicable. This will no generate the best code though. But for deeper trees the
overhead of the permute probably does not matter much.
> 
> 
> Best,
> Arnold
> 
> On 11/09/14, suyog sarda   wrote:
> > Hi Arnold, Nadav, Hal,
> > all,
> >
> >
> > Restarting this thread with few more observations on horizontal
reduction store
> > (after using flags - slp-vectorize-hor-store and -slp-vectorize-hor,
thanks Arnold for pointing out earlier).
> >
> >
> > The SLP vectorizer does vectorize straight line code :
> >
> >
> > (this code may result as part of loop unrolling as stated earlier in
the thread.
> > Though for loop vectorization , trip count should be atleast 16,
taking smaller
> > code here to put some findings.)
> >
> >
> > float a[4], sum;
> >
> > void foo() {
> >
> >  int i;
> >
> >  for(i=0;i<4;i++);
> >
> >    sum += a[i];
> > }
> >
> > after loop unrolling -
> >
> > float a[4], sum;
> > void foo() {
> >   sum = a[0]+a[1]+a[2]+a[3];
> > }
> >
> >
> > This code gets vectorized depending on how we organize the code, and
subsequently
> >
> > how the expression tree is formed.
> >
> >
> > case 1:
> >
> > float a[4], sum;
> > void foo() {
> >   sum = a[0]+a[1]+a[2]+a[3];
> > }
> >
> >
> > The expression tree for this will be
> >
> >
> >     a[0]    a[1]
> >
> >        \       /
> >         \     /
> >
> >            +      a[2]
> >
> >             \     /
> >              \   /
> >
> >                +       a[3]
> >
> >                  \      /
> >                   \    /
> >                     +
> >                      |
> >                      |
> >                      ↓
> >
> >                      sum
> >
> >
> > This doesn't vectorize, because in function tryToVectorizeList(),
we check if the
> >
> > scalar instruction are of the same type. In above case, it will be
fadd and load,
> >
> > and hence no vectorization takes place.
> >
> >
> >
> > case 2:
> >
> > float a[4], sum;
> > void foo() {
> >   sum = (a[0]+a[1])+(a[2]+a[3]);
> > }
> >
> >
> > The expression tree for this will be (notice brackets above):
> >
> >
> > a[0]    a[1]      a[2]    a[3]
> >
> >    \       /            \        /
> >     \     /              \      /
> >        +                   +
> >          \                /
> >           \              /
> >            \            /
> >                  +
> >                    |
> >                   |
> >                   ↓
> >                  sum
> >
> >
> > In this case, in function tryToVectorizeList(), both the scalar
instructions are
> >
> > same i.e. fadd. Hence we proceed for vectorization ahead.
> >
> > But this still doesn't vectorizes the code. Ahead, while trying to
schedule bundle of code,
> >
> > it checks whether the loads are for consecutive memory access across
two subtrees from
> > same base pointer.
> >
> >
> > For above code, it checks if (a[0],a[2]) and (a[1],a[3]) are
consecutive memory
> > access (which, obviously, they are not). This cancels scheduling of
bundle of loads,
> > and hence calculated cost for non-consecutive loads comes greater
increasing overall
> >
> > cost of vectorization (and hence no vectorization).
> >
> >
> > Seems this check for consecutive memory access was written keeping in
mind following sort of code :
> >
> > sum = (a[0] + b[0]) + (a[1] + b[1]);
> >
> >
> >
> > Finally,
> >
> > case 3:
> >
> > float a[4], sum;
> > void foo() {
> >   sum = (a[0]+a[2])+(a[1]+a[3]);
> > }
> >
> >
> > The expression tree for this will be (notice brackets above):
> >
> >
> > a[0]    a[2]      a[1]    a[3]
> >
> >    \       /            \        /
> >     \     /              \      /
> >        +                   +
> >          \                /
> >           \              /
> >            \            /
> >                  +
> >                    |
> >                   |
> >                   ↓
> >                  sum
> >
> >
> >
> > This code gets vectorized, as tryToVectorizeList() gets both scalar
operation as fadd,
> >
> > as well as there is a consecutive memory access across subtress rooted
at both fadd.
> >
> >
> > case 1 IR after SLP vectorization :
> >
> > define void @foo() #0 {
> > entry:
> >   %0 = load float* getelementptr inbounds ([8 x float]* @a, i64 0, i64
0), align 16, !tbaa !1
> >   %1 = load float* getelementptr inbounds ([8 x float]* @a, i64 0, i64
1), align 4, !tbaa !1
> >   %add = fadd float %0, %1
> >   %2 = load float* getelementptr inbounds ([8 x float]* @a, i64 0, i64
2), align 8, !tbaa !1
> >   %add1 = fadd float %add, %2
> >   %3 = load float* getelementptr inbounds ([8 x float]* @a, i64 0, i64
3), align 4, !tbaa !1
> >   %add2 = fadd float %add1, %3
> >   store float %add2, float* @sum, align 4, !tbaa !1
> >   ret void
> > }
> >
> >
> > case 2 IR after SLP vectorization :
> >
> > define void @foo() #0 {
> > entry:
> >   %0 = load float* getelementptr inbounds ([8 x float]* @a, i64 0, i64
0), align 16, !tbaa !1
> >   %1 = load float* getelementptr inbounds ([8 x float]* @a, i64 0, i64
1), align 4, !tbaa !1
> >   %add = fadd float %0, %1
> >   %2 = load float* getelementptr inbounds ([8 x float]* @a, i64 0, i64
2), align 8, !tbaa !1
> >   %3 = load float* getelementptr inbounds ([8 x float]* @a, i64 0, i64
3), align 4, !tbaa !1
> >   %add1 = fadd float %2, %3
> >   %add2 = fadd float %add, %add1
> >   store float %add2, float* @sum, align 4, !tbaa !1
> >   ret void
> > }
> >
> >
> > case 3 IR after SLP vectorization :
> >
> >
> > define void @foo() #0 {
> > entry:
> >   %0 = load <2 x float>* bitcast ([4 x float]* @a to <2 x
float>*), align 16, !tbaa !1
> >   %1 = load <2 x float>* bitcast (float* getelementptr inbounds
([4 x float]* @a, i64 0, i64 2) to <2 x float>*), align 8, !tbaa !1
> >   %2 = fadd <2 x float> %0, %1
> >   %3 = extractelement <2 x float> %2, i32 0
> >   %4 = extractelement <2 x float> %2, i32 1
> >   %add2 = fadd float %3, %4
> >   store float %add2, float* @sum, align 4, !tbaa !1
> >   ret void
> > }
> >
> >
> >
> > Few cases of improvements, as visible from above (noting down roughly,
didn't give detail thought on it yet):
> >
> > 1. The IR expression tree can be re-organized to cater above need
(some kind of balancing like AVL tree).
> >
> >     Alternatively, parse the expression tree without changing it and 
look upward tree if we encounter a
> >
> >     load instruction.
> >
> > 2. Seems, there is a case for improvement in checking if memory access
are consecutive.
> >     This needs to take into consideration all the loads of all the
subtree .
> >      If all the loads are from same base pointer, then are the memory
access in same subtree as
> >      well as across the subtree consecutive. (i will try to write some
code on this, any suggestions are welcomed)
> >
> >
> >
> > I am not sure how much all this will improve the code quality for
horizontal reduction
> > (donno how frequently such pattern of horizontal reduction from same
array occurs in real world/SPECS).
> >
> > Perhaps the best case i can think of is when loops are unrolled as
noted earlier in the thread.
> >
> >
> > Adding few more people to pitch in !!
> >
> >
> > Comments/Suggestions are most welcomed.
> >
> >
> > Regards,
> >
> > Suyog 
> >
> >    
> > 
> >
> >
> >
> >
> >
> >
> >
> >
> >
> > On Sat, Sep 20, 2014 at 12:05 AM, suyog sarda <sardask01 at
gmail.com <mailto:sardask01 at gmail.com> <sardask01 at gmail.com
<mailto:sardask01 at gmail.com>>> wrote:
> >
> > > Hi Arnold,
> > >
> > >
> > > Thanks for your reply.
> > >
> > >
> > > I tried test case as suggested by you.
> > >
> > > void foo(int *a, int *sum) {
> > > *sum =
a[0]+a[1]+a[2]+a[3]+a[4]+a[5]+a[6]+a[7]+a[8]+a[9]+a[10]+a[11]+a[12]+a[13]+a[14]+a[15];
> > > }
> > >
> > >
> > > so that it has a 'store' in its IR.
> > >
> > >
> > > IR before vectorization :
> > >
> > > target datalayout =
"e-m:e-p:32:32-f64:32:64-f80:32-n8:16:32-S128"
> > > target triple = "x86_64-pc-linux-gnu"
> > >
> > > ; Function Attrs: nounwind
> > > define void @foo(i32* nocapture readonly %a, i32* nocapture %sum)
#0 {
> > > entry:
> > >   %0 = load i32* %a, align 4, !tbaa !1
> > >   %arrayidx1 = getelementptr inbounds i32* %a, i32 1
> > >   %1 = load i32* %arrayidx1, align 4, !tbaa !1
> > >   %add = add nsw i32 %1, %0
> > >   %arrayidx2 = getelementptr inbounds i32* %a, i32 2
> > >   %2 = load i32* %arrayidx2, align 4, !tbaa !1
> > >   %add3 = add nsw i32 %add, %2
> > >   %arrayidx4 = getelementptr inbounds i32* %a, i32 3
> > >   %3 = load i32* %arrayidx4, align 4, !tbaa !1
> > >   %add5 = add nsw i32 %add3, %3
> > >   %arrayidx6 = getelementptr inbounds i32* %a, i32 4
> > >   %4 = load i32* %arrayidx6, align 4, !tbaa !1
> > >   %add7 = add nsw i32 %add5, %4
> > >   %arrayidx8 = getelementptr inbounds i32* %a, i32 5
> > >   %5 = load i32* %arrayidx8, align 4, !tbaa !1
> > >   %add9 = add nsw i32 %add7, %5
> > >   %arrayidx10 = getelementptr inbounds i32* %a, i32 6
> > >   %6 = load i32* %arrayidx10, align 4, !tbaa !1
> > >   %add11 = add nsw i32 %add9, %6
> > >   %arrayidx12 = getelementptr inbounds i32* %a, i32 7
> > >   %7 = load i32* %arrayidx12, align 4, !tbaa !1
> > >   %add13 = add nsw i32 %add11, %7
> > >   %arrayidx14 = getelementptr inbounds i32* %a, i32 8
> > >   %8 = load i32* %arrayidx14, align 4, !tbaa !1
> > >   %add15 = add nsw i32 %add13, %8
> > >   %arrayidx16 = getelementptr inbounds i32* %a, i32 9
> > >   %9 = load i32* %arrayidx16, align 4, !tbaa !1
> > >   %add17 = add nsw i32 %add15, %9
> > >   %arrayidx18 = getelementptr inbounds i32* %a, i32 10
> > >   %10 = load i32* %arrayidx18, align 4, !tbaa !1
> > >   %add19 = add nsw i32 %add17, %10
> > >   %arrayidx20 = getelementptr inbounds i32* %a, i32 11
> > >   %11 = load i32* %arrayidx20, align 4, !tbaa !1
> > >   %add21 = add nsw i32 %add19, %11
> > >   %arrayidx22 = getelementptr inbounds i32* %a, i32 12
> > >   %12 = load i32* %arrayidx22, align 4, !tbaa !1
> > >   %add23 = add nsw i32 %add21, %12
> > >   %arrayidx24 = getelementptr inbounds i32* %a, i32 13
> > >   %13 = load i32* %arrayidx24, align 4, !tbaa !1
> > >   %add25 = add nsw i32 %add23, %13
> > >   %arrayidx26 = getelementptr inbounds i32* %a, i32 14
> > >   %14 = load i32* %arrayidx26, align 4, !tbaa !1
> > >   %add27 = add nsw i32 %add25, %14
> > >   %arrayidx28 = getelementptr inbounds i32* %a, i32 15
> > >   %15 = load i32* %arrayidx28, align 4, !tbaa !1
> > >   %add29 = add nsw i32 %add27, %15
> > >
> > >
> > >   store i32 %add29, i32* %sum, align 4, !tbaa !1
> > >   ret void
> > > }
> > >
> > >
> > >
> > > IR after SLP vectorization with appropriate flags :
> > >
> > > $ opt -S -slp-vectorizer -slp-vectorize-hor=1
-slp-vectorize-hor-store=1 test.ll -debug
> > >
> > >
> > > (I hope i am passing the args correctly to opt)
> > >
> > > Subtarget features: SSELevel 3, 3DNowLevel 0, 64bit 1
> > > SLP: Analyzing blocks in foo.
> > > SLP: Found 1 stores to vectorize.
> > > SLP: Vectorizing a list of length = 2.
> > > ; ModuleID = 'test.ll'
> > > target datalayout =
"e-m:e-p:32:32-f64:32:64-f80:32-n8:16:32-S128"
> > > target triple = "x86_64-pc-linux-gnu"
> > >
> > > ; Function Attrs: nounwind
> > > define void @foo(i32* nocapture readonly %a, i32* nocapture %sum)
#0 {
> > > entry:
> > >   %0 = load i32* %a, align 4, !tbaa !1
> > >   %arrayidx1 = getelementptr inbounds i32* %a, i32 1
> > >   %1 = load i32* %arrayidx1, align 4, !tbaa !1
> > >   %add = add nsw i32 %1, %0
> > >   %arrayidx2 = getelementptr inbounds i32* %a, i32 2
> > >   %2 = load i32* %arrayidx2, align 4, !tbaa !1
> > >   %add3 = add nsw i32 %add, %2
> > >   %arrayidx4 = getelementptr inbounds i32* %a, i32 3
> > >   %3 = load i32* %arrayidx4, align 4, !tbaa !1
> > >   %add5 = add nsw i32 %add3, %3
> > >   %arrayidx6 = getelementptr inbounds i32* %a, i32 4
> > >   %4 = load i32* %arrayidx6, align 4, !tbaa !1
> > >   %add7 = add nsw i32 %add5, %4
> > >   %arrayidx8 = getelementptr inbounds i32* %a, i32 5
> > >   %5 = load i32* %arrayidx8, align 4, !tbaa !1
> > >   %add9 = add nsw i32 %add7, %5
> > >   %arrayidx10 = getelementptr inbounds i32* %a, i32 6
> > >   %6 = load i32* %arrayidx10, align 4, !tbaa !1
> > >   %add11 = add nsw i32 %add9, %6
> > >   %arrayidx12 = getelementptr inbounds i32* %a, i32 7
> > >   %7 = load i32* %arrayidx12, align 4, !tbaa !1
> > >   %add13 = add nsw i32 %add11, %7
> > >   %arrayidx14 = getelementptr inbounds i32* %a, i32 8
> > >   %8 = load i32* %arrayidx14, align 4, !tbaa !1
> > >   %add15 = add nsw i32 %add13, %8
> > >   %arrayidx16 = getelementptr inbounds i32* %a, i32 9
> > >   %9 = load i32* %arrayidx16, align 4, !tbaa !1
> > >   %add17 = add nsw i32 %add15, %9
> > >   %arrayidx18 = getelementptr inbounds i32* %a, i32 10
> > >   %10 = load i32* %arrayidx18, align 4, !tbaa !1
> > >   %add19 = add nsw i32 %add17, %10
> > >   %arrayidx20 = getelementptr inbounds i32* %a, i32 11
> > >   %11 = load i32* %arrayidx20, align 4, !tbaa !1
> > >   %add21 = add nsw i32 %add19, %11
> > >   %arrayidx22 = getelementptr inbounds i32* %a, i32 12
> > >   %12 = load i32* %arrayidx22, align 4, !tbaa !1
> > >   %add23 = add nsw i32 %add21, %12
> > >   %arrayidx24 = getelementptr inbounds i32* %a, i32 13
> > >   %13 = load i32* %arrayidx24, align 4, !tbaa !1
> > >   %add25 = add nsw i32 %add23, %13
> > >   %arrayidx26 = getelementptr inbounds i32* %a, i32 14
> > >   %14 = load i32* %arrayidx26, align 4, !tbaa !1
> > >   %add27 = add nsw i32 %add25, %14
> > >   %arrayidx28 = getelementptr inbounds i32* %a, i32 15
> > >   %15 = load i32* %arrayidx28, align 4, !tbaa !1
> > >   %add29 = add nsw i32 %add27, %15
> > >
> > >
> > >   store i32 %add29, i32* %sum, align 4, !tbaa !1
> > >   ret void
> > > }
> > >
> > >
> > > As observed above, SLP vectorization doesn't vectorize this
code.
> > >
> > >
> > > I tried debugging, just mentioning what i found -
> > > the code hits vectorizeChainsInBlock() ->
if(ShouldStartVectorizeHorAtStore) ->
> > > tryToVectorize() -> tryToVectorizePair() ->
tryToVectorizeList() - inside this function, it iterates in the
> > >
> > > for loop for checking if scalar instructions are of same type. It
exits for 2nd iteration in the loop as
> > >
> > > OpCode does not match , one opcode is 'add' and second is
'load'. So it exits from function
> > > 'tryToVectorizeList()', and comes back to function
'tryToVectorize()', but fails to satisfy any of the
> > >
> > > further 'if' in that function and returns back without
vectorizing any of the code.
> > >
> > >
> > > I will try to dig more into it and try to understand where the
code can be implemented.
> > >
> > >
> > > Comments/suggestions/explanations are always welcomed !! 
> > >
> > >
> > >
> > >
> > >
> > >
> > > On Fri, Sep 19, 2014 at 1:49 AM, Arnold <aschwaighofer at
apple.com <mailto:aschwaighofer at apple.com> <aschwaighofer at
apple.com <mailto:aschwaighofer at apple.com>>> wrote:
> > >
> > > > There is experimental code to handle horizontal reductions
hidden behind a flag "slp-vectorize-hor" you could try to enable that.
It won't currently work for your example though because we only start to
look for reductions at phis and stores "slp-vectorize-hor-stores".
> > > >
> > > >
> > > > You could start off by rewriting your example with a store
and see whether the tree match works after using both flags.
> > > >
> > > > F(int *sum ...){
> > > > *sum =
a[0]+a[1]+a[2]+a[3]+a[4]+a[5]+a[6]+a[7]+a[8]+a[9]+a[10]+a[11]+a[12]+a[13]+a[14]+a[15];
> > > > }
> > > >
> > > >
> > > > If it works we would only need to look for horizontal
reductions at returns.
> > > >
> > > >
> > > >
> > > >
> > > >
> > > >
> > > > Sent from my iPhone
> > > >
> > > > On Sep 18, 2014, at 12:24 PM, suyog sarda <sardask01 at
gmail.com <mailto:sardask01 at gmail.com> <sardask01 at gmail.com
<mailto:sardask01 at gmail.com>>> wrote:
> > > >
> > > >
> > > >
> > > > > Hi Nadav,
> > > > >
> > > > >
> > > > > Thanks for the quick reply !!
> > > > >
> > > > >
> > > > > Ok, so as of now we are lacking capability to handle
flat large reductions.
> > > > >
> > > > >
> > > > > I did go through function vectorizeChainsInBlock()
(line number 2862). In this function,
> > > > >
> > > > > we try to vectorize if we have phi nodes in the IR
(several if's check for phi nodes) i.e we try to
> > > > >
> > > > > construct tree that starts at chains.
> > > > >
> > > > >
> > > > > Any pointers on how to join multiple trees? I will also
try to dig more into it.
> > > > >
> > > > >
> > > > > Comments/Suggestions are most welcomed !!
> > > > >
> > > > >
> > > > > On Fri, Sep 19, 2014 at 12:23 AM, Nadav Rotem
<nrotem at apple.com <mailto:nrotem at apple.com> <nrotem at
apple.com <mailto:nrotem at apple.com>>> wrote:
> > > > >
> > > > > >
> > > > > >
> > > > > > > On Sep 18, 2014, at 11:48 AM, suyog sarda
<sardask01 at gmail.com <mailto:sardask01 at gmail.com> <sardask01
at gmail.com <mailto:sardask01 at gmail.com>>> wrote:
> > > > > > >
> > > > > > > Hi,
> > > > > > >
> > > > > > >
> > > > > > > I am trying to understand LLVM vectorization
implementation and was looking into both loop and SLP vectorization.
> > > > > > >
> > > > > > >
> > > > > > > test case 1:
> > > > > > >
> > > > > > >
> > > > > > > int foo(int *a) {
> > > > > > > int sum = 0,i;
> > > > > > > for(i=0; i<16; i++)
> > > > > > >   sum += a[i];
> > > > > > > return sum;
> > > > > > > }
> > > > > > >
> > > > > > >
> > > > > > > This code is vectorized by loop vectorizer
where we calculate scalar loop cost as 4 and vector loop cost as 2.
> > > > > > >
> > > > > > > Since vector loop cost is less and above
reduction is legal to vectorize, loop vectorizer produces vectorized code :
> > > > > > >
> > > > > > >
> > > > > > > IR without vectorization:
> > > > > > >
> > > > > > > target datalayout =
"e-m:e-p:32:32-f64:32:64-f80:32-n8:16:32-S128"
> > > > > > > target triple =
"x86_64-pc-linux-gnu"
> > > > > > >
> > > > > > > ; Function Attrs: nounwind readonly
> > > > > > > define i32 @foo(i32* nocapture readonly %a,
i32 %n) #0 {
> > > > > > > entry:
> > > > > > >   br label %for.body
> > > > > > >
> > > > > > > for.body:                                    
; preds = %for.body, %entry
> > > > > > >   %i.05 = phi i32 [ 0, %entry ], [ %inc,
%for.body ]
> > > > > > >   %sum.04 = phi i32 [ 0, %entry ], [ %add,
%for.body ]
> > > > > > >   %arrayidx = getelementptr inbounds i32* %a,
i32 %i.05
> > > > > > >   %0 = load i32* %arrayidx, align 4, !tbaa !1
> > > > > > >   %add = add nsw i32 %0, %sum.04
> > > > > > >   %inc = add nsw i32 %i.05, 1
> > > > > > >   %exitcond = icmp eq i32 %i.05, 15
> > > > > > >   br i1 %exitcond, label %for.end, label
%for.body
> > > > > > >
> > > > > > > for.end:                                     
; preds = %for.body
> > > > > > >   ret i32 %add
> > > > > > > }
> > > > > > >
> > > > > > >
> > > > > > > IR after vectorization:
> > > > > > >
> > > > > > > target datalayout =
"e-m:e-p:32:32-f64:32:64-f80:32-n8:16:32-S128"
> > > > > > > target triple =
"x86_64-pc-linux-gnu"
> > > > > > >
> > > > > > > ; Function Attrs: nounwind readonly
> > > > > > > define i32 @foo(i32* nocapture readonly %a,
i32 %n) #0 {
> > > > > > > entry:
> > > > > > >   %backedge.overflow = icmp eq i32 15, -1
> > > > > > >   %overflow.check.anchor = add i32 0, 0
> > > > > > >   br i1 %backedge.overflow, label %scalar.ph
<http://scalar.ph/>(http://scalar.ph/ <http://scalar.ph/>), label
%overflow.checked
> > > > > > >
> > > > > > > overflow.checked:                            
; preds = %entry
> > > > > > >   br i1 false, label %middle.block, label
%vector.ph <http://vector.ph/>(http://vector.ph/
<http://vector.ph/>)
> > > > > > >
> > > > > > > vector.ph
<http://vector.ph/>(http://vector.ph/ <http://vector.ph/>):         
; preds = %overflow.checked
> > > > > > >   br label %vector.body
> > > > > > >
> > > > > > > vector.body:                                 
; preds = %vector.body, %vector.ph <http://vector.ph/>(http://vector.ph/
<http://vector.ph/>)
> > > > > > >   %index = phi i32 [ 0, %vector.ph
<http://vector.ph/>(http://vector.ph/ <http://vector.ph/>) ], [
%index.next, %vector.body ]
> > > > > > >   %vec.phi = phi <4 x i32> [
zeroinitializer, %vector.ph <http://vector.ph/>(http://vector.ph/
<http://vector.ph/>) ], [ %14, %vector.body ]
> > > > > > >   %broadcast.splatinsert = insertelement
<4 x i32> undef, i32 %index, i32 0
> > > > > > >   %broadcast.splat = shufflevector <4 x
i32> %broadcast.splatinsert, <4 x i32> undef, <4 x i32>
zeroinitializer
> > > > > > >   %induction = add <4 x i32>
%broadcast.splat, <i32 0, i32 1, i32 2, i32 3>
> > > > > > >   %0 = extractelement <4 x i32>
%induction, i32 0
> > > > > > >   %1 = getelementptr inbounds i32* %a, i32 %0
> > > > > > >   %2 = insertelement <4 x i32*> undef,
i32* %1, i32 0
> > > > > > >   %3 = extractelement <4 x i32>
%induction, i32 1
> > > > > > >   %4 = getelementptr inbounds i32* %a, i32 %3
> > > > > > >   %5 = insertelement <4 x i32*> %2,
i32* %4, i32 1
> > > > > > >   %6 = extractelement <4 x i32>
%induction, i32 2
> > > > > > >   %7 = getelementptr inbounds i32* %a, i32 %6
> > > > > > >   %8 = insertelement <4 x i32*> %5,
i32* %7, i32 2
> > > > > > >   %9 = extractelement <4 x i32>
%induction, i32 3
> > > > > > >   %10 = getelementptr inbounds i32* %a, i32
%9
> > > > > > >   %11 = insertelement <4 x i32*> %8,
i32* %10, i32 3
> > > > > > >   %12 = getelementptr i32* %1, i32 0
> > > > > > >   %13 = bitcast i32* %12 to <4 x i32>*
> > > > > > >   %wide.load = load <4 x i32>* %13,
align 4, !tbaa !1
> > > > > > >   %14 = add nsw <4 x i32> %wide.load,
%vec.phi
> > > > > > >   %15 = add nsw <4 x i32> %induction,
<i32 1, i32 1, i32 1, i32 1>
> > > > > > >   %16 = icmp eq <4 x i32> %induction,
<i32 15, i32 15, i32 15, i32 15>
> > > > > > >   %index.next = add i32 %index, 4
> > > > > > >   %17 = icmp eq i32 %index.next, 16
> > > > > > >   br i1 %17, label %middle.block, label
%vector.body, !llvm.loop !5
> > > > > > >
> > > > > > > middle.block:                                
; preds = %vector.body, %overflow.checked
> > > > > > >   %resume.val = phi i32 [ 0,
%overflow.checked ], [ 16, %vector.body ]
> > > > > > >   %trunc.resume.val = phi i32 [ 0,
%overflow.checked ], [ 16, %vector.body ]
> > > > > > >   %rdx.vec.exit.phi = phi <4 x i32> [
zeroinitializer, %overflow.checked ], [ %14, %vector.body ]
> > > > > > >   %rdx.shuf = shufflevector <4 x i32>
%rdx.vec.exit.phi, <4 x i32> undef, <4 x i32> <i32 2, i32 3, i32
undef, i32 undef>
> > > > > > >   %bin.rdx = add <4 x i32>
%rdx.vec.exit.phi, %rdx.shuf
> > > > > > >   %rdx.shuf1 = shufflevector <4 x i32>
%bin.rdx, <4 x i32> undef, <4 x i32> <i32 1, i32 undef, i32
undef, i32 undef>
> > > > > > >   %bin.rdx2 = add <4 x i32> %bin.rdx,
%rdx.shuf1
> > > > > > >   %18 = extractelement <4 x i32>
%bin.rdx2, i32 0
> > > > > > >   %cmp.n = icmp eq i32 16, %resume.val
> > > > > > >   br i1 %cmp.n, label %for.end, label
%scalar.ph <http://scalar.ph/>(http://scalar.ph/
<http://scalar.ph/>)
> > > > > > >
> > > > > > > scalar.ph
<http://scalar.ph/>(http://scalar.ph/ <http://scalar.ph/>):         
; preds = %middle.block, %entry
> > > > > > >   %bc.resume.val = phi i32 [ %resume.val,
%middle.block ], [ 0, %entry ]
> > > > > > >   %bc.trunc.resume.val = phi i32 [
%trunc.resume.val, %middle.block ], [ 0, %entry ]
> > > > > > >   %bc.merge.rdx = phi i32 [ 0, %entry ], [
%18, %middle.block ]
> > > > > > >   br label %for.body
> > > > > > >
> > > > > > > for.body:                                    
; preds = %for.body, %scalar.ph <http://scalar.ph/>(http://scalar.ph/
<http://scalar.ph/>)
> > > > > > >   %i.05 = phi i32 [ %bc.trunc.resume.val,
%scalar.ph <http://scalar.ph/>(http://scalar.ph/
<http://scalar.ph/>) ], [ %inc, %for.body ]
> > > > > > >   %sum.04 = phi i32 [ %bc.merge.rdx,
%scalar.ph <http://scalar.ph/>(http://scalar.ph/
<http://scalar.ph/>) ], [ %add, %for.body ]
> > > > > > >   %arrayidx = getelementptr inbounds i32* %a,
i32 %i.05
> > > > > > >   %19 = load i32* %arrayidx, align 4, !tbaa
!1
> > > > > > >   %add = add nsw i32 %19, %sum.04
> > > > > > >   %inc = add nsw i32 %i.05, 1
> > > > > > >   %exitcond = icmp eq i32 %i.05, 15
> > > > > > >   br i1 %exitcond, label %for.end, label
%for.body, !llvm.loop !8
> > > > > > >
> > > > > > > for.end:                                     
; preds = %middle.block, %for.body
> > > > > > >   %add.lcssa = phi i32 [ %add, %for.body ], [
%18, %middle.block ]
> > > > > > >   ret i32 %add.lcssa
> > > > > > > } 
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > > Now for test case 2, where we unroll the loop
totally :
> > > > > > >
> > > > > > > int foo(int *a) {
> > > > > > > int sum = 0;
> > > > > > > sum =
a[0]+a[1]+a[2]+a[3]+a[4]+a[5]+a[6]+a[7]+a[8]+a[9]+a[10]+a[11]+a[12]+a[13]+a[14]+a[15];
> > > > > > > return sum;
> > > > > > > }
> > > > > > >
> > > > > > >
> > > > > > > This code is not vectorized by SLP
vectorization.
> > > > > > >
> > > > > > >
> > > > > > > IR before vectorization:
> > > > > > >
> > > > > > >
> > > > > > > test.ll
> > > > > > >
> > > > > > >
> > > > > > > target datalayout =
"e-m:e-p:32:32-f64:32:64-f80:32-n8:16:32-S128"
> > > > > > > target triple =
"x86_64-pc-linux-gnu"
> > > > > > >
> > > > > > > ; Function Attrs: nounwind readonly
> > > > > > > define i32 @foo(i32* nocapture readonly %a,
i32 %n) #0 {
> > > > > > > entry:
> > > > > > >   %0 = load i32* %a, align 4, !tbaa !1
> > > > > > >   %arrayidx1 = getelementptr inbounds i32*
%a, i32 1
> > > > > > >   %1 = load i32* %arrayidx1, align 4, !tbaa
!1
> > > > > > >   %add = add nsw i32 %1, %0
> > > > > > >   %arrayidx2 = getelementptr inbounds i32*
%a, i32 2
> > > > > > >   %2 = load i32* %arrayidx2, align 4, !tbaa
!1
> > > > > > >   %add3 = add nsw i32 %add, %2
> > > > > > >   %arrayidx4 = getelementptr inbounds i32*
%a, i32 3
> > > > > > >   %3 = load i32* %arrayidx4, align 4, !tbaa
!1
> > > > > > >   %add5 = add nsw i32 %add3, %3
> > > > > > >   %arrayidx6 = getelementptr inbounds i32*
%a, i32 4
> > > > > > >   %4 = load i32* %arrayidx6, align 4, !tbaa
!1
> > > > > > >   %add7 = add nsw i32 %add5, %4
> > > > > > >   %arrayidx8 = getelementptr inbounds i32*
%a, i32 5
> > > > > > >   %5 = load i32* %arrayidx8, align 4, !tbaa
!1
> > > > > > >   %add9 = add nsw i32 %add7, %5
> > > > > > >   %arrayidx10 = getelementptr inbounds i32*
%a, i32 6
> > > > > > >   %6 = load i32* %arrayidx10, align 4, !tbaa
!1
> > > > > > >   %add11 = add nsw i32 %add9, %6
> > > > > > >   %arrayidx12 = getelementptr inbounds i32*
%a, i32 7
> > > > > > >   %7 = load i32* %arrayidx12, align 4, !tbaa
!1
> > > > > > >   %add13 = add nsw i32 %add11, %7
> > > > > > >   %arrayidx14 = getelementptr inbounds i32*
%a, i32 8
> > > > > > >   %8 = load i32* %arrayidx14, align 4, !tbaa
!1
> > > > > > >   %add15 = add nsw i32 %add13, %8
> > > > > > >   %arrayidx16 = getelementptr inbounds i32*
%a, i32 9
> > > > > > >   %9 = load i32* %arrayidx16, align 4, !tbaa
!1
> > > > > > >   %add17 = add nsw i32 %add15, %9
> > > > > > >   %arrayidx18 = getelementptr inbounds i32*
%a, i32 10
> > > > > > >   %10 = load i32* %arrayidx18, align 4, !tbaa
!1
> > > > > > >   %add19 = add nsw i32 %add17, %10
> > > > > > >   %arrayidx20 = getelementptr inbounds i32*
%a, i32 11
> > > > > > >   %11 = load i32* %arrayidx20, align 4, !tbaa
!1
> > > > > > >   %add21 = add nsw i32 %add19, %11
> > > > > > >   %arrayidx22 = getelementptr inbounds i32*
%a, i32 12
> > > > > > >   %12 = load i32* %arrayidx22, align 4, !tbaa
!1
> > > > > > >   %add23 = add nsw i32 %add21, %12
> > > > > > >   %arrayidx24 = getelementptr inbounds i32*
%a, i32 13
> > > > > > >   %13 = load i32* %arrayidx24, align 4, !tbaa
!1
> > > > > > >   %add25 = add nsw i32 %add23, %13
> > > > > > >   %arrayidx26 = getelementptr inbounds i32*
%a, i32 14
> > > > > > >   %14 = load i32* %arrayidx26, align 4, !tbaa
!1
> > > > > > >   %add27 = add nsw i32 %add25, %14
> > > > > > >   %arrayidx28 = getelementptr inbounds i32*
%a, i32 15
> > > > > > >   %15 = load i32* %arrayidx28, align 4, !tbaa
!1
> > > > > > >   %add29 = add nsw i32 %add27, %15
> > > > > > >   ret i32 %add29
> > > > > > > }
> > > > > > >
> > > > > > > $ opt -S -slp-vectorizer -slp-vectorize-hor
test.ll -debug -o test2.ll
> > > > > > >
> > > > > > > Features:+64bit,+sse2
> > > > > > > CPU:generic
> > > > > > >
> > > > > > > Subtarget features: SSELevel 3, 3DNowLevel 0,
64bit 1
> > > > > > > SLP: Analyzing blocks in foo.
> > > > > > >
> > > > > > >
> > > > > > > test2.ll (IR after SLP vectorization) :
> > > > > > >
> > > > > > > target datalayout =
"e-m:e-p:32:32-f64:32:64-f80:32-n8:16:32-S128"
> > > > > > > target triple =
"x86_64-pc-linux-gnu"
> > > > > > >
> > > > > > > ; Function Attrs: nounwind readonly
> > > > > > > define i32 @foo(i32* nocapture readonly %a,
i32 %n) #0 {
> > > > > > > entry:
> > > > > > >   %0 = load i32* %a, align 4, !tbaa !1
> > > > > > >   %arrayidx1 = getelementptr inbounds i32*
%a, i32 1
> > > > > > >   %1 = load i32* %arrayidx1, align 4, !tbaa
!1
> > > > > > >   %add = add nsw i32 %1, %0
> > > > > > >   %arrayidx2 = getelementptr inbounds i32*
%a, i32 2
> > > > > > >   %2 = load i32* %arrayidx2, align 4, !tbaa
!1
> > > > > > >   %add3 = add nsw i32 %add, %2
> > > > > > >   %arrayidx4 = getelementptr inbounds i32*
%a, i32 3
> > > > > > >   %3 = load i32* %arrayidx4, align 4, !tbaa
!1
> > > > > > >   %add5 = add nsw i32 %add3, %3
> > > > > > >   %arrayidx6 = getelementptr inbounds i32*
%a, i32 4
> > > > > > >   %4 = load i32* %arrayidx6, align 4, !tbaa
!1
> > > > > > >   %add7 = add nsw i32 %add5, %4
> > > > > > >   %arrayidx8 = getelementptr inbounds i32*
%a, i32 5
> > > > > > >   %5 = load i32* %arrayidx8, align 4, !tbaa
!1
> > > > > > >   %add9 = add nsw i32 %add7, %5
> > > > > > >   %arrayidx10 = getelementptr inbounds i32*
%a, i32 6
> > > > > > >   %6 = load i32* %arrayidx10, align 4, !tbaa
!1
> > > > > > >   %add11 = add nsw i32 %add9, %6
> > > > > > >   %arrayidx12 = getelementptr inbounds i32*
%a, i32 7
> > > > > > >   %7 = load i32* %arrayidx12, align 4, !tbaa
!1
> > > > > > >   %add13 = add nsw i32 %add11, %7
> > > > > > >   %arrayidx14 = getelementptr inbounds i32*
%a, i32 8
> > > > > > >   %8 = load i32* %arrayidx14, align 4, !tbaa
!1
> > > > > > >   %add15 = add nsw i32 %add13, %8
> > > > > > >   %arrayidx16 = getelementptr inbounds i32*
%a, i32 9
> > > > > > >   %9 = load i32* %arrayidx16, align 4, !tbaa
!1
> > > > > > >   %add17 = add nsw i32 %add15, %9
> > > > > > >   %arrayidx18 = getelementptr inbounds i32*
%a, i32 10
> > > > > > >   %10 = load i32* %arrayidx18, align 4, !tbaa
!1
> > > > > > >   %add19 = add nsw i32 %add17, %10
> > > > > > >   %arrayidx20 = getelementptr inbounds i32*
%a, i32 11
> > > > > > >   %11 = load i32* %arrayidx20, align 4, !tbaa
!1
> > > > > > >   %add21 = add nsw i32 %add19, %11
> > > > > > >   %arrayidx22 = getelementptr inbounds i32*
%a, i32 12
> > > > > > >   %12 = load i32* %arrayidx22, align 4, !tbaa
!1
> > > > > > >   %add23 = add nsw i32 %add21, %12
> > > > > > >   %arrayidx24 = getelementptr inbounds i32*
%a, i32 13
> > > > > > >   %13 = load i32* %arrayidx24, align 4, !tbaa
!1
> > > > > > >   %add25 = add nsw i32 %add23, %13
> > > > > > >   %arrayidx26 = getelementptr inbounds i32*
%a, i32 14
> > > > > > >   %14 = load i32* %arrayidx26, align 4, !tbaa
!1
> > > > > > >   %add27 = add nsw i32 %add25, %14
> > > > > > >   %arrayidx28 = getelementptr inbounds i32*
%a, i32 15
> > > > > > >   %15 = load i32* %arrayidx28, align 4, !tbaa
!1
> > > > > > >   %add29 = add nsw i32 %add27, %15
> > > > > > >   ret i32 %add29
> > > > > > > }
> > > > > > >
> > > > > > >
> > > > > > > Shouldn't the SLP vectorizer vectorize
above code? Am I missing out something?
> > > > > > >
> > > > > > > How does loop unrolling affect the final
vectorization of code?
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > >
> > > > > >
> > > > > >
> > > > > >
> > > > > > Hi Suyog, 
> > > > > >
> > > > > >
> > > > > > Thank you for taking the time to investigate the
performance of the vectorizers. You are correct that the SLP-vectorizer should
be able to do something about the second case (the unrolled one).  Please look
into line 2861 in the SLP-vectorizer. This is where we try to analyze reductions
and vectorize them. At the moment we don’t have support for a flat yet large
reduction that is the result of unrolled loops because the current algorithm
tries to construct trees that start at the chains, and it does not support
joining multiple trees.
> > > > > >
> > > > > >
> > > > > >
http://llvm.org/docs/doxygen/html/SLPVectorizer_8cpp_source.html#l02861
<http://llvm.org/docs/doxygen/html/SLPVectorizer_8cpp_source.html#l02861>
> > > > > >
> > > > > >
> > > > > > Thanks,
> > > > > > Nadav
> > > > > >
> > > > > >
> > > > > >
> > > > > >
> > > > > > > I tried to debug above IR. Since there is no
store in above IR, SLP vectorization doesn't call
> > > > > > > vectorizeStoreChains(). In
vectorizeChainsInBlock(), as there is no phi node in above IR, it
> > > > > > > also fails to vectorize the IR.
> > > > > > >
> > > > > > >
> > > > > > > If it is perfectly legal to vectorize above
IR, are we lacking code for it right now? Or its not
> > > > > > >
> > > > > > > possible to vectorize above code (as far as i
know, it is perfectly possible to vectorize above code)?
> > > > > > >
> > > > > > > If its possible, can someone help me/point
out specifics how to start for implementing vectorization for such code?
> > > > > > >
> > > > > > > (We do have function calls
isConsecutiveAccess() to identify it. Is it a case for horizontal reduction,
though the term
> > > > > > > 'reduction' is associated with
loops/phi nodes.)
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > > This brings to me another question - if we
perform aggressive loop unrolling, we might loose opportunity for
> > > > > > >
> > > > > > > vectorization as visible above !!
> > > > > > >
> > > > > > >
> > > > > > > (I was looking into bug 20035, when i
encountered above issue. Though both are not related.)
> > > > > > >
> > > > > > >
> > > > > > > Your comments/suggestions are most awaited.
> > > > > > >
> > > > > > >
> > > > > > >  
> > > > > > >
> > > > > > > --
> > > > > > > With regards,
> > > > > > > Suyog Sarda
> > > > > > >
> >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> >
> > > > > > >
> > > > > > >
> > > > > >
> > > > > >
> > > > > >
> > > > > >
> > > > >
> > > > >
> > > > >
> > > > >
> > > > > --
> > > > > With regards,
> > > > > Suyog Sarda
> > > > >
> >
> > > > >
> > > > >
> >
> > > > >
> > > > >
> > > >
> > > >
> > > >
> > > >
> > >
> > >
> > >
> > >
> > > --
> > > With regards,
> > > Suyog Sarda
> > >
> >
> > >
> > >
> >
> > >
> > >
> > >
> >
> >
> >
> >
> > --
> > With regards,
> > Suyog Sarda
> >
> >
> >
> >
> >
> >
> 
> 
> 
> 
> -- 
> With regards,
> Suyog Sarda
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llvm dev - Nov 2014 - [LLVMdev] [Vectorization] Mis match in code generated

[LLVMdev] [Vectorization] Mis match in code generated

[LLVMdev] [Vectorization] Mis match in code generated

[LLVMdev] [Vectorization] Mis match in code generated