[SLP] avoid reduction transform on patterns that the backend can load-combine (2nd...

[SLP] avoid reduction transform on patterns that the backend can load-combine (2nd try)

The 1st attempt at this modified the cost model in a bad way to avoid the vectorization,
but that caused problems for other users (the loop vectorizer) of the cost model.

I don't see an ideal solution to these 2 related, potentially large, perf regressions:
https://bugs.llvm.org/show_bug.cgi?id=42708
https://bugs.llvm.org/show_bug.cgi?id=43146

We decided that load combining was unsuitable for IR because it could obscure other
optimizations in IR. So we removed the LoadCombiner pass and deferred to the backend.
Therefore, preventing SLP from destroying load combine opportunities requires that it
recognizes patterns that could be combined later, but not do the optimization itself (
it's not a vector combine anyway, so it's probably out-of-scope for SLP).

Here, we add a cost-independent bailout with a conservative pattern match for a
multi-instruction sequence that can probably be reduced later.

In the x86 tests shown (and discussed in more detail in the bug reports), SDAG combining
will produce a single instruction on these tests like:

  movbe   rax, qword ptr [rdi]

or:

  mov     rax, qword ptr [rdi]

Not some (half) vector monstrosity as we currently do using SLP:

  vpmovzxbq       ymm0, dword ptr [rdi + 1] # ymm0 = mem[0],zero,zero,..
  vpsllvq ymm0, ymm0, ymmword ptr [rip + .LCPI0_0]
  movzx   eax, byte ptr [rdi]
  movzx   ecx, byte ptr [rdi + 5]
  shl     rcx, 40
  movzx   edx, byte ptr [rdi + 6]
  shl     rdx, 48
  or      rdx, rcx
  movzx   ecx, byte ptr [rdi + 7]
  shl     rcx, 56
  or      rcx, rdx
  or      rcx, rax
  vextracti128    xmm1, ymm0, 1
  vpor    xmm0, xmm0, xmm1
  vpshufd xmm1, xmm0, 78          # xmm1 = xmm0[2,3,0,1]
  vpor    xmm0, xmm0, xmm1
  vmovq   rax, xmm0
  or      rax, rcx
  vzeroupper
  ret

Differential Revision: https://reviews.llvm.org/D67841

git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@375025 91177308-0d34-0410-b5e6-96231b3b80d8