Before this patch we relied on the order of phi nodes when we looked for phi
nodes of the same type. This could prevent vectorization of cases where there
was a phi node of a second type in between phi nodes of some type.
This is important for vectorization of an internal graphics kernel. On the test
suite + external on x86_64 (and on a run on armv7s) it showed no impact on
either performance or compile time.
radar://15024459
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@192537 91177308-0d34-0410-b5e6-96231b3b80d8
1) If the width of vectorization list candidate is bigger than vector reg width, we will break it down to fit the vector reg.
2) We do not vectorize the width which is not power of two.
The performance result shows it will help some spec benchmarks. mesa improved 6.97% and ammp improved 1.54%.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@189830 91177308-0d34-0410-b5e6-96231b3b80d8
using GEPs. Previously, it used a number of different heuristics for
analyzing the GEPs. Several of these were conservatively correct, but
failed to fall back to SCEV even when SCEV might have given a reasonable
answer. One was simply incorrect in how it was formulated.
There was good code already to recursively evaluate the constant offsets
in GEPs, look through pointer casts, etc. I gathered this into a form
code like the SLP code can use in a previous commit, which allows all of
this code to become quite simple.
There is some performance (compile time) concern here at first glance as
we're directly attempting to walk both pointers constant GEP chains.
However, a couple of thoughts:
1) The very common cases where there is a dynamic pointer, and a second
pointer at a constant offset (usually a stride) from it, this code
will actually not do any unnecessary work.
2) InstCombine and other passes work very hard to collapse constant
GEPs, so it will be rare that we iterate here for a long time.
That said, if there remain performance problems here, there are some
obvious things that can improve the situation immensely. Doing
a vectorizer-pass-wide memoizer for each individual layer of pointer
values, their base values, and the constant offset is likely to be able
to completely remove redundant work and strictly limit the scaling of
the work to scrape these GEPs. Since this optimization was not done on
the prior version (which would still benefit from it), I've not done it
here. But if folks have benchmarks that slow down it should be straight
forward for them to add.
I've added a test case, but I'm not really confident of the amount of
testing done for different access patterns, strides, and pointer
manipulation.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@189007 91177308-0d34-0410-b5e6-96231b3b80d8
To support this we have to insert 'extractelement' instructions to pick the right lane.
We had this functionality before but I removed it when we moved to the multi-block design because it was too complicated.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@185230 91177308-0d34-0410-b5e6-96231b3b80d8
