back into a vector
Previously the cost of the existing ExtractElement/ExtractValue
instructions was considered as a dead cost only if it was detected that
they have only one use. But these instructions may be considered
dead also if users of the instructions are also going to be vectorized,
like:
```
%x0 = extractelement <2 x float> %x, i32 0
%x1 = extractelement <2 x float> %x, i32 1
%x0x0 = fmul float %x0, %x0
%x1x1 = fmul float %x1, %x1
%add = fadd float %x0x0, %x1x1
```
This can be transformed to
```
%1 = fmul <2 x float> %x, %x
%2 = extractelement <2 x float> %1, i32 0
%3 = extractelement <2 x float> %1, i32 1
%add = fadd float %2, %3
```
because though `%x0` and `%x1` have 2 users each other, these users are
part of the vectorized tree and we can consider these `extractelement`
instructions as dead.
Differential Revision: https://reviews.llvm.org/D29900
llvm-svn: 295056
reductions.
Currently, LLVM supports vectorization of horizontal reduction
instructions with initial value set to 0. Patch supports vectorization
of reduction with non-zero initial values. Also, it supports a
vectorization of instructions with some extra arguments, like:
```
float f(float x[], int a, int b) {
float p = a % b;
p += x[0] + 3;
for (int i = 1; i < 32; i++)
p += x[i];
return p;
}
```
Patch allows vectorization of this kind of horizontal reductions.
Differential Revision: https://reviews.llvm.org/D29727
llvm-svn: 294934
This breaks when one of the extra values is also a scalar that
participates in the same vectorization tree which we'll end up
reducing.
llvm-svn: 294245
This generalizes memory access sorting to use differences between SCEVs,
instead of relying on constant offsets. That allows us to properly do
SLP vectorization of non-sequentially ordered loads within loops bodies.
Differential Revision: https://reviews.llvm.org/D29425
llvm-svn: 294027
Currently LLVM supports vectorization of horizontal reduction
instructions with initial value set to 0. Patch supports vectorization
of reduction with non-zero initial values. Also it supports a
vectorization of instructions with some extra arguments, like:
float f(float x[], int a, int b) {
float p = a % b;
p += x[0] + 3;
for (int i = 1; i < 32; i++)
p += x[i];
return p;
}
Patch allows vectorization of this kind of horizontal reductions.
Differential Revision: https://reviews.llvm.org/D28961
llvm-svn: 293994
The jumbled scalar loads will be sorted while building the tree and these accesses will be marked to generate shufflevector after the vectorized load with proper mask.
Reviewers: hfinkel, mssimpso, mkuper
Differential Revision: https://reviews.llvm.org/D26905
Change-Id: I9c0c8e6f91a00076a7ee1465440a3f6ae092f7ad
llvm-svn: 293386
instructions.
If number of instructions in horizontal reduction list is not power of 2
then only PowerOf2Floor(NumberOfInstructions) last elements are actually
vectorized, other instructions remain scalar. Patch tries to vectorize
the remaining elements either.
Differential Revision: https://reviews.llvm.org/D28959
llvm-svn: 293042
The removed assert seems bogus - it's perfectly legal for the roots of the
vectorized subtrees to be equal even if the original scalar values aren't,
if the original scalars happen to be equivalent.
This fixes PR31599.
Differential Revision: https://reviews.llvm.org/D28539
llvm-svn: 291692
This adds a combine that canonicalizes a chain of inserts which broadcasts
a value into a single insert + a splat shufflevector.
This fixes PR31286.
Differential Revision: https://reviews.llvm.org/D27992
llvm-svn: 290641
This patch ensures the correct minimum bit width during type-shrinking.
Previously when type-shrinking, we always sign-extended values back to their
original width. However, if we are going to sign-extend, and the sign bit is
unknown, we have to increase the minimum bit width by one bit so the
sign-extend will fill the upper bits correctly. If the sign bit is known to be
zero, we can perform a zero-extend instead. This should fix PR31243.
Reference: https://llvm.org/bugs/show_bug.cgi?id=31243
Differential Revision: https://reviews.llvm.org/D27466
llvm-svn: 289470
Summary:
This change adds some verification in the IR verifier around struct path
TBAA metadata.
Other than some basic sanity checks (e.g. we get constant integers where
we expect constant integers), this checks:
- That by the time an struct access tuple `(base-type, offset)` is
"reduced" to a scalar base type, the offset is `0`. For instance, in
C++ you can't start from, say `("struct-a", 16)`, and end up with
`("int", 4)` -- by the time the base type is `"int"`, the offset
better be zero. In particular, a variant of this invariant is needed
for `llvm::getMostGenericTBAA` to be correct.
- That there are no cycles in a struct path.
- That struct type nodes have their offsets listed in an ascending
order.
- That when generating the struct access path, you eventually reach the
access type listed in the tbaa tag node.
Reviewers: dexonsmith, chandlerc, reames, mehdi_amini, manmanren
Subscribers: mcrosier, llvm-commits
Differential Revision: https://reviews.llvm.org/D26438
llvm-svn: 289402
When trying to vectorize trees that start at insertelement instructions
function tryToVectorizeList() uses vectorization factor calculated as
MinVecRegSize/ScalarTypeSize. But sometimes it does not work as tree
cost for this fixed vectorization factor is too high.
Patch tries to improve the situation. It tries different vectorization
factors from max(PowerOf2Floor(NumberOfVectorizedValues),
MinVecRegSize/ScalarTypeSize) to MinVecRegSize/ScalarTypeSize and tries
to choose the best one.
Differential Revision: https://reviews.llvm.org/D27215
llvm-svn: 289043
This reverts commit r288497, as it broke the AArch64 build of Compiler-RT's
builtins (twice: once in r288412 and once in r288497). We should investigate
this offline.
llvm-svn: 288508
When trying to vectorize trees that start at insertelement instructions
function tryToVectorizeList() uses vectorization factor calculated as
MinVecRegSize/ScalarTypeSize. But sometimes it does not work as tree
cost for this fixed vectorization factor is too high.
Patch tries to improve the situation. It tries different vectorization
factors from max(PowerOf2Floor(NumberOfVectorizedValues),
MinVecRegSize/ScalarTypeSize) to MinVecRegSize/ScalarTypeSize and tries
to choose the best one.
Differential Revision: https://reviews.llvm.org/D27215
llvm-svn: 288497
When trying to vectorize trees that start at insertelement instructions
function tryToVectorizeList() uses vectorization factor calculated as
MinVecRegSize/ScalarTypeSize. But sometimes it does not work as tree
cost for this fixed vectorization factor is too high.
Patch tries to improve the situation. It tries different vectorization
factors from max(PowerOf2Floor(NumberOfVectorizedValues),
MinVecRegSize/ScalarTypeSize) to MinVecRegSize/ScalarTypeSize and tries
to choose the best one.
Differential Revision: https://reviews.llvm.org/D27215
llvm-svn: 288412
Currently when cost of scalar operations is evaluated the vector type is
used for scalar operations. Patch fixes this issue and fixes evaluation
of the vector operations cost.
Several test showed that vector cost model is too optimistic. It
allowed vectorization of 8 or less add/fadd operations, though scalar
code is faster. Actually, only for 16 or more operations vector code
provides better performance.
Differential Revision: https://reviews.llvm.org/D26277
llvm-svn: 288398
Currently SLP vectorizer tries to vectorize a binary operation and dies
immediately after unsuccessful the first unsuccessfull attempt. Patch
tries to improve the situation, trying to vectorize all binary
operations of all children nodes in the binop tree.
Differential Revision: https://reviews.llvm.org/D25517
llvm-svn: 288115
Summary:
This extends FCOPYSIGN support to 512-bit vectors.
I've also added tests to show what the 128-bit and 256-bit cases look like with broadcast loads.
Reviewers: delena, zvi, RKSimon, spatel
Subscribers: llvm-commits
Differential Revision: https://reviews.llvm.org/D26791
llvm-svn: 287298
This patch avoids scalarization of CTLZ by instead expanding to use CTPOP (ref: "Hacker's Delight") when the necessary operations are available.
This also adds the necessary cost models for X86 SSE2 targets (the main beneficiary) to ensure vectorization only happens when its useful.
Differential Revision: https://reviews.llvm.org/D25910
llvm-svn: 286233