Based off D148215, when expanding a min/max reduction we should be creating min/max intrinsics directly instead of relying on instcombine to fold them back together.
This patch handles integer min/max cases. Hopefully we can add floating point support soon (at least for fastmath/nnan cases) - but we're missing some of the plumbing to pass the correct FMF to the intrinsic at the moment.
Differential Revision: https://reviews.llvm.org/D148221
Whilst writing a patch to add extra tail-folding RUN lines to
existing tests I noticed a few areas where they can be
cleaned up a little:
1. scalable-reductions.ll: fmin_fast does not mark fcmp as fast.
2. sve-inductions-unusual-types.ll: remove direct references to
SSA variable names.
3. sve-strict-fadd-cost.ll: don't force vector width so we see
costs for different VFs in one go. This will be important for
the follow-on patch.
4. sve-vector-reverse.ll,vector-reverse-mask4.ll: add noalias
keyword to simplify IR.
4. sve-widen-gep.ll,sve-widen-phi.ll: regenerate using script.
These changes will make the subsequent patch adding RUN lines much
easier to review!
Differential Revision: https://reviews.llvm.org/D132219
This patch is in preparation for enabling vectorisation with tail-folding
by default for SVE targets. Once we do that many existing tests will
break that depend upon having normal unpredicated vector loops. For
all such tests I have added the flag:
-prefer-predicate-over-epilogue=scalar-epilogue
Differential Revision: https://reviews.llvm.org/D129137
When compiling the attached new test in scalable-reductions-tf.ll we
were hitting this assertion in fixReduction:
Assertion `isa<PHINode>(U) && "Reduction exit must feed Phi's or select"
The loop contains a reduction and an intermediate store of the reduction
value. When vectorising with tail-folding the contains of 'U' in the
assertion above happened to be a scatter_store. It turns out that we
were still creating a widen recipe for the invariant store, despite
knowing that we can actually sink it. The simplest fix is to change
buildVPlanWithVPRecipes so that we look for invariant stores before
attempting to widen it.
Differential Revision: https://reviews.llvm.org/D126295
Adds ability to vectorize loops containing a store to a loop-invariant
address as part of a reduction that isn't converted to SSA form due to
lack of aliasing info. Runtime checks are generated to ensure the store
does not alias any other accesses in the loop.
Ordered fadd reductions are not yet supported.
Differential Revision: https://reviews.llvm.org/D110235
The availability of SVE should be sufficient to enable scalable
auto-vectorization.
This patch adds a new TTI interface to query the target what style of
vectorization it wants when scalable vectors are available. For other
targets than AArch64, this currently defaults to 'FixedWidthOnly'.
Differential Revision: https://reviews.llvm.org/D115651
This patch adds a TTI function, isElementTypeLegalForScalableVector, to query
whether it is possible to vectorize a given element type. This is called by
isLegalToVectorizeInstTypesForScalable to reject scalable vectorization if
any of the instruction types in the loop are unsupported, e.g:
int foo(__int128_t* ptr, int N)
#pragma clang loop vectorize_width(4, scalable)
for (int i=0; i<N; ++i)
ptr[i] = ptr[i] + 42;
This example currently crashes if we attempt to vectorize since i128 is not a
supported type for scalable vectorization.
Reviewed By: sdesmalen, david-arm
Differential Revision: https://reviews.llvm.org/D102253
Since d6de1e1a71406c75a4ea4d5a2fe84289f07ea3a1, no attributes is quivalent to
setting attribute to false.
This is a preliminary commit for https://reviews.llvm.org/D99080
This patch adds a new option to the LoopVectorizer to control how
scalable vectors can be used.
Initially, this suggests three levels to control scalable
vectorization, although other more aggressive options can be added in
the future.
The possible options are:
- Disabled: Disables vectorization with scalable vectors.
- Enabled: Vectorize loops using scalable vectors or fixed-width
vectors, but favors fixed-width vectors when the cost
is a tie.
- Preferred: Like 'Enabled', but favoring scalable vectors when the
cost-model is inconclusive.
Reviewed By: paulwalker-arm, vkmr
Differential Revision: https://reviews.llvm.org/D101945
Temporarily reverting this patch due to some unexpected issue found
by one of the PPC buildbots.
This reverts commit 584e9b6e4b4987b882719923e640eed854613d91.
This patch also refactors the way the feasible max VF is calculated,
although this is NFC for fixed-width vectors.
After this change scalable VF hints are no longer truncated/clamped
to a shorter scalable VF, nor does it drop the 'scalable flag' from
the suggested VF to vectorize with a similar VF that is fixed.
Instead, the hint is ignored which means the vectorizer is free
to find a more suitable VF, using the CostModel to determine the
best possible VF.
Reviewed By: c-rhodes, fhahn
Differential Revision: https://reviews.llvm.org/D98509
This patch enables scalable vectorization of loops with integer/fast reductions, e.g:
```
unsigned sum = 0;
for (int i = 0; i < n; ++i) {
sum += a[i];
}
```
A new TTI interface, isLegalToVectorizeReduction, has been added to prevent
reductions which are not supported for scalable types from vectorizing.
If the reduction is not supported for a given scalable VF,
computeFeasibleMaxVF will fall back to using fixed-width vectorization.
Reviewed By: david-arm, fhahn, dmgreen
Differential Revision: https://reviews.llvm.org/D95245
