Revert "[NFCI] Regenerate SROA/LoopVectorize test checks"

This reverts commit 14e3450fb57305aa9ff3e9e60687b458e43835c9.

[NFCI] Regenerate LoopVectorize test checks

[IR] In ConstantFoldShuffleVectorInstruction use zeroinitializer for splats of 0

When creating a splat of 0 for scalable vectors we tend to create them
with using a combination of shufflevector and

[IR] In ConstantFoldShuffleVectorInstruction use zeroinitializer for splats of 0

When creating a splat of 0 for scalable vectors we tend to create them
with using a combination of shufflevector and insertelement, i.e.

shufflevector (<vscale x 4 x i32> insertelement (<vscale x 4 x i32> poison, i32 0, i32 0),
<vscale x 4 x i32> poison, <vscale x 4 x i32> zeroinitializer)

However, for the case of a zero splat we can actually just replace the
above with zeroinitializer instead. This makes the IR a lot simpler and
easier to read. I have changed ConstantFoldShuffleVectorInstruction to
use zeroinitializer when creating a splat of integer 0 or FP +0.0 values.

Differential Revision: https://reviews.llvm.org/D113394

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[LoopVectorize] Permit vectorisation of more select(cmp(), X, Y) reduction patterns

This patch adds further support for vectorisation of loops that involve
selecting an integer value based on a prev

[LoopVectorize] Permit vectorisation of more select(cmp(), X, Y) reduction patterns

This patch adds further support for vectorisation of loops that involve
selecting an integer value based on a previous comparison. Consider the
following C++ loop:

int r = a;
for (int i = 0; i < n; i++) {
if (src[i] > 3) {
r = b;
}
src[i] += 2;
}

We should be able to vectorise this loop because all we are doing is
selecting between two states - 'a' and 'b' - both of which are loop
invariant. This just involves building a vector of values that contain
either 'a' or 'b', where the final reduced value will be 'b' if any lane
contains 'b'.

The IR generated by clang typically looks like this:

%phi = phi i32 [ %a, %entry ], [ %phi.update, %for.body ]
...
%pred = icmp ugt i32 %val, i32 3
%phi.update = select i1 %pred, i32 %b, i32 %phi

We already detect min/max patterns, which also involve a select + cmp.
However, with the min/max patterns we are selecting loaded values (and
hence loop variant) in the loop. In addition we only support certain
cmp predicates. This patch adds a new pattern matching function
(isSelectCmpPattern) and new RecurKind enums - SelectICmp & SelectFCmp.
We only support selecting values that are integer and loop invariant,
however we can support any kind of compare - integer or float.

Tests have been added here:

Transforms/LoopVectorize/AArch64/sve-select-cmp.ll
Transforms/LoopVectorize/select-cmp-predicated.ll
Transforms/LoopVectorize/select-cmp.ll

Differential Revision: https://reviews.llvm.org/D108136

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Revert "[LoopVectorize] Permit vectorisation of more select(cmp(), X, Y) reduction patterns"

It appears to cause stage2 clang build failures, e.g.,
https://lab.llvm.org/buildbot/#/builders/74/builds

Revert "[LoopVectorize] Permit vectorisation of more select(cmp(), X, Y) reduction patterns"

It appears to cause stage2 clang build failures, e.g.,
https://lab.llvm.org/buildbot/#/builders/74/builds/7145.

This reverts commit 1fb37334bdb3cdb028977382fbd84cebde64ebb2.

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[LoopVectorize] Permit vectorisation of more select(cmp(), X, Y) reduction patterns

This patch adds further support for vectorisation of loops that involve
selecting an integer value based on a prev

[LoopVectorize] Permit vectorisation of more select(cmp(), X, Y) reduction patterns

This patch adds further support for vectorisation of loops that involve
selecting an integer value based on a previous comparison. Consider the
following C++ loop:

int r = a;
for (int i = 0; i < n; i++) {
if (src[i] > 3) {
r = b;
}
src[i] += 2;
}

We should be able to vectorise this loop because all we are doing is
selecting between two states - 'a' and 'b' - both of which are loop
invariant. This just involves building a vector of values that contain
either 'a' or 'b', where the final reduced value will be 'b' if any lane
contains 'b'.

The IR generated by clang typically looks like this:

%phi = phi i32 [ %a, %entry ], [ %phi.update, %for.body ]
...
%pred = icmp ugt i32 %val, i32 3
%phi.update = select i1 %pred, i32 %b, i32 %phi

We already detect min/max patterns, which also involve a select + cmp.
However, with the min/max patterns we are selecting loaded values (and
hence loop variant) in the loop. In addition we only support certain
cmp predicates. This patch adds a new pattern matching function
(isSelectCmpPattern) and new RecurKind enums - SelectICmp & SelectFCmp.
We only support selecting values that are integer and loop invariant,
however we can support any kind of compare - integer or float.

Tests have been added here:

Transforms/LoopVectorize/AArch64/sve-select-cmp.ll
Transforms/LoopVectorize/select-cmp-predicated.ll
Transforms/LoopVectorize/select-cmp.ll

Differential Revision: https://reviews.llvm.org/D108136

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[LV] Mark increment of main vector loop induction variable as NUW.

This patch marks the induction increment of the main induction variable
of the vector loop as NUW when not folding the tail.

If th

[LV] Mark increment of main vector loop induction variable as NUW.

This patch marks the induction increment of the main induction variable
of the vector loop as NUW when not folding the tail.

If the tail is not folded, we know that End - Start >= Step (either
statically or through the minimum iteration checks). We also know that both
Start % Step == 0 and End % Step == 0. We exit the vector loop if %IV +
%Step == %End. Hence we must exit the loop before %IV + %Step unsigned
overflows and we can mark the induction increment as NUW.

This should make SCEV return more precise bounds for the created vector
loops, used by later optimizations, like late unrolling.

At the moment quite a few tests still need to be updated, but before
doing so I'd like to get initial feedback to make sure I am not missing
anything.

Note that this could probably be further improved by using information
from the original IV.

Attempt of modeling of the assumption in Alive2:
https://alive2.llvm.org/ce/z/H_DL_g

Part of a set of fixes required for PR50412.

Reviewed By: mkazantsev

Differential Revision: https://reviews.llvm.org/D103255

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[LV] Add -scalable-vectorization=<option> flag.

This patch adds a new option to the LoopVectorizer to control how
scalable vectors can be used.

Initially, this suggests three levels to control scal

[LV] Add -scalable-vectorization=<option> flag.

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

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[LoopVectorize][SVE] Remove assert for scalable vector in InnerLoopVectorizer::fixReduction

The function fixReduction used to assert/crash for scalable vector when
a vector reduce could be done with

[LoopVectorize][SVE] Remove assert for scalable vector in InnerLoopVectorizer::fixReduction

The function fixReduction used to assert/crash for scalable vector when
a vector reduce could be done with a smaller vector.
This patch removes this assertion as it is safe to use scalable vector for
vector reduce and truncate.

Differential Revision: https://reviews.llvm.org/D101260

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