This patch moves branch condition creation to enter the scalar epilogue
loop to VPlan. Modeling the branch in the middle block also requires
modeling the successor blocks. This is done using the recently
introduced VPIRBasicBlock.
Note that the middle.block is still created as part of the skeleton and
then patched in during VPlan execution. Unfortunately the skeleton needs
to create the middle.block early on, as it is also used for induction
resume value creation and is also needed to properly update the
dominator tree during skeleton creation.
After this patch lands, I plan to move induction resume value and phi
node creation in the scalar preheader to VPlan. Once that is done, we
should be able to create the middle.block in VPlan directly.
This is a re-worked version based on the earlier
https://reviews.llvm.org/D150398 and the main change is the use of
VPIRBasicBlock.
Depends on https://github.com/llvm/llvm-project/pull/92525
PR: https://github.com/llvm/llvm-project/pull/92651
Use VPIRBasicBlock to wrap the middle block and implement patching up
branches in predecessors in VPIRBasicBlock::execute. The IR middle block
is only created after skeleton creation. Initially a regular
VPBasicBlock is created, which will later be replaced by a
VPIRBasicBlock once the middle IR basic block has been created.
Note that this slightly changes the order of instructions created in the
middle block; code generated by recipe execution in the middle block
will now be inserted before the terminator (and in between the compare
to used by the terminator). The original order will be restored in
https://github.com/llvm/llvm-project/pull/92651.
PR: https://github.com/llvm/llvm-project/pull/95816
This reverts commit e4ea0997486000b460c4875a00301b73b3c0d6a7.
The recommit fixes a reported crash by adding a missing check to make
sure the cast recipes are only introduced when vectorizing.
Test coverage added in 3cac608fbd0811b2f5c59c6e13148162ccd8543e.
Original commit message:
Update the code to create Trunc/Ext recipes directly in
adjustRecipesForReductions instead of fixing it up later in
fixReductions.
This explicitly models the required conversions and also makes sure they
are generated at the right place (instead of after the exit condition),
hence the changes in a few tests.
Update the code to create Trunc/Ext recipes directly in
adjustRecipesForReductions instead of fixing it up later in
fixReductions.
This explicitly models the required conversions and also makes sure they
are generated at the right place (instead of after the exit condition),
hence the changes in a few tests.
Instcombine prefers this canonical form (see getPreferredVectorIndex),
as does IRBuilder when passing the index as an integer so we may as
well use the prefered form from creation.
NOTE: All test changes are mechanical with nothing else expected
beyond a change of index type from i32 to i64.
Differential Revision: https://reviews.llvm.org/D140983
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
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
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
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
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
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
