Currently we will allow loops with a fixed width VF of 1 to vectorize
if the -enable-strict-reductions flag is set. However, the loop vectorizer
will not use ordered reductions if `VF.isScalar()` and the resulting
vectorized loop will be out of order.
This patch removes `VF.isVector()` when checking if ordered reductions
should be used. Also, instead of converting the FAdds to reductions if the
VF = 1, operands of the FAdds are changed such that the order is preserved.
Reviewed By: david-arm
Differential Revision: https://reviews.llvm.org/D104533
Sinking scalar operands into predicated-triangle regions may allow
merging regions. This patch adds a VPlan-to-VPlan transform that tries
to merge predicate-triangle regions after sinking.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D100260
This patch updates VPWidenPHI recipes for first-order recurrences to
also track the incoming value from the back-edge. Similar to D99294,
which did the same for reductions.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D104197
Make getPointersDiff() and sortPtrAccesses() compatible with opaque
pointers by explicitly passing in the element type instead of
determining it from the pointer element type.
The SLPVectorizer result is slightly non-optimal in that unnecessary
pointer bitcasts are added.
Differential Revision: https://reviews.llvm.org/D104784
Perform better analysis when trying to vectorize PHIs.
1. Do not try to vectorize vector PHIs.
2. Do deeper analysis for more profitable nodes for the vectorization.
Before we just tried to vectorize the PHIs of the same type. Patch
improves this and tries to vectorize PHIs with incoming values which
come from the same basic block, have the same and/or alternative
opcodes.
It allows to save the compile time and provides better vectorization
results in general.
Part of D57059.
Differential Revision: https://reviews.llvm.org/D103638
This really isn't talking about vectors in general,
but only about either fixed or scalable vectors,
and it's pretty confusing to see it state
that there aren't any vectors :)
At the moment, we create insertelement instructions directly after
LastInst when inserting scalar values in a vector in
VPTransformState::get.
This results in invalid IR when LastInst is a phi, followed by another
phi. In that case, the new instructions should be inserted just after
the last PHI node in the block.
At the moment, I don't think the problematic case can be triggered, but
it can happen once predicate regions are merged and multiple
VPredInstPHI recipes are in the same block (D100260).
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D104188
This can be seen as a follow up to commit 0ee439b705,
that changed the second argument of __powidf2, __powisf2 and
__powitf2 in compiler-rt from si_int to int. That was to align with
how those runtimes are defined in libgcc.
One thing that seem to have been missing in that patch was to make
sure that the rest of LLVM also handle that the argument now depends
on the size of int (not using the si_int machine mode for 32-bit).
When using __builtin_powi for a target with 16-bit int clang crashed.
And when emitting libcalls to those rtlib functions, typically when
lowering @llvm.powi), the backend would always prepare the exponent
argument as an i32 which caused miscompiles when the rtlib was
compiled with 16-bit int.
The solution used here is to use an overloaded type for the second
argument in @llvm.powi. This way clang can use the "correct" type
when lowering __builtin_powi, and then later when emitting the libcall
it is assumed that the type used in @llvm.powi matches the rtlib
function.
One thing that needed some extra attention was that when vectorizing
calls several passes did not support that several arguments could
be overloaded in the intrinsics. This patch allows overload of a
scalar operand by adding hasVectorInstrinsicOverloadedScalarOpd, with
an entry for powi.
Differential Revision: https://reviews.llvm.org/D99439
As Eli mentioned post-commit in D103378, the result of the freeze may
still be out-of-range according to Alive2. So for now, just limit the
transform to indices that are non-poison.
It was found by chance revealing discrepancy between comment (few lines above),
the condition and how re-ordering of instruction is done inside the if statement
it guards. The condition was always evaluated to true.
Differential Revision: https://reviews.llvm.org/D104064
We were passing the RecurrenceDescriptor by value to most of the reduction analysis methods, despite it being rather bulky with TrackingVH members (that can be costly to copy). In all these cases we're only using the RecurrenceDescriptor for rather basic purposes (access to types/kinds etc.).
Differential Revision: https://reviews.llvm.org/D104029
This fixes the concern in single element store scalarization that the
alignment of new store may be larger than it should be. It calculates
the largest alignment if index is constant, and a safe one if not.
Reviewed By: lebedev.ri, spatel
Differential Revision: https://reviews.llvm.org/D103419
First we refactor the code which does no wrapping add sequences
match: we need to allow different operand orders for
the key add instructions involved in the match.
Then we use the refactored code trying 4 variants of matching operands.
Originally the code relied on the fact that the matching operands
of the two last add instructions of memory index calculations
had the same LHS argument. But which operand is the same
in the two instructions is actually not essential, so now we allow
that to be any of LHS or RHS of each of the two instructions.
This increases the chances of vectorization to happen.
Reviewed By: volkan
Differential Revision: https://reviews.llvm.org/D103912
As noted in https://bugs.llvm.org/show_bug.cgi?id=46666, the current behavior of assuming if-conversion safety if a loop is annotated parallel (`!llvm.loop.parallel_accesses`), is not expectable, the documentation for this behavior was since removed from the LangRef again, and can lead to invalid reads.
This was observed in POCL (https://github.com/pocl/pocl/issues/757) and would require similar workarounds in current work at hipSYCL.
The question remains why this was initially added and what the implications of removing this optimization would be.
Do we need an alternative mechanism to propagate the information about legality of if-conversion?
Or is the idea that conditional loads in `#pragma clang loop vectorize(assume_safety)` can be executed unmasked without additional checks flawed in general?
I think this implication is not part of what a user of that pragma (and corresponding metadata) would expect and thus dangerous.
Only two additional tests failed, which are adapted in this patch. Depending on the further direction force-ifcvt.ll should be removed or further adapted.
Reviewed By: jdoerfert
Differential Revision: https://reviews.llvm.org/D103907
There is no need to schedule insertelement instructions. The compiler
did not schedule them before it started support their vectorization and
it should not do it after. We pre-schedule them manually when finding
a build vector sequence.
Disabling scheduling of insertelement instructions improves compile
time and vectorization of the very large basic blocks by saving
scheduling budget for other instructions.
Differential Revision: https://reviews.llvm.org/D104026
```
llvm-project/llvm/lib/Transforms/Vectorize/LoopVectorize.cpp:8024:19: warning: loop variable 'VF' of type 'const llvm::ElementCount' creates a copy from type 'const llvm::ElementCount' [-Wrange-loop-analysis]
for (const auto VF : VFCandidates) {
^
llvm-project/llvm/lib/Transforms/Vectorize/LoopVectorize.cpp:8024:8: note: use reference type 'const llvm::ElementCount &' to prevent copying
for (const auto VF : VFCandidates) {
^~~~~~~~~~~~~~~
&
1 warning generated.
```
Differential Revision: https://reviews.llvm.org/D103970
1. Better sorting of scalars to be gathered. Trying to insert
constants/arguments/instructions-out-of-loop at first and only then
the instructions which are inside the loop. It improves hoisting of
invariant insertelements instructions.
2. Better detection of shuffle candidates in gathering function.
3. The cost of insertelement for constants is 0.
Part of D57059.
Differential Revision: https://reviews.llvm.org/D103458
If the `-enable-strict-reductions` flag is set to true, then currently we will
always choose to vectorize the loop with strict in-order reductions. This is
not necessary where we allow the reordering of FP operations, such as
when loop hints are passed via metadata.
This patch moves useOrderedReductions so that we can also check whether
loop hints allow reordering, in which case we should use the default
behaviour of vectorizing with unordered reductions.
Reviewed By: sdesmalen
Differential Revision: https://reviews.llvm.org/D103814
The non-DOT printing does not include the successors of VPregionBlocks.
This patch use the same style for printing successors as for
VPBasicBlock.
I think the printing of successors could be a bit improved further, as
at the moment it is hard to ensure a check line matches all successors.
But that can be done as follow-up.
Reviewed By: a.elovikov
Differential Revision: https://reviews.llvm.org/D103515
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
No need to recalculate the cost of extractelements, just no need to
compensate the cost of all extractelements, need to check before if this
is actually going to be removed at the vectorization. Also, no need to
generate new extractelement instruction, we may just regenerate the
original one. It may improve the final vectorization.
Differential Revision: https://reviews.llvm.org/D102933
tryToVectorizeList function allows to reorder only 2 scalars. Patch
allows to reorder >2 scalars. Also, to avoid possible regressions, it
allows extra vectorization of the remaining parts of the scalars
elements if possible.
Part of D57059.
Differential Revision: https://reviews.llvm.org/D103247
As noticed by NAKAMURA Takumi back in 2017, we cannot use
properlyDominates for std::stable_sort as properlyDominates only
partially orders blocks. That is, for blocks A, B, C, D, where A
dominates B and C dominates D, we have A == C, B == C, but A < B. This
is not a valid comparison function for std::stable_sort and causes
different results between libstdc++ and libc++. This change uses DFS
numbering to give deterministic results for all reachable blocks.
Unreachable blocks are ignored already, so do not need special
consideration.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D103441
This patch uses the calculated maximum scalable VFs to build VPlans,
cost them and select a suitable scalable VF.
Reviewed By: paulwalker-arm
Differential Revision: https://reviews.llvm.org/D98722
llvm::getLoadStoreType was added recently and has the same implementation
as 'getMemInstValueType' in LoopVectorize.cpp. Since there is no
value in having two implementations, this patch removes the custom LV
implementation in favor of the generic one defined in Instructions.h.
As the existing test unreachable.ll shows, we should be doing more
work to avoid entering unreachable blocks: we should not stop
vectorization just because a PHI incoming value from an unreachable
block cannot be vectorized. We know that particular value will never
be used so we can just replace it with poison.
Implemented better scheme for perfect/shuffled matches of the gather
nodes which allows to fix the performance regressions introduced by
earlier patches. Starting detecting matches for broadcast nodes and
extractelement gathering.
Differential Revision: https://reviews.llvm.org/D102920
If the index itself is already poison, the poison propagates through
instructions clamping the index to a valid range. This still causes
introducing a load of poison, as flagged by Alive2 and pointed out
at 575e2aff55.
This patch updates the code to freeze the index, unless it is proven to
not be poison.
Reviewed By: nlopes
Differential Revision: https://reviews.llvm.org/D103378
Update isFirstOrderRecurrence to explore all uses of a recurrence phi
and check if we can sink them. If there are multiple users to sink, they
are all mapped to the previous instruction.
Fixes PR44286 (and another PR or two).
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D84951
For uniform ReplicateRecipes, only the first lane should be used, so
sinking them would mean we have to compute the value of the first lane
multiple times. Also, at the moment, sinking them causes a crash because
the value of the first lane is re-used by all users.
Reported post-commit for D100258.
SLP vectorizer should not consider in sertelements with multiple uses as
a part of high level build vector, it must be considered as
a terminating insertelement in the vector build, otherwise it may
produce incorrect code.
Differential Revision: https://reviews.llvm.org/D103164
When loop hints are passed via metadata, the allowReordering function
in LoopVectorizationLegality will allow the order of floating point
operations to be changed:
bool allowReordering() const {
// When enabling loop hints are provided we allow the vectorizer to change
// the order of operations that is given by the scalar loop. This is not
// enabled by default because can be unsafe or inefficient.
The -enable-strict-reductions flag introduced in D98435 will currently only
vectorize reductions in-loop if hints are used, since canVectorizeFPMath()
will return false if reordering is not allowed.
This patch changes canVectorizeFPMath() to query whether it is safe to
vectorize the loop with ordered reductions if no hints are used. For
testing purposes, an additional flag (-hints-allow-reordering) has been
added to disable the reordering behaviour described above.
Reviewed By: sdesmalen
Differential Revision: https://reviews.llvm.org/D101836
We can only scalarize memory accesses if we know the index is valid.
This patch adjusts canScalarizeAcceess to fall back to
computeConstantRange to check if the index is known to be valid.
Reviewed By: nlopes
Differential Revision: https://reviews.llvm.org/D102476
This patch adds a first VPlan-based implementation of sinking of scalar
operands.
The current version traverse a VPlan once and processes all operands of
a predicated REPLICATE recipe. If one of those operands can be sunk,
it is moved to the block containing the predicated REPLICATE recipe.
Continue with processing the operands of the sunk recipe.
The initial version does not re-process candidates after other recipes
have been sunk. It also cannot partially sink induction increments at
the moment. The VPlan only contains WIDEN-INDUCTION recipes and if the
induction is used for example in a GEP, only the first lane is used and
in the lowered IR the adds for the other lanes can be sunk into the
predicated blocks.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D100258
This reverts commit 94d54155e2.
This fixes a sanitizer failure by moving scalarizeLoadExtract(I)
before foldSingleElementStore(I), which may remove instructions.
This patch adds a new combine that tries to scalarize chains of
`extractelement (load %ptr), %idx` to `load (gep %ptr, %idx)`. This is
profitable when extracting only a few elements out of a large vector.
At the moment, `store (extractelement (load %ptr), %idx), %ptr`
operations on large vectors result in huge code in the backend.
This can easily be triggered by using the matrix extension, e.g.
https://clang.godbolt.org/z/qsccPdPf4
This should complement D98240.
Reviewed By: spatel
Differential Revision: https://reviews.llvm.org/D100273
External insertelement users can be represented as a result of shuffle
of the vectorized element and noconsecutive insertlements too. Added
support for handling non-consecutive insertelements.
Differential Revision: https://reviews.llvm.org/D101555
If we gather extract elements and they actually are just shuffles, it
might be profitable to vectorize them even if the tree is tiny.
Differential Revision: https://reviews.llvm.org/D101460
In InnerLoopVectorizer::setDebugLocFromInst we were previously
asserting that the VF is not scalable. This is because we want to
use the number of elements to create a duplication factor for the
debug profiling data. However, for scalable vectors we only know the
minimum number of elements. I've simply removed the assert for now
and added a FIXME saying that we assume vscale is always 1. When
vscale is not 1 it just means that the profiling data isn't as
accurate, but shouldn't cause any functional problems.
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
This patch implements first part of Flow Sensitive SampleFDO (FSAFDO).
It has the following changes:
(1) disable current discriminator encoding scheme,
(2) new hierarchical discriminator for FSAFDO.
For this patch, option "-enable-fs-discriminator=true" turns on the new
functionality. Option "-enable-fs-discriminator=false" (the default)
keeps the current SampleFDO behavior. When the fs-discriminator is
enabled, we insert a flag variable, namely, llvm_fs_discriminator, to
the object. This symbol will checked by create_llvm_prof tool, and used
to generate a profile with FS-AFDO discriminators enabled. If this
happens, for an extbinary format profile, create_llvm_prof tool
will add a flag to profile summary section.
Differential Revision: https://reviews.llvm.org/D102246
Currently all AA analyses marked as preserved are stateless, not taking
into account their dependent analyses. So there's no need to mark them
as preserved, they won't be invalidated unless their analyses are.
SCEVAAResults was the one exception to this, it was treated like a
typical analysis result. Make it like the others and don't invalidate
unless SCEV is invalidated.
Reviewed By: asbirlea
Differential Revision: https://reviews.llvm.org/D102032
This allows cast/dyn_cast'ing from VPUser to recipes. This is needed
because there are VPUsers that are not recipes.
Reviewed By: gilr, a.elovikov
Differential Revision: https://reviews.llvm.org/D100257
This patch introduces a new class, MaxVFCandidates, that holds the
maximum vectorization factors that have been computed for both scalable
and fixed-width vectors.
This patch is intended to be NFC for fixed-width vectors, although
considering a scalable max VF (which is disabled by default) pessimises
tail-loop elimination, since it can no longer determine if any chosen VF
(less than fixed/scalable MaxVFs) is guaranteed to handle all vector
iterations if the trip-count is known. This issue will be addressed in
a future patch.
Reviewed By: fhahn, david-arm
Differential Revision: https://reviews.llvm.org/D98721
This reverts commit 6d3e3ae8a9.
Still seeing PPC build bot failures, and one arm self host bot failing. I'm officially stumped, and need help from a bot owner to reduce.
Resubmit after fixing test/Transforms/LoopVectorize/ARM/mve-gather-scatter-tailpred.ll
Previous commit message...
This is a resubmit of 3e5ce4 (which was reverted by 7fe41ac). The original commit caused a PPC build bot failure we never really got to the bottom of. I can't reproduce the issue, and the bot owner was non-responsive. In the meantime, we stumbled across an issue which seems possibly related, and worked around a latent bug in 80e8025. My best guess is that the original patch exposed that latent issue at higher frequency, but it really is just a guess.
Original commit message follows...
If we know that the scalar epilogue is required to run, modify the CFG to end the middle block with an unconditional branch to scalar preheader. This is instead of a conditional branch to either the preheader or the exit block.
The motivation to do this is to support multiple exit blocks. Specifically, the current structure forces us to identify immediate dominators and *which* exit block to branch from in the middle terminator. For the multiple exit case - where we know require scalar will hold - these questions are ill formed.
This is the last change needed to support multiple exit loops, but since the diffs are already large enough, I'm going to land this, and then enable separately. You can think of this as being NFCIish prep work, but the changes are a bit too involved for me to feel comfortable tagging the review that way.
Differential Revision: https://reviews.llvm.org/D94892
This is a resubmit of 3e5ce4 (which was reverted by 7fe41ac). The original commit caused a PPC build bot failure we never really got to the bottom of. I can't reproduce the issue, and the bot owner was non-responsive. In the meantime, we stumbled across an issue which seems possibly related, and worked around a latent bug in 80e8025. My best guess is that the original patch exposed that latent issue at higher frequency, but it really is just a guess.
Original commit message follows...
If we know that the scalar epilogue is required to run, modify the CFG to end the middle block with an unconditional branch to scalar preheader. This is instead of a conditional branch to either the preheader or the exit block.
The motivation to do this is to support multiple exit blocks. Specifically, the current structure forces us to identify immediate dominators and *which* exit block to branch from in the middle terminator. For the multiple exit case - where we know require scalar will hold - these questions are ill formed.
This is the last change needed to support multiple exit loops, but since the diffs are already large enough, I'm going to land this, and then enable separately. You can think of this as being NFCIish prep work, but the changes are a bit too involved for me to feel comfortable tagging the review that way.
Differential Revision: https://reviews.llvm.org/D94892
As discussed in D102437, the VF argument to isScalarWithPredication
seems redundant, so this is intended to be a non-functional change. It
seems wrong to query the widening decision at this point. Removing the
operand and code to get the widening decision causes no unit/regression
tests to fail. I've also found no issues running the LLVM test-suite.
This subsequently removes the VF argument from isPredicatedInst as well,
since it is no longer required.
Add new type of tree node for `InsertElementInst` chain forming vector.
These instructions could be either removed, or replaced by shuffles during
vectorization and we can add this node to cost model, so naturally estimating
their cost, getting rid of `CompensateCost` tricks and reducing further work
for InstCombine. This fixes PR40522 and PR35732 in a natural way. Also this
patch is the first step towards revectorization of partially vectorization
(to fix PR42022 completely). After adding inserts to tree the next step is
to add vector instructions there (for instance, to merge `store <2 x float>`
and `store <2 x float>` to `store <4 x float>`).
Fixes PR40522 and PR35732.
Differential Revision: https://reviews.llvm.org/D98714
This change enables cases for which the index value for the first
load/store instruction in a pair could be a function argument. This
allows using llvm.assume to provide known bits information in such
cases.
Patch by Viacheslav Nikolaev. Thanks!
Differential Revision: https://reviews.llvm.org/D101680
In InnerLoopVectorizer::widenPHIInstruction there are cases where we have
to scalarise a pointer induction variable after vectorisation. For scalable
vectors we already deal with the case where the pointer induction variable
is uniform, but we currently crash if not uniform. For fixed width vectors
we calculate every lane of the scalarised pointer induction variable for a
given VF, however this cannot work for scalable vectors. In this case I
have added support for caching the whole vector value for each unrolled
part so that we can always extract an arbitrary element. Additionally, we
still continue to cache the known minimum number of lanes too in order
to improve code quality by avoiding an extractelement operation.
I have adapted an existing test `pointer_iv_mixed` from the file:
Transforms/LoopVectorize/consecutive-ptr-uniforms.ll
and added it here for scalable vectors instead:
Transforms/LoopVectorize/AArch64/sve-widen-phi.ll
Differential Revision: https://reviews.llvm.org/D101294
Vector single element update optimization is landed in 2db4979. But the
scope needs restriction. This patch restricts the index to inbounds and
vector must be fixed sized. In future, we may use value tracking to
relax constant restrictions.
Reviewed By: fhahn
Differential Revision: https://reviews.llvm.org/D102146
If the simplified VPValue is a recipe, we need to register it for Instr,
in case it needs to be recorded. The way this is handled in general may
change soon, following some post-commit comments.
This fixes PR50298.
The test example from https://llvm.org/PR50256 (and reduced here)
shows that we can match a load combine candidate even when there
are no "or" instructions. We can avoid that by confirming that we
do see an "or". This doesn't apply when matching an or-reduction
because that match begins from the operands of the reduction.
Differential Revision: https://reviews.llvm.org/D102074
Need to remove the old code for avoiding double counting of the gather
nodes with perfect diamond matches within the tree after we started
detecting perfect/shuffled matching in the previous patch D100495. We
may skip the cost for such nodes completely.
Differential Revision: https://reviews.llvm.org/D102023
The comment incorrectly states that the PHI is recorded. That's not
accurate, only the recipe for the incoming value is recorded.
Suggested post-commit for 4ba8720f88.
Currently sinking a replicate region into another replicate region is
not supported. Add an assert, to make the problem more obvious, should
it occur.
Discussed post-commit for ccebf7a109.
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
The loop vectorizer will currently assume a large trip count when
calculating which of several vectorization factors are more profitable.
That is often not a terrible assumption to make as small trip count
loops will usually have been fully unrolled. There are cases however
where we will try to vectorize them, and especially when folding the
tail by masking can incorrectly choose to vectorize loops that are not
beneficial, due to the folded tail rounding the iteration count up for
the vectorized loop.
The motivating example here has a trip count of 5, so either performs 5
scalar iterations or 2 vector iterations (with VF=4). At a high enough
trip count the vectorization becomes profitable, but the rounding up to
2 vector iterations vs only 5 scalar makes it unprofitable.
This adds an alternative cost calculation when we know the max trip
count and are folding tail by masking, rounding the iteration count up
to the correct number for the vector width. We still do not account for
anything like setup cost or the mixture of vector and scalar loops, but
this is at least an improvement in a few cases that we have had
reported.
Differential Revision: https://reviews.llvm.org/D101726
Adds support for scalable vectorization of loops containing first-order recurrences, e.g:
```
for(int i = 0; i < n; i++)
b[i] = a[i] + a[i - 1]
```
This patch changes fixFirstOrderRecurrence for scalable vectors to take vscale into
account when inserting into and extracting from the last lane of a vector.
CreateVectorSplice has been added to construct a vector for the recurrence, which
returns a splice intrinsic for scalable types. For fixed-width the behaviour
remains unchanged as CreateVectorSplice will return a shufflevector instead.
The tests included here are the same as test/Transform/LoopVectorize/first-order-recurrence.ll
Reviewed By: david-arm, fhahn
Differential Revision: https://reviews.llvm.org/D101076
LoopVectorize has a fairly deeply baked in design problem where it will try to query analysis (primarily SCEV, but also ValueTracking) in the midst of mutating IR. In particular, the intermediate IR state does not represent the semantics of the original (or final) program.
Fixing this for real is hard, but all of the cases seen so far share a common symptom. In cases seen to date, the analysis being queried is the computation of the original loop's trip count. We can fix this particular instance of the issue by simply computing the trip count early, and caching it.
I want to be really clear that this is nothing but a workaround. It does nothing to fix the root issue, and at best, delays the time until we have to fix this for real. Florian and I have discussed an eventual solution in the review comments for https://reviews.llvm.org/D100663, but it's a lot of work.
Test taken from https://reviews.llvm.org/D100663.
Differential Revision: https://reviews.llvm.org/D101487
This patch updates the code that sinks recipes required for first-order
recurrences to properly handle replicate-regions. At the moment, the
code would just move the replicate recipe out of its replicate-region,
producing an invalid VPlan.
When sinking a recipe in a replicate-region, we have to sink the whole
region. To do that, we first need to split the block at the target
recipe and move the region in between.
This patch also adds a splitAt helper to VPBasicBlock to split a
VPBasicBlock at a given iterator.
Fixes PR50009.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D100751
This patch updates the code handling reduction recipes to also keep
track of the incoming value from the latch in the recipe. This is needed
to model the def-use chains completely in VPlan, so that it is possible
to replace the incoming value with an arbitrary VPValue.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D99294
Need to check if target allows/supports masked gathers before trying to
estimate its cost, otherwise we may fail to vectorize some of the
patterns because of too pessimistic cost model.
Part of D57059.
Differential Revision: https://reviews.llvm.org/D101297
Need to check if target allows/supports masked gathers before trying to
estimate its cost, otherwise we may fail to vectorize some of the
patterns because of too pessimistic cost model.
Part of D57059.
Differential Revision: https://reviews.llvm.org/D101297
As we gradually move more elements of LV to VPlan, we are trying to
reduce the number of places that still has to check IR of the original
loop.
This patch adjusts the code to fix cross iteration phis to get the PHIs
to fix directly from the VPlan that is executed. We still need the
original PHI to check for first-order recurrences, but we can get rid of
that once we model that explicitly in VPlan as well.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D99293
This patch introduces a helper to obtain an iterator range for the
PHI-like recipes in a block.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D100101
If the extracts from the non-power-2 vectors are recognized as shuffles,
need some extra checks to not crash cost calculations if trying to gext
the ecost for subvector extracts. In this case need to check carefully
that we do not exit out of bounds of the original vector, otherwise the
TTI's cost model will crash on assert.
Differential Revision: https://reviews.llvm.org/D101477
Added an extra analysis for better choosing of shuffle kind in
getShuffleCost functions for better cost estimation if mask was
provided.
Differential Revision: https://reviews.llvm.org/D100865
Added an extra analysis for better choosing of shuffle kind in
getShuffleCost functions for better cost estimation if mask was
provided.
Differential Revision: https://reviews.llvm.org/D100865
As suggested in D99294, this adds a getVPSingleValue helper to use for
recipes that are guaranteed to define a single value. This replaces uses
of getVPValue() which used to default to I = 0.
This patch causes the loop vectorizer to not interleave loops that have
nounroll loop hints (llvm.loop.unroll.disable and llvm.loop.unroll_count(1)).
Note that if a particular interleave count is being requested
(through llvm.loop.interleave_count), it will still be honoured, regardless
of the presence of nounroll hints.
Reviewed By: Meinersbur
Differential Revision: https://reviews.llvm.org/D101374
This patch fixes a crash encountered when vectorising the following loop:
void foo(float *dst, float *src, long long n) {
for (long long i = 0; i < n; i++)
dst[i] = -src[i];
}
using scalable vectors. I've added a test to
Transforms/LoopVectorize/AArch64/sve-basic-vec.ll
as well as cleaned up the other tests in the same file.
Differential Revision: https://reviews.llvm.org/D98054
If the first tree element is vectorize and the second is gather, it
still might be profitable to vectorize it if the gather node contains
less scalars to vectorize than the original tree node. It might be
profitable to use shuffles.
Differential Revision: https://reviews.llvm.org/D101397
This patch simplifies the calculation of certain costs in
getInstructionCost when isScalarAfterVectorization() returns a true value.
There are a few places where we multiply a cost by a number N, i.e.
unsigned N = isScalarAfterVectorization(I, VF) ? VF.getKnownMinValue() : 1;
return N * TTI.getArithmeticInstrCost(...
After some investigation it seems that there are only these cases that occur
in practice:
1. VF is a scalar, in which case N = 1.
2. VF is a vector. We can only get here if: a) the instruction is a
GEP/bitcast/PHI with scalar uses, or b) this is an update to an induction
variable that remains scalar.
I have changed the code so that N is assumed to always be 1. For GEPs
the cost is always 0, since this is calculated later on as part of the
load/store cost. PHI nodes are costed separately and were never previously
multiplied by VF. For all other cases I have added an assert that none of
the users needs scalarising, which didn't fire in any unit tests.
Only one test required fixing and I believe the original cost for the scalar
add instruction to have been wrong, since only one copy remains after
vectorisation.
I have also added a new test for the case when a pointer PHI feeds directly
into a store that will be scalarised as we were previously never testing it.
Differential Revision: https://reviews.llvm.org/D99718
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
When using the -enable-strict-reductions flag where UF>1 we generate multiple
Phi nodes, though only one of these is used as an input to the vector.reduce.fadd
intrinsics. The unused Phi nodes are removed later by instcombine.
This patch changes widenPHIInstruction/fixReduction to only generate
one Phi, and adds an additional test for unrolling to strict-fadd.ll
Reviewed By: david-arm
Differential Revision: https://reviews.llvm.org/D100570
This patch simplifies the calculation of certain costs in
getInstructionCost when isScalarAfterVectorization() returns a true value.
There are a few places where we multiply a cost by a number N, i.e.
unsigned N = isScalarAfterVectorization(I, VF) ? VF.getKnownMinValue() : 1;
return N * TTI.getArithmeticInstrCost(...
After some investigation it seems that there are only these cases that occur
in practice:
1. VF is a scalar, in which case N = 1.
2. VF is a vector. We can only get here if: a) the instruction is a
GEP/bitcast/PHI with scalar uses, or b) this is an update to an induction
variable that remains scalar.
I have changed the code so that N is assumed to always be 1. For GEPs
the cost is always 0, since this is calculated later on as part of the
load/store cost. PHI nodes are costed separately and were never previously
multiplied by VF. For all other cases I have added an assert that none of
the users needs scalarising, which didn't fire in any unit tests.
Only one test required fixing and I believe the original cost for the scalar
add instruction to have been wrong, since only one copy remains after
vectorisation.
I have also added a new test for the case when a pointer PHI feeds directly
into a store that will be scalarised as we were previously never testing it.
Differential Revision: https://reviews.llvm.org/D99718
This patch simplifies VPSlotTracker by using the recursive traversal
iterator to traverse all blocks in a VPlan in reverse post-order when
numbering VPValues in a plan.
This depends on a fix to RPOT (D100169). It also extends the traversal
unit tests to check RPOT.
Reviewed By: a.elovikov
Differential Revision: https://reviews.llvm.org/D100176
When iterating over const blocks, the base type in the lambdas needs
to use const VPBlockBase *, otherwise it cannot be used with input
iterators over const VPBlockBase.
Also adjust the type of the input iterator range to const &, as it
does not take ownership of the input range.
This patch adds a blocksOnly helpers which take an iterator range
over VPBlockBase * or const VPBlockBase * and returns an interator
range that only include BlockTy blocks. The accesses are casted to
BlockTy.
Reviewed By: a.elovikov
Differential Revision: https://reviews.llvm.org/D101093
This patch adds a new iterator to traverse through VPRegionBlocks and a
GraphTraits specialization using the iterator to traverse through
VPRegionBlocks.
Because there is already a GraphTraits specialization for VPBlockBase *
and co, a new VPBlockRecursiveTraversalWrapper helper is introduced.
This allows us to provide a new GraphTraits specialization for that
type. Users can use the new recursive traversal by using this wrapper.
The graph trait visits both the entry block of a region, as well as all
its successors. Exit blocks of a region implicitly have their parent
region's successors. This ensures all blocks in a region are visited
before any blocks in a successor region when doing a reverse post-order
traversal of the graph.
Reviewed By: a.elovikov
Differential Revision: https://reviews.llvm.org/D100175
We can skip check for undefs trying to find perfect/shuffled tree
entries matching, they can be ignored completely improving the final
cost/vectorization results.
Differential Revision: https://reviews.llvm.org/D101061
This commit fixes a bug where the loop vectoriser fails to predicate
loads/stores when interleaving for targets that support masked
loads and stores.
Code such as:
1 void foo(int *restrict data1, int *restrict data2)
2 {
3 int counter = 1024;
4 while (counter--)
5 if (data1[counter] > data2[counter])
6 data1[counter] = data2[counter];
7 }
... could previously be transformed in such a way that the predicated
store implied by:
if (data1[counter] > data2[counter])
data1[counter] = data2[counter];
... was lost, resulting in miscompiles.
This bug was causing some tests in llvm-test-suite to fail when built
for SVE.
Differential Revision: https://reviews.llvm.org/D99569
1. No need to call `areAllUsersVectorized` as later the cost is
calculated only if the instruction has one use and gets vectorized.
2. Need to calculate the cost of the dead extractelement more precisely,
taking the vector type of the vector operand, not the resulting
vector type.
Part of D57059.
Differential Revision: https://reviews.llvm.org/D99980
In quite a few cases in LoopVectorize.cpp we call createStepForVF
with a step value of 0, which leads to unnecessary generation of
llvm.vscale intrinsic calls. I've optimised IRBuilder::CreateVScale
and createStepForVF to return 0 when attempting to multiply
vscale by 0.
Differential Revision: https://reviews.llvm.org/D100763
SLP supports perfect diamond matching for the vectorized tree entries
but do not support it for gathered entries and does not support
non-perfect (shuffled) matching with 1 or 2 tree entries. Patch adds
support for this matching to improve cost of the vectorized tree.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D100495
SLP supports perfect diamond matching for the vectorized tree entries
but do not support it for gathered entries and does not support
non-perfect (shuffled) matching with 1 or 2 tree entries. Patch adds
support for this matching to improve cost of the vectorized tree.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D100495
SLP supports perfect diamond matching for the vectorized tree entries
but do not support it for gathered entries and does not support
non-perfect (shuffled) matching with 1 or 2 tree entries. Patch adds
support for this matching to improve cost of the vectorized tree.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D100495
Rather than maintaining two separate values, a `float` for the per-lane
cost and a Width for the VF, maintain a single VectorizationFactor which
comprises the two and also removes the need for converting an integer value
to float.
This simplifies the query when asking if one VF is more profitable than
another when we want to extend this for scalable vectors (which may
require additional options to determine if e.g. a scalable VF of the
some cost, is more profitable than a fixed VF of the same cost).
The patch isn't entirely NFC because it also fixes an issue in
selectEpilogueVectorizationFactor, where the cost passed to ProfitableVFs
no longer truncates the floating-point cost from `float` to `unsigned` to
then perform the calculation on the truncated cost. It now does
a cost comparison with the correct precision.
Reviewed By: dmgreen
Differential Revision: https://reviews.llvm.org/D100121
SLP supports perfect diamond matching for the vectorized tree entries
but do not support it for gathered entries and does not support
non-perfect (shuffled) matching with 1 or 2 tree entries. Patch adds
support for this matching to improve cost of the vectorized tree.
Differential Revision: https://reviews.llvm.org/D100495
Add an initial version of a helper to determine whether a recipe may
have side-effects.
Reviewed By: a.elovikov
Differential Revision: https://reviews.llvm.org/D100259
There were a few places in widenPHIInstruction where calculations of
offsets were failing to take the runtime calculation of VF into
account for scalable vectors. I've fixed those cases in this patch
as well as adding an assert that we should not be scalarising for
scalable vectors.
Tests are added here:
Transforms/LoopVectorize/AArch64/sve-widen-phi.ll
Differential Revision: https://reviews.llvm.org/D99254
There are a few places in LoopVectorize.cpp where we have been too
cautious in adding VF.isScalable() asserts and it can be confusing.
It also makes it more difficult to see the genuine places where
work needs doing to improve scalable vectorization support.
This patch changes getMemInstScalarizationCost to return an
invalid cost instead of firing an assert for scalable vectors. Also,
vectorizeInterleaveGroup had multiple asserts all for the same
thing. I have removed all but one assert near the start of the
function, and added a new assert that we aren't dealing with masks
for scalable vectors.
Differential Revision: https://reviews.llvm.org/D99727
Only attempt to propagateIRFlags if we have both SelectInst - afaict we shouldn't have matched a min/max reduction without both SelectInst, but static analyzer doesn't know that.
Main reason is preparation to transform AliasResult to class that contains
offset for PartialAlias case.
Reviewed By: asbirlea
Differential Revision: https://reviews.llvm.org/D98027
Instead of passing the start value and the defined value to
widenPHIInstruction, pass the VPWidenPHIRecipe directly, which can be
used to get both (and more in future patches).
D99674 stopped the folding of certain select operations into and/or, due
to incorrect folding in the presence of poison. D97360 added some costs
to attempt to account for the change, but only worked at the getUserCost
level, not the getCmpSelInstrCost that the vectorizer will use directly.
This adds similar logic into the vectorizer to handle these logical
and/or selects, treating them like and/or directly.
This fixes 60% performance regressions from code like the attached test
case.
Differential Revision: https://reviews.llvm.org/D99884
No need to lookup through and/or try to vectorize operands of the
CmpInst instructions during attempts to find/vectorize min/max
reductions. Compiler implements postanalysis of the CmpInsts so we can
skip extra attempts in tryToVectorizeHorReductionOrInstOperands and save
compile time.
Differential Revision: https://reviews.llvm.org/D99950
Add the subclass, update a few places which check for the intrinsic to use idiomatic dyn_cast, and update the public interface of AssumptionCache to use the new class. A follow up change will do the same for the newer assumption query/bundle mechanisms.
Previously we could only vectorize FP reductions if fast math was enabled, as this allows us to
reorder FP operations. However, it may still be beneficial to vectorize the loop by moving
the reduction inside the vectorized loop and making sure that the scalar reduction value
be an input to the horizontal reduction, e.g:
%phi = phi float [ 0.0, %entry ], [ %reduction, %vector_body ]
%load = load <8 x float>
%reduction = call float @llvm.vector.reduce.fadd.v8f32(float %phi, <8 x float> %load)
This patch adds a new flag (IsOrdered) to RecurrenceDescriptor and makes use of the changes added
by D75069 as much as possible, which already teaches the vectorizer about in-loop reductions.
For now in-order reduction support is off by default and controlled with the `-enable-strict-reductions` flag.
Reviewed By: david-arm
Differential Revision: https://reviews.llvm.org/D98435
David Sherwood