For the simple copy loop (see test case) vectorizer selects VF equal to 32 while the loop is known to have 17 iterations only. Such behavior makes no sense to me since such vector loop will never be executed. The only case we may want to select VF large than TC is masked vectoriztion. So I haven't touched that case.
Reviewed By: dmgreen
Differential Revision: https://reviews.llvm.org/D114528
Given a MLA reduction from two different types (say i8 and i16), we were
previously failing to find the reduction pattern, often making us chose
the lower vector factor. This improves that by using the largest of the
two extension types, allowing us to use the larger VF as the type of the
reduction.
As per https://godbolt.org/z/KP549EEYM the backend handles this
valiantly, leading to better performance.
Differential Revision: https://reviews.llvm.org/D115432
This patch simplifies handling of redundant induction casts, by
removing dead cast instructions after initial VPlan construction.
This has the following benefits:
1. fixes a crash
(see @test_optimized_cast_induction_feeding_first_order_recurrence)
2. Simplifies VPWidenIntOrFpInduction to a single-def recipes
3. Retires recordVectorLoopValueForInductionCast.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D115112
This patch adds on an overhead cost for gathers and scatters, which
is a rough estimate based on performance investigations I have
performed on SVE hardware for various micro-benchmarks.
Differential Revision: https://reviews.llvm.org/D115143
I've added some tests that were previously missing for the gather-scatter costs
being calculated by the vectorizer for AArch64:
Transforms/LoopVectorize/AArch64/sve-gather-scatter-cost.ll
The costs are sometimes different to the ones in
Analysis/CostModel/AArch64/sve-gather.ll
because the vectorizer also adds on the address computation cost.
The default for min is changed to 1. The behaviour of -mvscale-{min,max}
in Clang is also changed such that 16 is the max vscale when targeting
SVE and no max is specified.
Reviewed By: sdesmalen, paulwalker-arm
Differential Revision: https://reviews.llvm.org/D113294
If the condition of a select is a compare, pass its predicate to
TTI::getCmpSelInstrCost to get a more accurate cost value instead
of passing BAD_ICMP_PREDICATE.
I noticed that the commit message from D90070 had a comment about the
vectorized select predicate possibly being composed of other compares with
different predicate values, but I wasn't able to construct an example
where this was an actual issue. If this is an issue, I guess we could
add another check that the block isn't predicated for any reason.
Reviewed By: dmgreen, fhahn
Differential Revision: https://reviews.llvm.org/D114646
MVE can treat v16i1, v8i1, v4i1 and v2i1 as different views onto the
same 16bit VPR.P0 register, with v2i1 holding two 8 bit values for the
two halves. This was never treated as a legal type in llvm in the past
as there are not many 64bit instructions and no 64bit compares. There
are a few instructions that could use it though, notably a VSELECT (as
it can handle any size using the underlying v16i8 VPSEL), AND/OR/XOR for
similar reasons, some gathers/scatter and long multiplies and VCTP64
instructions.
This patch goes through and makes v2i1 a legal type, handling all the
cases that fall out of that. It also makes VSELECT legal for v2i64 as a
side benefit. A lot of the codegen changes as a result - usually in way
that is a little better or a little worse, but still expensive. Costs
can change a little too in the process, again in a way that expensive
things remain expensive. A lot of the tests that changed are mainly to
ensure correctness - the code can hopefully be improved in the future
where it comes up in practice.
The intrinsics currently remain using the v4i1 they previously did to
emulate a v2i1. This will be changed in a followup patch but this one
was already large enough.
Differential Revision: https://reviews.llvm.org/D114449
We ask `TTI.getAddressComputationCost()` about the cost of computing vector address,
and then multiply it by the vector width. This doesn't make any sense,
it implies that we'd do a vector GEP and then scalarize the vector of pointers,
but there is no such thing in the vectorized IR, we perform scalar GEP's.
This is *especially* bad on X86, and was effectively prohibiting any scalarized
vectorization of gathers/scatters, because `X86TTIImpl::getAddressComputationCost()`
says that cost of vector address computation is `10` as compared to `1` for scalar.
The computed costs are similar to the ones with D111222+D111220,
but we end up without masked memory intrinsics that we'd then have to
expand later on, without much luck. (D111363)
Differential Revision: https://reviews.llvm.org/D111460
collectLoopScalars should only add non-uniform nodes to the list if they
are used by a load/store instruction that is marked as CM_Scalarize.
Before this patch, the LV incorrectly marked pointer induction variables
as 'scalar' when they required to be widened by something else,
such as a compare instruction, and weren't used by a node marked as
'CM_Scalarize'. This case is covered by sve-widen-phi.ll.
This change also allows removing some code where the LV tried to
widen the PHI nodes with a stepvector, even though it was marked as
'scalarAfterVectorization'. Now that this code is more careful about
marking instructions that need widening as 'scalar', this code has
become redundant.
Differential Revision: https://reviews.llvm.org/D114373
In VPRecipeBuilder::handleReplication if we believe the instruction
is predicated we then proceed to create new VP region blocks even
when the load is uniform and only predicated due to tail-folding.
I have updated isPredicatedInst to avoid treating a uniform load as
predicated when tail-folding, which means we can do a single scalar
load and a vector splat of the value.
Tests added here:
Transforms/LoopVectorize/AArch64/tail-fold-uniform-memops.ll
Differential Revision: https://reviews.llvm.org/D112552
This patch updates the cost model for ordered reductions so that a call
to the llvm.fmuladd intrinsic is modelled as a normal fmul instruction
plus the cost of an ordered fadd reduction.
Differential Revision: https://reviews.llvm.org/D111630
In-loop vector reductions which use the llvm.fmuladd intrinsic involve
the creation of two recipes; a VPReductionRecipe for the fadd and a
VPInstruction for the fmul. If the call to llvm.fmuladd has fast-math flags
these should be propagated through to the fmul instruction, so an
interface setFastMathFlags has been added to the VPInstruction class to
enable this.
Differential Revision: https://reviews.llvm.org/D113125
This patch fixes PR52111. The problem is that LV propagates poison-generating flags (`nuw`/`nsw`, `exact`
and `inbounds`) in instructions that contribute to the address computation of widen loads/stores that are
guarded by a condition. It may happen that when the code is vectorized and the control flow within the loop
is linearized, these flags may lead to generating a poison value that is effectively used as the base address
of the widen load/store. The fix drops all the integer poison-generating flags from instructions that
contribute to the address computation of a widen load/store whose original instruction was in a basic block
that needed predication and is not predicated after vectorization.
Reviewed By: fhahn, spatel, nlopes
Differential Revision: https://reviews.llvm.org/D111846
A first step towards modeling preheader and exit blocks in VPlan as well.
Keeping the vector loop in a region allows for changing the VF as we
traverse region boundaries.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D113182
checkOrderedReductions looks for Phi nodes which can be classified as in-order,
meaning they can be vectorised without unsafe math. In order to vectorise the
reduction it should also be classified as in-loop by getReductionOpChain, which
checks that the reduction has two uses.
In this patch, a similar check is added to checkOrderedReductions so that we
now return false if there are more than two uses of the FAdd instruction.
This fixes PR52515.
Reviewed By: fhahn, david-arm
Differential Revision: https://reviews.llvm.org/D114002
This patch adds a reduced version of the test case from PR52024.
Together with 764d9aa979 the test causes a crash, because LV expands a
SCEV expression during code generation, when the dominator tree is not
up-to-date.
When getTypeConversion returns TypeScalarizeScalableVector we were
sometimes returning a non-simple type from getTypeLegalizationCost.
However, many callers depend upon this being a simple type and will
crash if not. This patch changes getTypeLegalizationCost to ensure
that we always a return sensible simple VT. If the vector type
contains unusual integer types, e.g. <vscale x 2 x i3>, then we just
set the type to MVT::i64 as a reasonable default.
A test has been added here that demonstrates the vectoriser can
correctly calculate the cost of vectorising a "zext i3 to i64"
instruction with a VF=vscale x 1:
Transforms/LoopVectorize/AArch64/sve-inductions-unusual-types.ll
Differential Revision: https://reviews.llvm.org/D113777
When asking how many parts are required for a scalable vector type
there are occasions when it cannot be computed. For example, <vscale x 1 x i3>
is one such vector for AArch64+SVE because at the moment no matter how we
promote the i3 type we never end up with a legal vector. This means
that getTypeConversion returns TypeScalarizeScalableVector as the
LegalizeKind, and then getTypeLegalizationCost returns an invalid cost.
This then causes BasicTTImpl::getNumberOfParts to dereference an invalid
cost, which triggers an assert. This patch changes getNumberOfParts to
return 0 for such cases, since the definition of getNumberOfParts in
TargetTransformInfo.h states that we can use a return value of 0 to represent
an unknown answer.
Currently, LoopVectorize.cpp is the only place where we need to check for
0 as a return value, because all other instances will not currently
ask for the number of parts for <vscale x 1 x iX> types.
In addition, I have changed the target-independent interface for
getNumberOfParts to return 1 and assume there is a single register
that can fit the type. The loop vectoriser has lots of tests that are
target-independent and they relied upon the 0 value to mean the
answer is known and that we are not scalarising the vector.
I have added tests here that show we correctly return an invalid cost
for VF=vscale x 1 when the loop contains unusual types such as i7:
Transforms/LoopVectorize/AArch64/sve-inductions-unusual-types.ll
Differential Revision: https://reviews.llvm.org/D113772
At the moment, computeRecurrenceType does not include any sign bits in
the maximum bit width. If the value can be negative, this means the sign
bit will be missing and the sext won't properly extend the value.
If the value can be negative, increment the bitwidth by one to make sure
there is at least one sign bit in the result value.
Note that the increment is also needed *if* the value is *known* to be
negative, as a sign bit needs to be preserved for the sext to work.
Note that this at the moment prevents vectorization, because the
analysis computes i1 as type for the recurrence when looking through the
AND in lookThroughAnd.
Fixes PR51794, PR52485.
Reviewed By: spatel
Differential Revision: https://reviews.llvm.org/D113056
This is one of those wonderful "in theory X doesn't matter, but in practice is does" changes. In this particular case, we shift the IVs inserted by the runtime unroller to clamp iteration count of the loops* from decrementing to incrementing.
Why does this matter? A couple of reasons:
* SCEV doesn't have a native subtract node. Instead, all subtracts (A - B) are represented as A + -1 * B and drops any flags invalidated by such. As a result, SCEV is slightly less good at reasoning about edge cases involving decrementing addrecs than incrementing ones. (You can see this in the inferred flags in some of the test cases.)
* Other parts of the optimizer produce incrementing IVs, and they're common in idiomatic source language. We do have support for reversing IVs, but in general if we produce one of each, the pair will persist surprisingly far through the optimizer before being coalesced. (You can see this looking at nearby phis in the test cases.)
Note that if the hardware prefers decrementing (i.e. zero tested) loops, LSR should convert back immediately before codegen.
* Mostly irrelevant detail: The main loop of the prolog case is handled independently and will simple use the original IV with a changed start value. We could in theory use this scheme for all iteration clamping, but that's a larger and more invasive change.
`collectElementTypesForWidening` collects the types of load, store and
reduction Phis in a loop. These types are later checked using
`isElementTypeLegalForScalableVector` to prevent vectorisation of
loops with instruction types that are unsupported.
This patch removes i1 from the list of types supported for scalable
vectors. This fixes an assert ("Cannot yet scalarize uniform stores") in
`setCostBasedWideningDecision` when we have a loop containing a uniform
i1 store and a scalable VF, which we cannot create a scatter for.
Reviewed By: david-arm
Differential Revision: https://reviews.llvm.org/D113680
Unfortunately sinking recipes for first-order recurrences relies on
the original position of recipes. So if a recipes needs to be sunk after
an optimized induction, it needs to stay in the original position, until
sinking is done. This is causing PR52460.
To fix the crash, keep the recipes in the original position until
sink-after is done.
Post-commit follow-up to c45045bfd0 to address PR52460.
This reverts commit 7cd273c339.
Several patches with tests fixes have been applied:
0cada82f0a "[Test] Remove incorrect test in GVN"
97cb13615d "[Test] Separate IndVars test into AArch64 and X86 parts"
985cc490f1 "[Test] Remove separated test in IndVars",
and test failures caused by 5ec2386 should be resolved now.
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
Changes VPReplicateRecipe to extract the last lane from an unconditional,
uniform store instruction. collectLoopUniforms will also add stores to
the list of uniform instructions where Legal->isUniformMemOp is true.
setCostBasedWideningDecision now sets the widening decision for
all uniform memory ops to Scalarize, where previously GatherScatter
may have been chosen for scalable stores.
This fixes an assert ("Cannot yet scalarize uniform stores") in
setCostBasedWideningDecision when we have a loop containing a
uniform i1 store and a scalable VF, which we cannot create a scatter for.
Reviewed By: sdesmalen, david-arm, fhahn
Differential Revision: https://reviews.llvm.org/D112725
This reapplies patch db289340c8.
The test failures on build with expensive checks caused by the patch happened due
to the fact that we sorted loop Phis in replaceCongruentIVs using llvm::sort,
which shuffles the given container if the expensive checks are enabled,
so equivalent Phis in the sorted vector had different mutual order from run
to run. replaceCongruentIVs tries to replace narrow Phis with truncations
of wide ones. In some test cases there were several Phis with the same
width, so if their order differs from run to run, the narrow Phis would
be replaced with a different Phi, depending on the shuffling result.
The patch ae14fae0ff fixed this issue by
replacing llvm::sort with llvm::stable_sort.
All phi-like recipes should be at the beginning of a VPBasicBlock with
no other recipes in between. Ensure that the recurrence-splicing recipe
is not added between phi-like recipes, but after them.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D111301
When targeting a specific CPU with scalable vectorization, the knowledge
of that particular CPU's vscale value can be used to tune the cost-model
and make the cost per lane less pessimistic.
If the target implements 'TTI.getVScaleForTuning()', the cost-per-lane
is calculated as:
Cost / (VScaleForTuning * VF.KnownMinLanes)
Otherwise, it assumes a value of 1 meaning that the behavior
is unchanged and calculated as:
Cost / VF.KnownMinLanes
Reviewed By: kmclaughlin, david-arm
Differential Revision: https://reviews.llvm.org/D113209
In IndVarSimplify after simplifying and extending loop IVs we call 'replaceCongruentIVs'.
This function optionally takes a TTI argument to be able to replace narrow IVs uses
with truncates of the widest one.
For some reason the TTI wasn't passed to the function, so it couldn't perform such
transform.
This patch fixes it.
Reviewed By: mkazantsev
Differential Revision: https://reviews.llvm.org/D113024
At the moment in LoopVectorizationCostModel::selectEpilogueVectorizationFactor
we bail out if the main vector loop uses a scalable VF. This patch adds
support for generating epilogue vector loops using a fixed-width VF when the
main vector loop uses a scalable VF.
I've changed LoopVectorizationCostModel::selectEpilogueVectorizationFactor
so that we convert the scalable VF into a fixed-width VF and do profitability
checks on that instead. In addition, since the scalable and fixed-width VFs
live in different VPlans that means I had to change the calls to
LVP.hasPlanWithVFs so that we only pass in the fixed-width VF.
New tests added here:
Transforms/LoopVectorize/AArch64/sve-epilog-vect.ll
Differential Revision: https://reviews.llvm.org/D109432
I've added a test for a loop containing a conditional uniform load for
a target that supports masked loads. The test just ensures that we
correctly use gather instructions and have the correct mask.
Differential Revision: https://reviews.llvm.org/D112619
This patch updates VPReductionRecipe::execute so that the fast-math
flags associated with the underlying instruction of the VPRecipe are
propagated through to the reductions which are created.
Differential Revision: https://reviews.llvm.org/D112548
We never expect the runtime VF to be negative so we should use
the uitofp instruction instead of sitofp.
Differential revision: https://reviews.llvm.org/D112610
This patch updates recipe creation to ensure all
VPWidenIntOrFpInductionRecipes are in the header block. At the moment,
new induction recipes can be created in different blocks when trying to
optimize casts and induction variables.
Having all induction recipes in the header makes it easier to
analyze/transform them in VPlan.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D111300
Upon further investigation and discussion,
this is actually the opposite direction from what we should be taking,
and this direction wouldn't solve the motivational problem anyway.
Additionally, some more (polly) tests have escaped being updated.
So, let's just take a step back here.
This reverts commit f3190dedee.
This reverts commit 749581d21f.
This reverts commit f3df87d57e.
This reverts commit ab1dbcecd6.
There's precedent for that in `CreateOr()`/`CreateAnd()`.
The motivation here is to avoid bloating the run-time check's IR
in `SCEVExpander::generateOverflowCheck()`.
Refs. https://reviews.llvm.org/D109368#3089809
It's a no-op, no overflow happens ever: https://alive2.llvm.org/ce/z/Zw89rZ
While generally i don't like such hacks,
we have a very good reason to do this: here we are expanding
a run-time correctness check for the vectorization,
and said `umul_with_overflow` will not be optimized out
before we query the cost of the checks we've generated.
Which means, the cost of run-time checks would be artificially inflated,
and after https://reviews.llvm.org/D109368 that will affect
the minimal trip count for which these checks are even evaluated.
And if they aren't even evaluated, then the vectorized code
certainly won't be run.
We could consider doing this in IRBuilder, but then we'd need to
also teach `CreateExtractValue()` to look into chain of `insertvalue`'s,
and i'm not sure there's precedent for that.
Refs. https://reviews.llvm.org/D109368#3089809
While we could emit such a tautological `select`,
it will stick around until the next instsimplify invocation,
which may happen after we count the cost of this redundant `select`.
Which is precisely what happens with loop vectorization legality checks,
and that artificially increases the cost of said checks,
which is bad.
There is prior art for this in `IRBuilderBase::CreateAnd()`/`IRBuilderBase::CreateOr()`.
Refs. https://reviews.llvm.org/D109368#3089809
I have removed LoopVectorizationPlanner::setBestPlan, since this
function is quite aggressive because it deletes all other plans
except the one containing the <VF,UF> pair required. The code is
currently written to assume that all <VF,UF> pairs will live in the
same vplan. This is overly restrictive, since scalable VFs live in
different plans to fixed-width VFS. When we add support for
vectorising epilogue loops when the main loop uses scalable vectors
then we will the vplan for the main loop will be different to the
epilogue.
Instead I have added a new function called
LoopVectorizationPlanner::getBestPlanFor
that returns the best vplan for the <VF,UF> pair requested and leaves
all the vplans untouched. We then pass this best vplan to
LoopVectorizationPlanner::executePlan
which now takes an additional VPlanPtr argument.
Differential revision: https://reviews.llvm.org/D111125
The math here is:
Cost of 1 load = cost of n loads / n
Cost of live loads = num live loads * Cost of 1 load
Cost of live loads = num live loads * (cost of n loads / n)
Cost of live loads = cost of n loads * (num live loads / n)
But, all the variables here are integers,
and integer division rounds down,
but this calculation clearly expects float semantics.
Instead multiply upfront, and then perform round-up-division.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D112302
This patch introduces a new function:
AArch64Subtarget::getVScaleForTuning
that returns a value for vscale that can be used for tuning the cost
model when using scalable vectors. The VScaleForTuning option in
AArch64Subtarget is initialised according to the following rules:
1. If the user has specified the CPU to tune for we use that, else
2. If the target CPU was specified we use that, else
3. The tuning is set to "generic".
For CPUs of type "generic" I have assumed that vscale=2.
New tests added here:
Analysis/CostModel/AArch64/sve-gather.ll
Analysis/CostModel/AArch64/sve-scatter.ll
Transforms/LoopVectorize/AArch64/sve-strict-fadd-cost.ll
Differential Revision: https://reviews.llvm.org/D110259
Right now when we see -O# we add the corresponding 'default<O#>' into
the list of passes to run when translating legacy -pass-name. This has
the side effect of not using the default AA pipeline.
Instead, treat -O# as -passes='default<O#>', but don't allow any other
-passes or -pass-name. I think we can keep `opt -O#` as shorthand for
`opt -passes='default<O#>` but disallow anything more than just -O#.
Tests need to be updated to not use `opt -O# -pass-name`.
Reviewed By: asbirlea
Differential Revision: https://reviews.llvm.org/D112036
This simplifies the return value of addRuntimeCheck from a pair of
instructions to a single `Value *`.
The existing users of addRuntimeChecks were ignoring the first element
of the pair, hence there is not reason to track FirstInst and return
it.
Additionally all users of addRuntimeChecks use the second returned
`Instruction *` just as `Value *`, so there is no need to return an
`Instruction *`. Therefore there is no need to create a redundant
dummy `and X, true` instruction any longer.
Effectively this change should not impact the generated code because the
redundant AND will be folded by later optimizations. But it is easy to
avoid creating it in the first place and it allows more accurately
estimating the cost of the runtime checks.
These cases use the same codegen as AVX2 (pshuflw/pshufd) for the sub-128bit vector deinterleaving, and unpcklqdq for v2i64.
It's going to take a while to add full interleaved cost coverage, but since these are the same for SSE2 -> AVX2 it should be an easy win.
Fixes PR47437
Differential Revision: https://reviews.llvm.org/D111938
And another attempt to start untangling this ball of threads around gather.
There's `TTI::prefersVectorizedAddressing()`hoop, which confusingly defaults to `true`,
which tells LV to try to vectorize the addresses that lead to loads,
but X86 generally can not deal with vectors of addresses,
the only instructions that support that are GATHER/SCATTER,
but even those aren't available until AVX2, and aren't really usable until AVX512.
This specializes the hook for X86, to return true only if we have AVX512 or AVX2 w/ fast gather.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D111546
While i've modelled most of the relevant tuples for AVX2,
that only covered fully-interleaved groups.
By definition, interleaving load of stride N means:
load N*VF elements, and shuffle them into N VF-sized vectors,
with 0'th vector containing elements `[0, VF)*stride + 0`,
and 1'th vector containing elements `[0, VF)*stride + 1`.
Example: https://godbolt.org/z/df561Me5E (i64 stride 4 vf 2 => cost 6)
Now, not fully interleaved load, is when not all of these vectors is demanded.
So at worst, we could just pretend that everything is demanded,
and discard the non-demanded vectors. What this means is that the cost
for not-fully-interleaved group should be not greater than the cost
for the same fully-interleaved group, but perhaps somewhat less.
Examples:
https://godbolt.org/z/a78dK5Geq (i64 stride 4 (indices 012u) vf 2 => cost 4)
https://godbolt.org/z/G91ceo8dM (i64 stride 4 (indices 01uu) vf 2 => cost 2)
https://godbolt.org/z/5joYob9rx (i64 stride 4 (indices 0uuu) vf 2 => cost 1)
As we have established over the course of last ~70 patches, (wow)
`BaseT::getInterleavedMemoryOpCos()` is absolutely bogus,
it is usually almost an order of magnitude overestimation,
so i would claim that we should at least use the hardcoded costs
of fully interleaved load groups.
We could go further and adjust them e.g. by the number of demanded indices,
but then i'm somewhat fearful of underestimating the cost.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D111174
`X86TTIImpl::getGSScalarCost()` has (at least) two issues:
* it naively computes the cost of sequence of `insertelement`/`extractelement`.
If we are operating not on the XMM (but YMM/ZMM),
this widely overestimates the cost of subvector insertions/extractions.
* Gather/scatter takes a vector of pointers, and scalarization results in us performing
scalar memory operation for each of these pointers, but we never account for the cost
of extracting these pointers out of the vector of pointers.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D111222
This patch fixes another crash revealed by PR51614:
when *deciding* to vectorize with masked interleave groups, check if the access
is reverse (which is currently not supported).
Differential Revision: https://reviews.llvm.org/D108900
collectLoopScalars collects pointer induction updates in ScalarPtrs, assuming
that the instruction will be scalar after vectorization. This may crash later
in VPReplicateRecipe::execute() if there there is another user of the instruction
other than the Phi node which needs to be widened.
This changes collectLoopScalars so that if there are any other users of
Update other than a Phi node, it is not added to ScalarPtrs.
Reviewed By: david-arm, fhahn
Differential Revision: https://reviews.llvm.org/D111294
At the moment, a VPValue is created for the backedge-taken count, which
is used by some recipes. To make it easier to identify the operands of
recipes using the backedge-taken count, print it at the beginning of the
VPlan if it is used.
Reviewed By: a.elovikov
Differential Revision: https://reviews.llvm.org/D111298
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
The only sched models that for cpu's that support avx2
but not avx512 are: haswell, broadwell, skylake, zen1-3
For load we have:
https://godbolt.org/z/n8aMKeo4E - for intels `Block RThroughput: =4.0`; for ryzens, `Block RThroughput: <=2.0`
So pick cost of `4`.
For store we have:
https://godbolt.org/z/n8aMKeo4E - for intels `Block RThroughput: =4.0`; for ryzens, `Block RThroughput: =2.0`
So pick cost of `4`.
I'm directly using the shuffling asm the llc produced,
without any manual fixups that may be needed
to ensure sequential execution.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D110755
The only sched models that for cpu's that support avx2
but not avx512 are: haswell, broadwell, skylake, zen1-3
For load we have:
https://godbolt.org/z/EM5Ean7bd - for intels `Block RThroughput: =2.0`; for ryzens, `Block RThroughput: =1.0`
So pick cost of `2`.
For store we have:
https://godbolt.org/z/EM5Ean7bd - for intels `Block RThroughput: =2.0`; for ryzens, `Block RThroughput: <=2.0`
So pick cost of `2`.
I'm directly using the shuffling asm the llc produced,
without any manual fixups that may be needed
to ensure sequential execution.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D110754
The only sched models that for cpu's that support avx2
but not avx512 are: haswell, broadwell, skylake, zen1-3
For load we have:
https://godbolt.org/z/4rY96hnGT - for intels `Block RThroughput: =2.0`; for ryzens, `Block RThroughput: =1.0`
So pick cost of `2`.
For store we have:
https://godbolt.org/z/vbo37Y3r9 - for intels `Block RThroughput: =1.0`; for ryzens, `Block RThroughput: =0.5`
So pick cost of `1`.
I'm directly using the shuffling asm the llc produced,
without any manual fixups that may be needed
to ensure sequential execution.
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D110753
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
The expansion for these was updated in https://reviews.llvm.org/D47927 but the cost model was not adjusted.
I believe the cost model was also incorrect for the old expansion.
The expansion prior to D47927 used 3 icmps using LHS, RHS, and Result
to calculate theirs signs. Then 2 icmps to compare the signs. Followed
by an And. The previous cost model was using 3 icmps and 2 selects.
Digging back through git blame, those 2 selects in the cost model used to
be 2 icmps, but were changed in https://reviews.llvm.org/D90681
Differential Revision: https://reviews.llvm.org/D110739
getScalarizationOverhead() results in a somewhat better cost estimation than counting the insertion/extraction costs directly. Notably, this is still overestimating the costs.
Original Patch by: @lebedev.ri (Roman Lebedev)
Differential Revision: https://reviews.llvm.org/D110713
This reverts commit 8fdac7cb7a.
The issue causing the revert has been fixed a while ago in 60b852092c.
Original message:
Now that SCEVExpander can preserve LCSSA form,
we do not have to worry about LCSSA form when
trying to look through PHIs. SCEVExpander will take
care of inserting LCSSA PHI nodes as required.
This increases precision of the analysis in some cases.
Reviewed By: mkazantsev, bmahjour
Differential Revision: https://reviews.llvm.org/D71539
Update the costs to match the codegen from combineMulToPMADDWD - not only can we use PMADDWD is its zero-extended, but also if its a constant or sign-extended from a vXi16 (which can be replaced with a zero-extension).
As we're checking the cost debug analysis these should match the original IR line - so we shouldn't have any variable naming issues.
I'm investigating v4i32 mul -> PMADDDW costs handling (for PR47437) and these CHECK lines were proving tricky to keep track of
This patch fixes the crash found by PR51614:
whenever doing tail folding, interleave groups must be considered under mask.
Another fix D108900 follows for targets that support masked loads and stores:
when *deciding* to vectorize with masked interleave groups, check if the access
is reverse - which is currently not supported; rather than (only) asserting when
computing cost and generating code.
Differential Revision: https://reviews.llvm.org/D108891
In ValueTracking.cpp we use a function called
computeKnownBitsFromOperator to determine the known bits of a value.
For the vscale intrinsic if the function contains the vscale_range
attribute we can use the maximum and minimum values of vscale to
determine some known zero and one bits. This should help to improve
code quality by allowing certain optimisations to take place.
Tests added here:
Transforms/InstCombine/icmp-vscale.ll
Differential Revision: https://reviews.llvm.org/D109883
Mostly this fixes cases where !noalias or !alias.scope were passed
a scope rather than a scope list. In some cases I opted to drop
the metadata entirely instead, because it is not really relevant
to the test.
This extends the reduction logic in the vectorizer to handle intrinsic
versions of min and max, both the floating point variants already
created by instcombine under fastmath and the integer variants from
D98152.
As a bonus this allows us to match a chain of min or max operations into
a single reduction, similar to how add/mul/etc work.
Differential Revision: https://reviews.llvm.org/D109645
This is a first step towards addressing the last remaining limitation of
the VPlan version of sinkScalarOperands: the legacy version can
partially sink operands. For example, if a GEP has uniform users outside
the sink target block, then the legacy version will sink all scalar
GEPs, other than the one for lane 0.
This patch works towards addressing this case in the VPlan version by
detecting such cases and duplicating the sink candidate. All users
outside of the sink target will be updated to use the uniform clone.
Note that this highlights an issue with VPValue naming. If we duplicate
a replicate recipe, they will share the same underlying IR value and
both VPValues will have the same name ir<%gep>.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D104254
SCEV does not look through non-header PHIs inside the loop. Such phis
can be analyzed by adding separate accesses for each incoming pointer
value.
This results in 2 more loops vectorized in SPEC2000/186.crafty and
avoids regressions when sinking instructions before vectorizing.
Fixes PR50296, PR50288.
Reviewed By: Meinersbur
Differential Revision: https://reviews.llvm.org/D102266
Users of VPValues are managed in a vector, so we need to be more
careful when iterating over users while updating them. For now, just
copy them.
Fixes 51798.
Currently, opaque pointers are supported in two forms: The
-force-opaque-pointers mode, where all pointers are opaque and
typed pointers do not exist. And as a simple ptr type that can
coexist with typed pointers.
This patch removes support for the mixed mode. You either get
typed pointers, or you get opaque pointers, but not both. In the
(current) default mode, using ptr is forbidden. In -opaque-pointers
mode, all pointers are opaque.
The motivation here is that the mixed mode introduces additional
issues that don't exist in fully opaque mode. D105155 is an example
of a design problem. Looking at D109259, it would probably need
additional work to support mixed mode (e.g. to generate GEPs for
typed base but opaque result). Mixed mode will also end up
inserting many casts between i8* and ptr, which would require
significant additional work to consistently avoid.
I don't think the mixed mode is particularly valuable, as it
doesn't align with our end goal. The only thing I've found it to
be moderately useful for is adding some opaque pointer tests in
between typed pointer tests, but I think we can live without that.
Differential Revision: https://reviews.llvm.org/D109290
For SVE, when scalarising the PHI instruction the whole vector part is
generated as opposed to creating instructions for each lane for fixed-
width vectors. However, in some cases the lane values may be needed
later (e.g for a load instruction) so we still need to calculate
these values to avoid extractelement being called on the vector part.
Differential Revision: https://reviews.llvm.org/D109445
Store the used element type in the InductionDescriptor. For typed
pointers, it remains the pointer element type. For opaque pointers,
we always use an i8 element type, such that the step is a simple
offset.
A previous version of this patch instead tried to guess the element
type from an induction GEP, but this is not reliable, as the GEP
may be hidden (see @both in iv_outside_user.ll).
Differential Revision: https://reviews.llvm.org/D104795
Reverted (manually due to merge conflicts) while regressions reported on PR51540 are investigated
As noticed on D106352, after we've folded "(select C, (gep Ptr, Idx), Ptr) -> (gep Ptr, (select C, Idx, 0))" if the inner Ptr was also a (now one use) gep we could then merge the geps, using the sum of the indices instead.
I've limited this to basic 2-op geps - a more general case further down InstCombinerImpl.visitGetElementPtrInst doesn't have the one-use limitation but only creates the add if it can be created via SimplifyAddInst.
https://alive2.llvm.org/ce/z/f8pLfD (Thanks Roman!)
Differential Revision: https://reviews.llvm.org/D106450
Adjusting the reduction recipes still relies on references to the
original IR, which can become outdated by the first-order recurrence
handling. Until reduction recipe construction does not require IR
references, move it before first-order recurrence handling, to prevent a
crash as exposed by D106653.
This reverts commit f4122398e7 to
investigate a crash exposed by it.
The patch breaks building the code below with `clang -O2 --target=aarch64-linux`
int a;
double b, c;
void d() {
for (; a; a++) {
b += c;
c = a;
}
}
I have added a new TTI interface called enableOrderedReductions() that
controls whether or not ordered reductions should be enabled for a
given target. By default this returns false, whereas for AArch64 it
returns true and we rely upon the cost model to make sensible
vectorisation choices. It is still possible to override the new TTI
interface by setting the command line flag:
-force-ordered-reductions=true|false
I have added a new RUN line to show that we use ordered reductions by
default for SVE and Neon:
Transforms/LoopVectorize/AArch64/strict-fadd.ll
Transforms/LoopVectorize/AArch64/scalable-strict-fadd.ll
Differential Revision: https://reviews.llvm.org/D106653
For tight loops like this:
float r = 0;
for (int i = 0; i < n; i++) {
r += a[i];
}
it's better not to vectorise at -O3 using fixed-width ordered reductions
on AArch64 targets. Although the resulting number of instructions in the
generated code ends up being comparable to not vectorising at all, there
may be additional costs on some CPUs, for example perhaps the scheduling
is worse. It makes sense to deter vectorisation in tight loops.
Differential Revision: https://reviews.llvm.org/D108292
Removed AArch64 usage of the getMaxVScale interface, replacing it with
the vscale_range(min, max) IR Attribute.
Reviewed By: paulwalker-arm
Differential Revision: https://reviews.llvm.org/D106277
LoopLoadElimination, LoopVersioning and LoopVectorize currently
fetch MemorySSA when construction LoopAccessAnalysis. However,
LoopAccessAnalysis does not actually use MemorySSA and we can pass
nullptr instead.
This saves one MemorySSA calculation in the default pipeline, and
thus improves compile-time.
Differential Revision: https://reviews.llvm.org/D108074
Previously we emitted a "does not support scalable vectors"
remark for all targets whenever vectorisation is attempted. This
pollutes the output for architectures that don't support scalable
vectors and is likely confusing to the user.
Instead this patch introduces a debug message that reports when
scalable vectorisation is allowed by the target and only issues
the previous remark when scalable vectorisation is specifically
requested, for example:
#pragma clang loop vectorize_width(2, scalable)
Differential Revision: https://reviews.llvm.org/D108028
I have added RUN lines to both:
Transforms/LoopVectorize/AArch64/strict-fadd.ll
Transforms/LoopVectorize/AArch64/scalable-strict-fadd.ll
to show the default behaviour is to not vectorise when the following
flag is unset:
-force-ordered-reductions
This patch updates ConstantVector::getSplat to use poison instead
of undef when using insertelement/shufflevector to splat.
This follows on from D93793.
Differential Revision: https://reviews.llvm.org/D107751
Teach LV to use masked-store to support interleave-store-group with
gaps (instead of scatters/scalarization).
The symmetric case of using masked-load to support
interleaved-load-group with gaps was introduced a while ago, by
https://reviews.llvm.org/D53668; This patch completes the store-scenario
leftover from D53668, and solves PR50566.
Reviewed by: Ayal Zaks
Differential Revision: https://reviews.llvm.org/D104750
This patch adds more instructions to the Uniforms list, for example certain
intrinsics that are uniform by definition or whose operands are loop invariant.
This list includes:
1. The intrinsics 'experimental.noalias.scope.decl' and 'sideeffect', which
are always uniform by definition.
2. If intrinsics 'lifetime.start', 'lifetime.end' and 'assume' have
loop invariant input operands then these are also uniform too.
Also, in VPRecipeBuilder::handleReplication we check if an instruction is
uniform based purely on whether or not the instruction lives in the Uniforms
list. However, there are certain cases where calls to some intrinsics can
be effectively treated as uniform too. Therefore, we now also treat the
following cases as uniform for scalable vectors:
1. If the 'assume' intrinsic's operand is not loop invariant, then we
are free to treat this as uniform anyway since it's only a performance
hint. We will get the benefit for the first lane.
2. When the input pointers for 'lifetime.start' and 'lifetime.end' are loop
variant then for scalable vectors we assume these still ultimately come
from the broadcast of an alloca. We do not support scalable vectorisation
of loops containing alloca instructions, hence the alloca itself would
be invariant. If the pointer does not come from an alloca then the
intrinsic itself has no effect.
I have updated the assume test for fixed width, since we now treat it
as uniform:
Transforms/LoopVectorize/assume.ll
I've also added new scalable vectorisation tests for other intriniscs:
Transforms/LoopVectorize/scalable-assume.ll
Transforms/LoopVectorize/scalable-lifetime.ll
Transforms/LoopVectorize/scalable-noalias-scope-decl.ll
Differential Revision: https://reviews.llvm.org/D107284
Since all operands to ExtractValue must be loop-invariant when we deem
the loop vectorizable, we can consider ExtractValue to be uniform.
Reviewed By: david-arm
Differential Revision: https://reviews.llvm.org/D107286
This patch adds more instructions to the Uniforms list, for example certain
intrinsics that are uniform by definition or whose operands are loop invariant.
This list includes:
1. The intrinsics 'experimental.noalias.scope.decl' and 'sideeffect', which
are always uniform by definition.
2. If intrinsics 'lifetime.start', 'lifetime.end' and 'assume' have
loop invariant input operands then these are also uniform too.
Also, in VPRecipeBuilder::handleReplication we check if an instruction is
uniform based purely on whether or not the instruction lives in the Uniforms
list. However, there are certain cases where calls to some intrinsics can
be effectively treated as uniform too. Therefore, we now also treat the
following cases as uniform for scalable vectors:
1. If the 'assume' intrinsic's operand is not loop invariant, then we
are free to treat this as uniform anyway since it's only a performance
hint. We will get the benefit for the first lane.
2. When the input pointers for 'lifetime.start' and 'lifetime.end' are loop
variant then for scalable vectors we assume these still ultimately come
from the broadcast of an alloca. We do not support scalable vectorisation
of loops containing alloca instructions, hence the alloca itself would
be invariant. If the pointer does not come from an alloca then the
intrinsic itself has no effect.
I have updated the assume test for fixed width, since we now treat it
as uniform:
Transforms/LoopVectorize/assume.ll
I've also added new scalable vectorisation tests for other intriniscs:
Transforms/LoopVectorize/scalable-assume.ll
Transforms/LoopVectorize/scalable-lifetime.ll
Transforms/LoopVectorize/scalable-noalias-scope-decl.ll
Differential Revision: https://reviews.llvm.org/D107284
The tests previously had lots of unnecessary CHECK lines, where
all we really need to check is the presence (or absence) of the
assume intrinsic and the correct input operands.
Differential Revision: https://reviews.llvm.org/D107157
This change wasn't strictly necessary for D106164 and could be removed.
This patch addresses the post-commit comments from @fhahn on D106164, and
also changes sve-widen-gep.ll to use the same IR test as shown in
pointer-induction.ll.
Reviewed By: fhahn
Differential Revision: https://reviews.llvm.org/D106878
The two tests (@testloopvariant and @testbitcast) are actually
identical as in both loops the bitcast gets widened, forcing the
lifetime marker to be replicated using each lane of the input
vector.
Differential Revision: https://reviews.llvm.org/D107150
I'm renaming the flag because a future patch will add a new
enableOrderedReductions() TTI interface and so the meaning of this
flag will change to be one of forcing the target to enable/disable
them. Also, since other places in LoopVectorize.cpp use the word
'Ordered' instead of 'strict' I changed the flag to match.
Differential Revision: https://reviews.llvm.org/D107264
This patch updates VPInterleaveRecipe::print to print the actual defined
VPValues for load groups and the store VPValue operands for store
groups.
The IR references may become outdated while transforming the VPlan and
the defined and stored VPValues always are up-to-date.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D107223
If a reduction Phi has a single user which `AND`s the Phi with a type mask,
`lookThroughAnd` will return the user of the Phi and the narrower type represented
by the mask. Currently this is only used for arithmetic reductions, whereas loops
containing logical reductions will create a reduction intrinsic using the widened
type, for example:
for.body:
%phi = phi i32 [ %and, %for.body ], [ 255, %entry ]
%mask = and i32 %phi, 255
%gep = getelementptr inbounds i8, i8* %ptr, i32 %iv
%load = load i8, i8* %gep
%ext = zext i8 %load to i32
%and = and i32 %mask, %ext
...
^ this will generate an and reduction intrinsic such as the following:
call i32 @llvm.vector.reduce.and.v8i32(<8 x i32>...)
The same example for an add instruction would create an intrinsic of type i8:
call i8 @llvm.vector.reduce.add.v8i8(<8 x i8>...)
This patch changes AddReductionVar to call lookThroughAnd for other integer
reductions, allowing loops similar to the example above with reductions such
as and, or & xor to vectorize.
Reviewed By: david-arm, dmgreen
Differential Revision: https://reviews.llvm.org/D105632
This makes a couple of changes to the costing of MLA reduction patterns,
to more accurately cost various patterns that can come up from
vectorization.
- The Arm implementation of getExtendedAddReductionCost is altered to
only provide costs for legal or smaller types. Larger than legal types
need to be split, which currently does not work very well, especially
for predicated reductions where the predicate may be legal but needs to
be split. Currently we limit it to legal or smaller input types.
- The getReductionPatternCost has learnt that reduce(ext(mul(ext, ext))
is a pattern that can come up, and can be treated the same as
reduce(mul(ext, ext)) providing the extension types match.
- And it has been adjusted to not count the ext in reduce(mul(ext, ext))
as part of a reduce(mul) pattern.
Together these changes help to more accurately cost the mla reductions
in cases such as where the extend types don't match or the extend
opcodes are different, picking better vector factors that don't result
in expanded reductions.
Differential Revision: https://reviews.llvm.org/D106166
It was writing to the source directory (which may not be writeable),
rather than using %t.
Fixes: a5dd6c6cf9 ("[LoopVectorize] Don't interleave scalar ordered reductions for inner loops")
Consider the following loop:
void foo(float *dst, float *src, int N) {
for (int i = 0; i < N; i++) {
dst[i] = 0.0;
for (int j = 0; j < N; j++) {
dst[i] += src[(i * N) + j];
}
}
}
When we are not building with -Ofast we may attempt to vectorise the
inner loop using ordered reductions instead. In addition we also try
to select an appropriate interleave count for the inner loop. However,
when choosing a VF=1 the inner loop will be scalar and there is existing
code in selectInterleaveCount that limits the interleave count to 2
for reductions due to concerns about increasing the critical path.
For ordered reductions this problem is even worse due to the additional
data dependency, and so I've added code to simply disable interleaving
for scalar ordered reductions for now.
Test added here:
Transforms/LoopVectorize/AArch64/strict-fadd-vf1.ll
Differential Revision: https://reviews.llvm.org/D106646
The Exit instruction passed in for checking if it's an ordered reduction need not be
an FPAdd operation. We need to bail out at that point instead of
assuming it is an FPAdd (and hence has two operands). See added testcase.
It crashes without the patch because the Exit instruction is a phi with
exactly one operand.
This latent bug was exposed by 95346ba which added support for
multi-exit loops for vectorization.
Reviewed-By: kmclaughlin
Differential Revision: https://reviews.llvm.org/D106843
The loop vectorizer may decide to use tail folding when the trip-count
is low. When that happens, scalable VFs are no longer a candidate,
since tail folding/predication is not yet supported for scalable vectors.
This can be re-enabled in a future patch.
Reviewed By: kmclaughlin
Differential Revision: https://reviews.llvm.org/D106657
Before MASSV only supported P8 and P9 on AIX ans Linux . This patch proposes
MASSV to add support of P7 and P10 only on AIX too.
Differential: https://reviews.llvm.org/D106678
Invalid costs can be used to avoid vectorization with a given VF, which is
used for scalable vectors to avoid things that the code-generator cannot
handle. If we override the cost using the -force-target-instruction-cost
option of the LV, we would override this mechanism, rendering the flag useless.
This change ensures the cost is only overriden when the original cost that
was calculated is valid. That allows the flag to be used in combination
with the -scalable-vectorization option.
Reviewed By: david-arm
Differential Revision: https://reviews.llvm.org/D106677
This change moves most of `sve-inductions.ll` to non-AArch64 specific
LV tests using the `-target-supports-scalable-vectors` flag, because they're
not explicitly AArch64-specific. One test builds on AArch64-specific
knowledge regarding masked loads/stores, and remains in sve-inductions.ll.
Scalarization for scalable vectors is not (yet) supported, so the
LV discards a VF when scalarization is chosen as the widening
decision. It should therefore not assert that the VF is not scalable
when it computes the decision to scalarize.
The code can get here when both the interleave-cost, gather/scatter cost
and scalarization-cost are all illegal. This may e.g. happen for SVE
when the VF=1, to avoid generating `<vscale x 1 x eltty>` types that
the code-generator cannot yet handle.
Reviewed By: david-arm
Differential Revision: https://reviews.llvm.org/D106656
This fixes an issue that was found in D105199, where a GEP instruction
is used both as the address of a store, as well as the value of a store.
For the former, the value is scalar after vectorization, but the latter
(as value) requires widening.
Other code in that function seems to prevent similar cases from happening,
but it seems this case was missed.
Reviewed By: david-arm
Differential Revision: https://reviews.llvm.org/D106164
This reverts the revert commit b1777b04dc.
The patch originally got reverted due to a crash:
https://bugs.chromium.org/p/chromium/issues/detail?id=1232798#c2
The underlying issue was that we were not using the stored values from
the modified memory recipes, but the out-of-date values directly from
the IR (accessed via the VPlan). This should be fixed in d995d6376. A
reduced version of the reproducer has been added in 93664503be.
Add folds to instcombine to support the removal of select instruction when the masked_load is guaranteed to zero the same lanes, i.e. select(mask, mload(,,mask,0), 0) -> mload(,,mask,0).
Patch originally authored by @paulwalker-arm
Reviewed By: david-arm
Differential Revision: https://reviews.llvm.org/D106376
I have added a new FastMathFlags parameter to getArithmeticReductionCost
to indicate what type of reduction we are performing:
1. Tree-wise. This is the typical fast-math reduction that involves
continually splitting a vector up into halves and adding each
half together until we get a scalar result. This is the default
behaviour for integers, whereas for floating point we only do this
if reassociation is allowed.
2. Ordered. This now allows us to estimate the cost of performing
a strict vector reduction by treating it as a series of scalar
operations in lane order. This is the case when FP reassociation
is not permitted. For scalable vectors this is more difficult
because at compile time we do not know how many lanes there are,
and so we use the worst case maximum vscale value.
I have also fixed getTypeBasedIntrinsicInstrCost to pass in the
FastMathFlags, which meant fixing up some X86 tests where we always
assumed the vector.reduce.fadd/mul intrinsics were 'fast'.
New tests have been added here:
Analysis/CostModel/AArch64/reduce-fadd.ll
Analysis/CostModel/AArch64/sve-intrinsics.ll
Transforms/LoopVectorize/AArch64/strict-fadd-cost.ll
Transforms/LoopVectorize/AArch64/sve-strict-fadd-cost.ll
Differential Revision: https://reviews.llvm.org/D105432
This patch avoids computing discounts for predicated instructions when the
VF is scalable.
There is no support for vectorization of loops with division because the
vectorizer cannot guarantee that zero divisions will not happen.
This loop now does not use VF scalable
```
for (long long i = 0; i < n; i++)
if (cond[i])
a[i] /= b[i];
```
Differential Revision: https://reviews.llvm.org/D101916
As noticed on D106352, after we've folded "(select C, (gep Ptr, Idx), Ptr) -> (gep Ptr, (select C, Idx, 0))" if the inner Ptr was also a (now one use) gep we could then merge the geps, using the sum of the indices instead.
I've limited this to basic 2-op geps - a more general case further down InstCombinerImpl.visitGetElementPtrInst doesn't have the one-use limitation but only creates the add if it can be created via SimplifyAddInst.
https://alive2.llvm.org/ce/z/f8pLfD (Thanks Roman!)
Differential Revision: https://reviews.llvm.org/D106450
If a reduction Phi has a single user which `AND`s the Phi with a type mask,
`lookThroughAnd` will return the user of the Phi and the narrower type represented
by the mask. Currently this is only used for arithmetic reductions, whereas loops
containing logical reductions will create a reduction intrinsic using the widened
type, for example:
for.body:
%phi = phi i32 [ %and, %for.body ], [ 255, %entry ]
%mask = and i32 %phi, 255
%gep = getelementptr inbounds i8, i8* %ptr, i32 %iv
%load = load i8, i8* %gep
%ext = zext i8 %load to i32
%and = and i32 %mask, %ext
...
^ this will generate an and reduction intrinsic such as the following:
call i32 @llvm.vector.reduce.and.v8i32(<8 x i32>...)
The same example for an add instruction would create an intrinsic of type i8:
call i8 @llvm.vector.reduce.add.v8i8(<8 x i8>...)
This patch changes AddReductionVar to call lookThroughAnd for other integer
reductions, allowing loops similar to the example above with reductions such
as and, or & xor to vectorize.
Reviewed By: david-arm, dmgreen
Differential Revision: https://reviews.llvm.org/D105632
This patch adds a VPFirstOrderRecurrencePHIRecipe, to further untangle
VPWidenPHIRecipe into distinct recipes for distinct use cases/lowering.
See D104989 for a new recipe for reduction phis.
This patch also introduces a new `FirstOrderRecurrenceSplice`
VPInstruction opcode, which is used to make the forming of the vector
recurrence value explicit in VPlan. This more accurately models def-uses
in VPlan and also simplifies code-generation. Now, the vector recurrence
values are created at the right place during VPlan-codegeneration,
rather than during post-VPlan fixups.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D105008
This fixes the lower and upper bound calculation of a
RuntimeCheckingPtrGroup when it has more than one loop
invariant pointers. Resolves PR50686.
Reviewed By: fhahn
Differential Revision: https://reviews.llvm.org/D104148
This patch returns an Invalid cost from getInstructionCost() for alloca
instructions if the VF is scalable, as otherwise loops which contain
these instructions will crash when attempting to scalarize the alloca.
Reviewed By: sdesmalen
Differential Revision: https://reviews.llvm.org/D105824
The original patch was:
https://reviews.llvm.org/D105806
There were some issues with undeterministic behaviour of the sorting
function, which led to scalable-call.ll passing and/or failing. This
patch fixes the issue by numbering all instructions in the array first,
and using that number as the order, which should provide a consistent
ordering.
This reverts commit a607f64118.
This change enables vectorization of multiple exit loops when the exit count is statically computable. That requirement - shared with the rest of LV - in turn requires each exit to be analyzeable and to dominate the latch.
The majority of work to support this was done in a set of previous patches. In particular,, 72314466 avoids having multiple edges from the middle block to the exits, and 4b33b2387 which added support for non-latch single exit and multiple exits with a single exiting block. As a result, this change is basically just removing a bailout and adjusting some tests now that the prerequisite work is done and has stuck in tree for a bit.
Differential Revision: https://reviews.llvm.org/D105817
The sort function for emitting an OptRemark was not deterministic,
which caused scalable-call.ll to fail on some buildbots. This patch
fixes that.
This patch also fixes an issue where `Instruction::comesBefore()`
is called when two Instructions are in different basic blocks,
which would otherwise cause an assertion failure.
This patch emits remarks for instructions that have invalid costs for
a given set of vectorization factors. Some example output:
t.c:4:19: remark: Instruction with invalid costs prevented vectorization at VF=(vscale x 1): load
dst[i] = sinf(src[i]);
^
t.c:4:14: remark: Instruction with invalid costs prevented vectorization at VF=(vscale x 1, vscale x 2, vscale x 4): call to llvm.sin.f32
dst[i] = sinf(src[i]);
^
t.c:4:12: remark: Instruction with invalid costs prevented vectorization at VF=(vscale x 1): store
dst[i] = sinf(src[i]);
^
Reviewed By: fhahn, kmclaughlin
Differential Revision: https://reviews.llvm.org/D105806
At the moment, <vscale x 1 x eltty> are not yet fully handled by the
code-generator, so to avoid vectorizing loops with that VF, we mark the
cost for these types as invalid.
The reason for not adding a new "TTI::getMinimumScalableVF" is because
the type is supposed to be a type that can be legalized. It partially is,
although the support for these types need some more work.
Reviewed By: paulwalker-arm, dmgreen
Differential Revision: https://reviews.llvm.org/D103882
Update (mainly) vXf32/vXf64 -> vXi8/vXi16 fptosi/fptoui costs based on the worst case costs from the script in D103695.
Move to using legalized types wherever possible, which allows us to prune the cost tables.
Revived D101297 in its original form + added some changes in X86
legalization cehcking for masked gathers.
This solution is the most stable and the most correct one. We have to
check the legality before trying to build the masked gather in SLP.
Without this check we have incorrect cost (for SLP) in case if the masked gather
is not legal/slower than the gather. And we're missing some
vectorization opportunities.
This can be fixed in the cost model, but in this case we need to add
special checks for the cost of GEPs for ScatterVectorize node, add
special check for small trees, etc., i.e. there are a lot of corner
cases here and there, which insrease code base and make it harder to
maintain the code.
> Can't we rely on cost model to deal with this? This can be profitable for futher vectorization, when we can start from such gather loads as seed.
The question from D101297. Actually, no, it can't. Actually, simple
gather may give us better result, especially after we started
vectorization of insertelements. Plus, like I said before, the cost for
non-legal masked gathers leads to missed vectorization opportunities.
Differential Revision: https://reviews.llvm.org/D105042
Resubmit after the following changes:
* Fix a latent bug related to unrolling with required epilogue (see e49d65f). I believe this is the cause of the prior PPC buildbot failure.
* Disable non-latch exits for epilogue vectorization to be safe (9ffa90d)
* Split out assert movement (600624a) to reduce churn if this gets reverted again.
Previous commit message (try 3)
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 reverts commit 706bbfb35b.
The committed version moves the definition of VPReductionPHIRecipe out
of an ifdef only intended for ::print helpers. This should resolve the
build failures that caused the revert
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
This reverts commit 3fed6d443f,
bbcbf21ae6 and
6c3451cd76.
The changes causing build failures with certain configurations, e.g.
https://lab.llvm.org/buildbot/#/builders/67/builds/3365/steps/6/logs/stdio
lib/libLLVMVectorize.a(LoopVectorize.cpp.o): In function `llvm::VPRecipeBuilder::tryToCreateWidenRecipe(llvm::Instruction*, llvm::ArrayRef<llvm::VPValue*>, llvm::VFRange&, std::unique_ptr<llvm::VPlan, std::default_delete<llvm::VPlan> >&) [clone .localalias.8]':
LoopVectorize.cpp:(.text._ZN4llvm15VPRecipeBuilder22tryToCreateWidenRecipeEPNS_11InstructionENS_8ArrayRefIPNS_7VPValueEEERNS_7VFRangeERSt10unique_ptrINS_5VPlanESt14default_deleteISA_EE+0x63b): undefined reference to `vtable for llvm::VPReductionPHIRecipe'
collect2: error: ld returned 1 exit status
This patch is a first step towards splitting up VPWidenPHIRecipe into
separate recipes for the 3 distinct cases they model:
1. reduction phis,
2. first-order recurrence phis,
3. pointer induction phis.
This allows untangling the code generation and allows us to reduce the
reliance on LoopVectorizationCostModel during VPlan code generation.
Discussed/suggested in D100102, D100113, D104197.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D104989
Loads of <4 x i8> vectors were modeled as extremely expensive. And while we
don't have a load instruction that supports this, it isn't that expensive to
create a vector of i8 elements. The codegen for this was fixed/optimised in
D105110. This now tweaks the cost model and enables SLP vectorisation of my
motivating case loadi8.ll.
Differential Revision: https://reviews.llvm.org/D103629
Update v4i64 -> v4f32/v4f64 uitofp costs based on the worst case costs from the script in D103695.
Fixes a few regressions before we start adding AVX costs for legalized types.
If we unroll a loop in the vectorizer (without vectorizing), and the cost model requires a epilogue be generated for correctness, the code generation must actually do so.
The included test case on an unmodified opt will access memory one past the expected bound. As a result, this patch is fixing a latent miscompile.
Differential Revision: https://reviews.llvm.org/D103700
This patch fixes a crash when the target instruction for sinking is
dead. In that case, no recipe is created and trying to get the recipe
for it results in a crash. To ensure all sink targets are alive, find &
use the first previous alive instruction.
Note that the case where the sink source is dead is already handled.
Found by
https://bugs.chromium.org/p/oss-fuzz/issues/detail?id=35320
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D104603
Previously in setCostBasedWideningDecision if we encountered an
invariant store we just assumed that we could scalarize the store
and called getUniformMemOpCost to get the associated cost.
However, for scalable vectors this is not an option because it is
not currently possibly to scalarize the store. At the moment we
crash in VPReplicateRecipe::execute when trying to scalarize the
store.
Therefore, I have changed setCostBasedWideningDecision so that if
we are storing a scalable vector out to a uniform address and the
target supports scatter instructions, then we should use those
instead.
Tests have been added here:
Transforms/LoopVectorize/AArch64/sve-inv-store.ll
Differential Revision: https://reviews.llvm.org/D104624
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
A backedge-taken count doesn't refer to memory; returning a pointer type
is nonsense. So make sure we always return an integer.
The obvious way to do this would be to just convert the operands of the
icmp to integers, but that doesn't quite work out at the moment:
isLoopEntryGuardedByCond currently gets confused by ptrtoint operations.
So we perform the ptrtoint conversion late for lt/gt operations.
The test changes are mostly innocuous. The most interesting changes are
more complex SCEV expressions of the form "(-1 * (ptrtoint i8* %ptr to
i64)) + %ptr)". This is expected: we can't fold this to zero because we
need to preserve the pointer base.
The call to isLoopEntryGuardedByCond in howFarToZero is less precise
because of ptrtoint operations; this shows up in the function
pr46786_c26_char in ptrtoint.ll. Fixing it here would require more
complex refactoring. It should eventually be fixed by future
improvements to isImpliedCond.
See https://bugs.llvm.org/show_bug.cgi?id=46786 for context.
Differential Revision: https://reviews.llvm.org/D103656
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 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
Fixes getTypeConversion to return `TypeScalarizeScalableVector` when a scalable vector
type cannot be legalized by widening/splitting. When this is the method of legalization
found, getTypeLegalizationCost will return an Invalid cost.
The getMemoryOpCost, getMaskedMemoryOpCost & getGatherScatterOpCost functions already call
getTypeLegalizationCost and will now also return an Invalid cost for unsupported types.
Reviewed By: sdesmalen, david-arm
Differential Revision: https://reviews.llvm.org/D102515
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
Noticed via code inspection. We changed the semantics of the IR when we added mustprogress, and we appear to have not updated this location.
Differential Revision: https://reviews.llvm.org/D103834
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
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
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
This is a patch that replaces shufflevector and insertelement's placeholder value with poison.
Underlying motivation is to fix the semantics of shufflevector with undef mask to return poison instead
(D93818)
The consensus has been made in the late 2020 via mailing list as well as the thread in https://bugs.llvm.org/show_bug.cgi?id=44185 .
This patch is a simple syntactic change to the existing code, hence directly pushed as a commit.
This reverts commit 1ed7f8ede5.
This change can cause loop-distribute to crash in some cases. Revert
until I have more time to wrap up a fix.
See PR50296, PR5028 and D102266.
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.
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
An additional RUN line has been added to both strict-fadd.ll &
scalable-strict-fadd.ll to ensure the correct behaviour of these
tests where `-enable-strict-reductions` is false.
Reviewed By: david-arm
Differential Revision: https://reviews.llvm.org/D103015
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
* Removes unnecessary loop hints.
* Use RUN line with '-scalable-vectorization=preferred' instead of 'on'
for the maximize-bandwidth behaviour. This prepares the test for enabling
scalable vectorization; With a forced instruction-cost of 1, 'on' will
always favour fixed-width VF to be chosen, whereas with 'preferred'
we can check that the maximize-bandwidth option in combination with
scalable-vectorization=preferred actually picks a scalable VF.
* Renamed to scalable-vectorization.ll, because a follow-up patch will
test more than just analysis.
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 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
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
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.
This patch adds support for Darwin's libsystem math vector functions to
TLI. Darwin's libsystem provides a range of vector functions for libm
functions.
This initial patch only adds the 2 x double and 4 x float versions,
which are available on both X86 and ARM64. On X86, wider vector versions
are supported as well.
Reviewed By: jroelofs
Differential Revision: https://reviews.llvm.org/D101856
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
This is a patch that disables the poison-unsafe select -> and/or i1 folding.
It has been blocking D72396 and also has been the source of a few miscompilations
described in llvm.org/pr49688 .
D99674 conditionally blocked this folding and successfully fixed the latter one.
The former one was still blocked, and this patch addresses it.
Note that a few test functions that has `_logical` suffix are now deoptimized.
These are created by @nikic to check the impact of disabling this optimization
by copying existing original functions and replacing and/or with select.
I can see that most of these are poison-unsafe; they can be revived by introducing
freeze instruction. I left comments at fcmp + select optimizations (or-fcmp.ll, and-fcmp.ll)
because I think they are good targets for freeze fix.
Reviewed By: nikic
Differential Revision: https://reviews.llvm.org/D101191
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
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
SCEV does not look through non-header PHIs inside the loop. Such phis
can be analyzed by adding separate accesses for each incoming pointer
value.
This results in 2 more loops vectorized in SPEC2000/186.crafty and
avoids regressions when sinking instructions before vectorizing.
Reviewed By: Meinersbur
Differential Revision: https://reviews.llvm.org/D101286
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
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
We can already vectorize loops that involve int<>int, fp<>fp, int<>fp
and fp<>int conversions, however we didn't previously have any tests
for them. This patch adds some tests for each conversion type.
Differential Revision: https://reviews.llvm.org/D99951
When vectorising for AArch64 targets if you specify the SVE attribute
we automatically then treat masked loads and stores as legal. Also,
since we have no cost model for masked memory ops we believe it's
cheap to use the masked load/store intrinsics even for fixed width
vectors. This can lead to poor code quality as the intrinsics will
currently be scalarised in the backend. This patch adds a basic
cost model that marks fixed-width masked memory ops as significantly
more expensive than for scalable vectors.
Tests for the cost model are added here:
Transforms/LoopVectorize/AArch64/masked-op-cost.ll
Differential Revision: https://reviews.llvm.org/D100745
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
Introduced the cost of thre reverse shuffles for AArch64, currently just
copied the costs for PermuteSingleSrc.
Differential Revision: https://reviews.llvm.org/D100871
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
This is similar to the subvector extractions,
except that the 0'th subvector isn't free to insert,
because we generally don't know whether or not
the upper elements need to be preserved:
https://godbolt.org/z/rsxP5W4sW
This is needed to avoid regressions in D100684
Reviewed By: RKSimon
Differential Revision: https://reviews.llvm.org/D100698
D98435 added support for in-order reductions and included tests for fixed-width
vectorization with the -enable-strict-reductions flag.
This patch adds similar tests to verify support for scalable vectorization of loops
with in-order reductions.
Reviewed By: david-arm
Differential Revision: https://reviews.llvm.org/D100385
This patch clarifies the semantics of the nofree function attribute to make clear that it provides an "as if" semantic. That is, a nofree function is guaranteed not to free memory which existed before the call, but might allocate and then deallocate that same memory within the lifetime of the callee.
This is the result of the discussion on llvm-dev under the thread "Ambiguity in the nofree function attribute".
The most important part of this change is the LangRef wording. The rest is minor comment changes to emphasize the new semantics where code was accidentally consistent, and fix one place which wasn't consistent. That one place is currently narrowly used as it is primarily part of the ongoing (and not yet enabled) deref-at-point semantics work.
Differential Revision: https://reviews.llvm.org/D100141
This also fixes a CHECK line in @fadd_strict_unroll which ensures the
changes made to fixReduction() to support in-order reductions with
unrolling are being tested correctly.
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
LLVM test Transforms/LoopVectorize/pr34681.ll tries to check for the
absence of a sequence of instructions with several CHECK-NOT with one of
those directives using a variable defined in another. However CHECK-NOT
are checked independently so that is using a variable defined in a
pattern that should not occur in the input.
This commit only checks for the absence of icmp ne 1 which rules out the
presence of the whole sequence and does not involve an undefined
variable.
Reviewed By: fhahn
Differential Revision: https://reviews.llvm.org/D99582
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
After D98856 these tests will by default break (fatal_error) if any of
the wrong interfaces are used, so there's no longer a need to have a
RUN line that checks for a warning message emitted by the compiler.
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
Changes getRecurrenceIdentity to always return a neutral value of -0.0 for FAdd.
Reviewed By: dmgreen, spatel
Differential Revision: https://reviews.llvm.org/D98963
We can't see how much overhead/redundancy is being
created with the partial checks.
To make it smaller and easier to read, I reduced the
vectorization factor because that does not add new
information - it just duplicates things.
Support deriving dereferenceability facts from allocation sites with known object sizes while correctly accounting for any possibly frees between allocation and use site. (At the moment, we're conservative and only allowing it in functions where we know we can't free.)
This is part of the work on deref-at-point semantics. I'm making the change unconditional as the miscompile in this case is way too easy to trip by accident, and the optimization was only recently added (by me).
There will be a follow up patch wiring through TLI since that should now be doable without introducing widespread miscompiles.
Differential Revision: https://reviews.llvm.org/D95815
This patch just adds tests that we can vectorize loop such as these:
for (i = 0; i < n; i++)
dst[i * 7] += 1;
and
for (i = 0; i < n; i++)
if (cond[i])
dst[i * 7] += 1;
using scalable vectors, where we expect to use gathers and scatters in the
vectorized loop. The vector of pointers used for the gather is identical
to those used for the scatter so there should be no memory dependences.
Tests are added here:
Transforms/LoopVectorize/AArch64/sve-large-strides.ll
Differential Revision: https://reviews.llvm.org/D99192
This marks FSIN and other operations to EXPAND for scalable
vectors, so that they are not assumed to be legal by the cost-model.
Depends on D97470
Reviewed By: dmgreen, paulwalker-arm
Differential Revision: https://reviews.llvm.org/D97471
LLVM test Transforms/LoopVectorize/X86/x86-pr39099.ll tries to check for
the absence of a sequence of instructions with several CHECK-NOT with
one of those directives using a variable defined in another. However
CHECK-NOT are checked independently so that is using a variable defined
in a pattern that should not occur in the input.
This commit only checks for the absence of a widened load which rules
out the presence of the whole sequence and does not involve an undefined
variable.
Reviewed By: fhahn
Differential Revision: https://reviews.llvm.org/D99583
This patch adds support for the vectorization of induction variables when
using scalable vectors, which required the following changes:
1. Removed assert from InnerLoopVectorizer::getStepVector.
2. Modified InnerLoopVectorizer::createVectorIntOrFpInductionPHI to use
a runtime determined value for VF and removed an assert.
3. Modified InnerLoopVectorizer::buildScalarSteps to work for scalable
vectors. I did this by calculating the full vector value for each Part
of the unroll factor (UF) and caching this in the VP state. This means
that we are always able to extract an arbitrary element from the vector
if necessary. In addition to this, I also permitted the caching of the
individual lane values themselves for the known minimum number of elements
in the same way we do for fixed width vectors. This is a further
optimisation that improves the code quality since it avoids unnecessary
extractelement operations when extracting the first lane.
4. Added an assert to InnerLoopVectorizer::widenPHIInstruction, since while
testing some code paths I noticed this is currently broken for scalable
vectors.
Various tests to support different cases have been added here:
Transforms/LoopVectorize/AArch64/sve-inductions.ll
Differential Revision: https://reviews.llvm.org/D98715
Re-apply 25fbe803d4, with a small update to emit the right remark
class.
Original message:
[LV] Move runtime pointer size check to LVP::plan().
This removes the need for the remaining doesNotMeet check and instead
directly checks if there are too many runtime checks for vectorization
in the planner.
A subsequent patch will adjust the logic used to decide whether to
vectorize with runtime to consider their cost more accurately.
Reviewed By: lebedev.ri
This removes the need for the remaining doesNotMeet check and instead
directly checks if there are too many runtime checks for vectorization
in the planner.
A subsequent patch will adjust the logic used to decide whether to
vectorize with runtime to consider their cost more accurately.
Reviewed By: lebedev.ri
Differential Revision: https://reviews.llvm.org/D98634
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 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. 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.
Differential Revision: https://reviews.llvm.org/D98512
D95598 added a cost model for broadcast shuffle, which should enable loops
such as the following to vectorize, where the load of b[42] is invariant
and can be done using a scalar load + splat:
for (int i=0; i<n; ++i)
a[i] = b[i] + b[42];
This patch adds tests to verify that we can vectorize such loops.
Reviewed By: joechrisellis
Differential Revision: https://reviews.llvm.org/D98506
The name is included when printing in DOT mode. Also print it in non-DOT
mode after 93a9d2de8f.
This will become more important to distinguish different plans once
VPlans are gradually refined.
The scalarization overhead was set deliberately high for MVE, whilst the
codegen was new. It helps protect us against the negative ramifications
of mixing scalar and vector instructions. This decreases that,
especially for floating point where the cost of extracting/inserting
lane elements can be low. For integer the cost is still fairly high due
to the cross-register-bank copy, but is no longer n^2 in the length of
the vector.
In general, this will decrease the cost of scalarizing floats and long
integer vectors. i64 increase in cost, having a high cost before and
after this patch. For floats this allows up to start doing things like
vectorizing fdiv instructions, even if they are scalarized.
Differential Revision: https://reviews.llvm.org/D98245
I foresee two uses for this:
1) It's easier to use those in debugger.
2) Once we start implementing more VPlan-to-VPlan transformations (especially
inner loop massaging stuff), using the vectorized LLVM IR as CHECK targets in
LIT test would become too obscure. I can imagine that we'd want to CHECK
against VPlan dumps after multiple transformations instead. That would be
easier with plain text dumps than with DOT format.
Reviewed By: fhahn
Differential Revision: https://reviews.llvm.org/D96628
This patch adds support for intrinsic overloading on unnamed types.
This fixes PR38117 and PR48340 and will also be needed for the Full Restrict Patches (D68484).
The main problem is that the intrinsic overloading name mangling is using 's_s' for unnamed types.
This can result in identical intrinsic mangled names for different function prototypes.
This patch changes this by adding a '.XXXXX' to the intrinsic mangled name when at least one of the types is based on an unnamed type, ensuring that we get a unique name.
Implementation details:
- The mapping is created on demand and kept in Module.
- It also checks for existing clashes and recycles potentially existing prototypes and declarations.
- Because of extra data in Module, Intrinsic::getName needs an extra Module* argument and, for speed, an optional FunctionType* argument.
- I still kept the original two-argument 'Intrinsic::getName' around which keeps the original behavior (providing the base name).
-- Main reason is that I did not want to change the LLVMIntrinsicGetName version, as I don't know how acceptable such a change is
-- The current situation already has a limitation. So that should not get worse with this patch.
- Intrinsic::getDeclaration and the verifier are now using the new version.
Other notes:
- As far as I see, this should not suffer from stability issues. The count is only added for prototypes depending on at least one anonymous struct
- The initial count starts from 0 for each intrinsic mangled name.
- In case of name clashes, existing prototypes are remembered and reused when that makes sense.
Reviewed By: fhahn
Differential Revision: https://reviews.llvm.org/D91250
This reverts commit 6b053c9867.
The build is broken:
ld.lld: error: undefined symbol: llvm::VPlan::printDOT(llvm::raw_ostream&) const
>>> referenced by LoopVectorize.cpp
>>> LoopVectorize.cpp.o:(llvm::LoopVectorizationPlanner::printPlans(llvm::raw_ostream&)) in archive lib/libLLVMVectorize.a
I foresee two uses for this:
1) It's easier to use those in debugger.
2) Once we start implementing more VPlan-to-VPlan transformations (especially
inner loop massaging stuff), using the vectorized LLVM IR as CHECK targets in
LIT test would become too obscure. I can imagine that we'd want to CHECK
against VPlan dumps after multiple transformations instead. That would be
easier with plain text dumps than with DOT format.
Reviewed By: fhahn
Differential Revision: https://reviews.llvm.org/D96628
This makes the induction part of the loop vectorizer match the reduction part.
We do not need all of the fast-math-flags. For example, there are some that
clearly are not in play like arcp or afn.
If we want to make FMF constraints consistent across the IR optimizer, we
might want to add nsz too, but that's up for debate (users can't expect
associative FP math and preservation of sign-of-zero at the same time?).
The calling code was fixed to avoid miscompiles with:
1bee549737
Differential Revision: https://reviews.llvm.org/D98708
The `hasIrregularType` predicate checks whether an array of N values of type Ty is "bitcast-compatible" with a <N x Ty> vector.
The previous check returned invalid results in some cases where there's some padding between the array elements: eg. a 4-element array of u7 values is considered as compatible with <4 x u7>, even though the vector is only loading/storing 28 bits instead of 32.
The problem causes LLVM to generate incorrect code for some targets: for AArch64 the vector loads/stores are lowered in terms of ubfx/bfi, effectively losing the top (N * padding bits).
Reviewed By: lebedev.ri
Differential Revision: https://reviews.llvm.org/D97465
This adds the cost of an i1 extract and a branch to the cost in
getMemInstScalarizationCost when the instruction is predicated. These
predicated loads/store would generate blocks of something like:
%c1 = extractelement <4 x i1> %C, i32 1
br i1 %c1, label %if, label %else
if:
%sa = extractelement <4 x i32> %a, i32 1
%sb = getelementptr inbounds float, float* %pg, i32 %sa
%sv = extractelement <4 x float> %x, i32 1
store float %sa, float* %sb, align 4
else:
So this increases the cost by the extract and branch. This is probably
still too low in many cases due to the cost of all that branching, but
there is already an existing hack increasing the cost using
useEmulatedMaskMemRefHack. It will increase the cost of a memop if it is
a load or there are more than one store. This patch improves the cost
for when there is only a single store, and hopefully at some point in
the future the hack can be removed.
Differential Revision: https://reviews.llvm.org/D98243
This patch adds support for reverse loop vectorization.
It is possible to vectorize the following loop:
```
for (int i = n-1; i >= 0; --i)
a[i] = b[i] + 1.0;
```
with fixed or scalable vector.
The loop-vectorizer will use 'reverse' on the loads/stores to make
sure the lanes themselves are also handled in the right order.
This patch adds support for scalable vector on IRBuilder interface to
create a reverse vector. The IR function
CreateVectorReverse lowers to experimental.vector.reverse for scalable vector
and keedp the original behavior for fixed vector using shuffle reverse.
Differential Revision: https://reviews.llvm.org/D95363
This reverts commit 329aeb5db4,
and relands commit 61f006ac65.
This is a continuation of D89456.
As it was suggested there, now that SCEV models `PtrToInt`,
we can try to improve SCEV's pointer handling.
In particular, i believe, i will need this in the future
to further fix `SCEVAddExpr`operation type handling.
This removes special handling of `ConstantPointerNull`
from `ScalarEvolution::createSCEV()`, and add constant folding
into `ScalarEvolution::getPtrToIntExpr()`.
This way, `null` constants stay as such in SCEV's,
but gracefully become zero integers when asked.
Reviewed By: Meinersbur
Differential Revision: https://reviews.llvm.org/D98147
This is a continuation of D89456.
As it was suggested there, now that SCEV models `PtrToInt`,
we can try to improve SCEV's pointer handling.
In particular, i believe, i will need this in the future
to further fix `SCEVAddExpr`operation type handling.
This removes special handling of `ConstantPointerNull`
from `ScalarEvolution::createSCEV()`, and add constant folding
into `ScalarEvolution::getPtrToIntExpr()`.
This way, `null` constants stay as such in SCEV's,
but gracefully become zero integers when asked.
Reviewed By: Meinersbur
Differential Revision: https://reviews.llvm.org/D98147
This patch fixes a crash when trying to get a scalar value using
VPTransformState::get() for uniform induction values or truncated
induction values. IVs and truncated IVs can be uniform and the updated
code accounts for that, fixing the crash.
This should fix
https://bugs.chromium.org/p/oss-fuzz/issues/detail?id=31981
Add support to widen select instructions in VPlan native path by using a correct recipe when such instructions are encountered. This is already used by inner loop vectorizer.
Previously select instructions get handled by the wrong recipe and resulted in unreachable instruction errors like this one: https://bugs.llvm.org/show_bug.cgi?id=48139.
Reviewed By: fhahn
Differential Revision: https://reviews.llvm.org/D97136
This test shows a case where we can potentially scalarize the store in a
predicated loop, creating a lot of instructions that would be much
slower than scalar.
Since P8 is the oldest machine supported by MASSV pass,
_massv place holder is removed and the oldest version of
MASSV functions is assumed. If the P9 vector specific is
detected in the compilation process, the P8 prefix will
be updated to P9.
Differential Revision: https://reviews.llvm.org/D98064
For loops of the form:
void foo(int *a, int *cond, short *inv, long long n) {
for (long long i=0; i<n; ++i) {
if (cond[i])
a[i] = *inv;
}
}
we can vectorise for SVE using masked gather loads where the array
of pointers is simply a vector splat of 'inv' and the mask comes
from the condition 'cond[i] != 0'.
This patch simply adds tests upstream to defend this capability.
Differential Revision: https://reviews.llvm.org/D98043
Add support to widen call instructions in VPlan native path by using a correct recipe when such instructions are encountered. This is already used by inner loop vectorizer.
Previously call instructions got handled by wrong recipes and resulted in unreachable instruction errors like this one: https://bugs.llvm.org/show_bug.cgi?id=48139.
Patch by Mauri Mustonen <mauri.mustonen@tuni.fi>
Reviewed By: fhahn
Differential Revision: https://reviews.llvm.org/D97278
These intrinsics, not the icmp+select are the canonical form nowadays,
so we might as well directly emit them.
This should not cause any regressions, but if it does,
then then they would needed to be fixed regardless.
Note that this doesn't deal with `SCEVExpander::isHighCostExpansion()`,
but that is a pessimization, not a correctness issue.
Additionally, the non-intrinsic form has issues with undef,
see https://reviews.llvm.org/D88287#2587863
There are certain loops like this below:
for (int i = 0; i < n; i++) {
a[i] = b[i] + 1;
*inv = a[i];
}
that can only be vectorised if we are able to extract the last lane of the
vectorised form of 'a[i]'. For fixed width vectors this already works since
we know at compile time what the final lane is, however for scalable vectors
this is a different story. This patch adds support for extracting the last
lane from a scalable vector using a runtime determined lane value. I have
added support to VPIteration for runtime-determined lanes that still permit
the caching of values. I did this by introducing a new class called VPLane,
which describes the lane we're dealing with and provides interfaces to get
both the compile-time known lane and the runtime determined value. Whilst
doing this work I couldn't find any explicit tests for extracting the last
lane values of fixed width vectors so I added tests for both scalable and
fixed width vectors.
Differential Revision: https://reviews.llvm.org/D95139
By implementing the method "unsigned RISCVTTIImpl::getRegisterBitWidth(bool Vector)",
fixed-length vectorization is enabled when possible. Without this method, the
"#pragma clang loop" directive is needed to enable vectorization(or the cost model
may inform LLVM that "Vectorization is possible but not beneficial").
Reviewed By: frasercrmck
Differential Revision: https://reviews.llvm.org/D97549
This code assumed that FP math was only permissable if it was
fully "fast", so it hard-coded "fast" when creating new instructions.
The underlying code already allows matching recurrences/reductions
that are only "reassoc", so this change should prevent the potential
miscompile seen in the test diffs (we created "fast" ops even though
none existed in the original code).
I don't know if we need to create the temporary IRBuilder objects
used here, so that could be follow-up clean-up.
There's an open question about whether we should require "nsz" in
addition to "reassoc" here. InstCombine uses that combo for its
reassociative folds, but I think codegen is not as strict.
Similar to b3a33553ae, but this shows a TODO and a potential
miscompile is already present.
We are tracking an FP instruction that does *not* have FMF (reassoc)
properties, so calling that "Unsafe" seems opposite of the common
reading.
I also removed one getter method by rolling the null check into
the access. Further simplification may be possible.
The motivation is to clean up the interactions between FMF and
function-level attributes in these classes and their callers.
The new test shows that there is an existing bug somewhere in
the callers. We assumed that the original code was fully 'fast'
and so we produced IR with 'fast' even though it was just 'reassoc'.
Under -O3 and -Ofast, the MASSV conversion prevents the sqrt call to be inlined.
Inline sqrt is faster than MASSV call on leppc.
Differential Revision: https://reviews.llvm.org/D97487
This patch updates LV to generate the runtime checks just after cost
modeling, to allow a more precise estimate of the actual cost of the
checks. This information will be used in future patches to generate
larger runtime checks in cases where the checks only make up a small
fraction of the expected scalar loop execution time.
The runtime checks are created up-front in a temporary block to allow better
estimating the cost and un-linked from the existing IR. After deciding to
vectorize, the checks are moved backed. If deciding not to vectorize, the
temporary block is completely removed.
This patch is similar in spirit to D71053, but explores a different
direction: instead of delaying the decision on whether to vectorize in
the presence of runtime checks it instead optimistically creates the
runtime checks early and discards them later if decided to not
vectorize. This has the advantage that the cost-modeling decisions
can be kept together and can be done up-front and thus preserving the
general code structure. I think delaying (part) of the decision to
vectorize would also make the VPlan migration a bit harder.
One potential drawback of this patch is that we speculatively
generate IR which we might have to clean up later. However it seems like
the code required to do so is quite manageable.
Reviewed By: lebedev.ri, ebrevnov
Differential Revision: https://reviews.llvm.org/D75980
This reverts the revert commit 437f0bbcd5.
It adds a new toVPRecipeResult, which forces VPRecipeOrVPValueTy to be
constructed with a VPRecipeBase *. This should address ambiguous
constructor issues for recipe sub-types that also inherit from VPValue.
Generalize the return value of tryToCreateWidenRecipe to return either a
newly create recipe or an existing VPValue. Use this to avoid creating
unnecessary VPBlendRecipes.
Fixes PR44800.
As a followup to D95291, getOperandsScalarizationOverhead was still
using a VF as a vector factor if the arguments were scalar, and would
assert on certain matrix intrinsics with differently sized vector
arguments. This patch removes the VF arg, instead passing the Types
through directly. This should allow it to more accurately compute the
cost without having to guess at which operands will be vectorized,
something difficult with more complex intrinsics.
This adjusts one SVE test as it is now calling the wrong intrinsic vs
veccall. Without invalid InstructCosts the cost of the scalarized
intrinsic is too low. This should get fixed when the cost of
scalarization is accounted for with scalable types.
Differential Revision: https://reviews.llvm.org/D96287
getIntrinsicInstrCost takes a IntrinsicCostAttributes holding various
parameters of the intrinsic being costed. It can either be called with a
scalar intrinsic (RetTy==Scalar, VF==1), with a vector instruction
(RetTy==Vector, VF==1) or from the vectorizer with a scalar type and
vector width (RetTy==Scalar, VF>1). A RetTy==Vector, VF>1 is considered
an error. Both of the vector modes are expected to be treated the same,
but because this is confusing many backends end up getting it wrong.
Instead of trying work with those two values separately this removes the
VF parameter, widening the RetTy/ArgTys by VF used called from the
vectorizer. This keeps things simpler, but does require some other
modifications to keep things consistent.
Most backends look like this will be an improvement (or were not using
getIntrinsicInstrCost). AMDGPU needed the most changes to keep the code
from c230965ccf working. ARM removed the fix in
dfac521da1, webassembly happens to get a fixup for an SLP cost
issue and both X86 and AArch64 seem to now be using better costs from
the vectorizer.
Differential Revision: https://reviews.llvm.org/D95291
This patch extends VPWidenPHIRecipe to manage pairs of incoming
(VPValue, VPBasicBlock) in the VPlan native path. This is made possible
because we now directly manage defined VPValues for recipes.
By keeping both the incoming value and block in the recipe directly,
code-generation in the VPlan native path becomes independent of the
predecessor ordering when fixing up non-induction phis, which currently
can cause crashes in the VPlan native path.
This fixes PR45958.
Reviewed By: sguggill
Differential Revision: https://reviews.llvm.org/D96773
This is a fix for https://llvm.org/PR49215 either before/after
we make a verifier enhancement for vector reductions with D96904.
I'm not sure what the current thinking is for pointer math/logic
in IR. We allow icmp on pointer values. Therefore, we match min/max
patterns, so without this patch, the vectorizer could form a vector
reduction from that sequence.
But the LangRef definitions for min/max and vector reduction
intrinsics do not allow pointer types:
https://llvm.org/docs/LangRef.html#llvm-smax-intrinsichttps://llvm.org/docs/LangRef.html#llvm-vector-reduce-umax-intrinsic
So we would crash/assert at some point - either in IR verification,
in the cost model, or in codegen. If we do want to allow this kind
of transform, we will need to update the LangRef and all of those
parts of the compiler.
Differential Revision: https://reviews.llvm.org/D97047
Now that all state for generated instructions is managed directly in
VPTransformState, VPCallBack is no longer needed. This patch updates the
last use of `getOrCreateScalarValue` to instead manage the value
directly in VPTransformState and removes VPCallback.
Reviewed By: gilr
Differential Revision: https://reviews.llvm.org/D95383
A v8i32 compare will produce a v8i1 predicate, but during codegen the
v8i32 will be split into two v4i32, potentially requiring two v4i1
predicates to be merged into a single v8i1. Because this merging of two
v4i1's into a v8i1 is very expensive, we need to make the cost of the
compare equally high.
This patch adds the cost of that to ARMTTIImpl::getCmpSelInstrCost.
Because we don't know whether the user of the predicate can be split,
and the cost model is mostly pre-instruction, we may be pessimistic but
that should only be for larger and legal types. This also adds min/max
detection to the costmodel where it can be detected, to keep those in
line with the cost of simple min/max instructions. Otherwise for the
most part, costs that were already expensive have become more expensive.
Differential Revision: https://reviews.llvm.org/D96692
Floating point conversions inside vectorized loops have performance
implications but are very subtle. The user could specify a floating
point constant, or call a function without realizing that it will
force a change in the vector width. An example of this behaviour is
seen in https://godbolt.org/z/M3nT6c . The vectorizer should indicate
when this happens becuase it is most likely unintended behaviour.
This patch adds a simple check for this behaviour by following floating
point stores in the original loop and checking if a floating point
conversion operation occurs.
Reviewed By: fhahn
Differential Revision: https://reviews.llvm.org/D95539
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
This patch updates codegen to use VPValues to manage the generated
scalarized instructions.
Reviewed By: gilr
Differential Revision: https://reviews.llvm.org/D92285
Currently, setting the `no-nans-fp-math` attribute to true will allow
loops with fmin/fmax to vectorize, though we should be requiring that
`no-signed-zeros-fp-math` is also set.
This patch adds the check for no-signed-zeros at the function level and includes
tests to make sure we don't vectorize functions with only one of the attributes
associated.
Reviewed By: spatel
Differential Revision: https://reviews.llvm.org/D96604
This patch fixes pr48832 by correctly generating the mask when a poison value is involved.
Consider this CFG (which is a part of the input):
```
for.body: ; preds = %for.cond
br i1 true, label %cond.false, label %land.rhs
land.rhs: ; preds = %for.body
br i1 poison, label %cond.end, label %cond.false
cond.false: ; preds = %for.body, %land.rhs
br label %cond.end
cond.end: ; preds = %land.rhs, %cond.false
%cond = phi i32 [ 0, %cond.false ], [ 1, %land.rhs ]
```
The path for.body -> land.rhs -> cond.end should be taken when 'select i1 false, i1 poison, i1 false' holds (which means it's never taken); but VPRecipeBuilder::createEdgeMask was emitting 'and i1 false, poison' instead.
The former one successfully blocks poison propagation whereas the latter one doesn't, making the condition poison and thus causing the miscompilation.
SimplifyCFG has a similar bug (which didn't expose a real-world bug yet), and a patch for this is also ongoing (see https://reviews.llvm.org/D95026).
Reviewed By: bjope
Differential Revision: https://reviews.llvm.org/D95217
Changes `getScalarizationOverhead` to return an invalid cost for scalable VFs
and adds some simple tests for loops containing a function for which
there is a vectorized variant available.
Reviewed By: david-arm
Differential Revision: https://reviews.llvm.org/D96356
The vector reduction intrinsics started life as experimental ops, so backend support
was lacking. As part of promoting them to 1st-class intrinsics, however, codegen
support was added/improved:
D58015
D90247
So I think it is safe to now remove this complication from IR.
Note that we still have an IR-level codegen expansion pass for these as discussed
in D95690. Removing that is another step in simplifying the logic. Also note that
x86 was already unconditionally forming reductions in IR, so there should be no
difference for x86.
I spot checked a couple of the tests here by running them through opt+llc and did
not see any asm diffs.
If we do find functional differences for other targets, it should be possible
to (at least temporarily) restore the shuffle IR with the ExpandReductions IR
pass.
Differential Revision: https://reviews.llvm.org/D96552
This reverts commit 502a67dd7f.
This expose a failure in test-suite build on PowerPC,
revert to unblock buildbot first,
Dave will re-commit in https://reviews.llvm.org/D96287.
Thanks Dave.
Define an option -riscv-vector-bits-max to specify the maximum vector
bits for vectorizer. Loop vectorizer will use the value to check if it
is safe to use the whole vector registers to vectorize the loop.
It is not the optimum solution for loop vectorizing for scalable vector.
It assumed the whole vector registers will be used to vectorize the code.
If it is possible, we should configure vl to do vectorize instead of
using whole vector registers.
We only consider LMUL = 1 in this patch.
This patch just an initial work for loop vectorizer for RISC-V Vector.
Differential Revision: https://reviews.llvm.org/D95659
getIntrinsicInstrCost takes a IntrinsicCostAttributes holding various
parameters of the intrinsic being costed. It can either be called with a
scalar intrinsic (RetTy==Scalar, VF==1), with a vector instruction
(RetTy==Vector, VF==1) or from the vectorizer with a scalar type and
vector width (RetTy==Scalar, VF>1). A RetTy==Vector, VF>1 is considered
an error. Both of the vector modes are expected to be treated the same,
but because this is confusing many backends end up getting it wrong.
Instead of trying work with those two values separately this removes the
VF parameter, widening the RetTy/ArgTys by VF used called from the
vectorizer. This keeps things simpler, but does require some other
modifications to keep things consistent.
Most backends look like this will be an improvement (or were not using
getIntrinsicInstrCost). AMDGPU needed the most changes to keep the code
from c230965ccf working. ARM removed the fix in
dfac521da1, webassembly happens to get a fixup for an SLP cost
issue and both X86 and AArch64 seem to now be using better costs from
the vectorizer.
Differential Revision: https://reviews.llvm.org/D95291
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 NFCI-ish prep work, but the changes are a bit too involved for me to feel comfortable tagging the change that way.
Differential Revision: https://reviews.llvm.org/D94892
This patch updates IRBuilder::CreateMaskedGather/Scatter to work
with ScalableVectorType and adds isLegalMaskedGather/Scatter functions
to AArch64TargetTransformInfo. In addition I've fixed up
isLegalMaskedLoad/Store to return true for supported scalar types,
since this is what the vectorizer asks for.
In LoopVectorize.cpp I've changed
LoopVectorizationCostModel::getInterleaveGroupCost to return an invalid
cost for scalable vectors, since currently this relies upon using shuffle
vector for reversing vectors. In addition, in
LoopVectorizationCostModel::setCostBasedWideningDecision I have assumed
that the cost of scalarising memory ops is infinitely expensive.
I have added some simple masked load/store and gather/scatter tests,
including cases where we use gathers and scatters for conditional invariant
loads and stores.
Differential Revision: https://reviews.llvm.org/D95350
Extend applyLoopGuards() to take into account conditions/assumes proving some
value %v to be divisible by D by rewriting %v to (%v / D) * D. This lets the
loop unroller and the loop vectorizer identify more loops as not requiring
remainder loops.
Differential Revision: https://reviews.llvm.org/D95521
This is another step (see D95452) towards correcting fast-math-flags
bugs in vector reductions.
There are multiple bugs visible in the test diffs, and this is still
not working as it should. We still use function attributes (rather
than FMF) to drive part of the logic, but we are not checking for
the correct FP function attributes.
Note that FMF may not be propagated optimally on selects (example
in https://llvm.org/PR35607 ). That's why I'm proposing to union the
FMF of a fcmp+select pair and avoid regressions on existing vectorizer
tests.
Differential Revision: https://reviews.llvm.org/D95690
D90687 introduced a crash:
llvm::LoopVectorizationCostModel::computeMaxVF(llvm::ElementCount, unsigned int):
Assertion `WideningDecisions.empty() && Uniforms.empty() && Scalars.empty() &&
"No decisions should have been taken at this point"' failed.
when compiling the following C code:
typedef struct {
char a;
} b;
b *c;
int d, e;
int f() {
int g = 0;
for (; d; d++) {
e = 0;
for (; e < c[d].a; e++)
g++;
}
return g;
}
with:
clang -Os -target hexagon -mhvx -fvectorize -mv67 testcase.c -S -o -
This occurred since prior to D90687 computeFeasibleMaxVF would only be
called in computeMaxVF when a scalar epilogue was allowed, but now it's
always called. This causes the assert above since computeFeasibleMaxVF
collects all viable VFs larger than the default MaxVF, and for each VF
calculates the register usage which results in analysis being done the
assert above guards against. This can occur in computeFeasibleMaxVF if
TTI.shouldMaximizeVectorBandwidth and this target hook is implemented in
the hexagon backend to always return true.
Reported by @iajbar.
Reviewed By: fhahn
Differential Revision: https://reviews.llvm.org/D94869
I am trying to untangle the fast-math-flags propagation logic
in the vectorizers (see a6f022127 for SLP).
The loop vectorizer has a mix of checking FP function attributes,
IR-level FMF, and just wrong assumptions.
I am trying to avoid regressions while fixing this, and I think
the IR-level logic is good enough for that, but it's hard to say
for sure. This would be the 1st step in the clean-up.
The existing test that I changed to include 'fast' actually shows
a miscompile: the function only had the equivalent of nnan, but we
created new instructions that had fast (all FMF set). This is
similar to the example in https://llvm.org/PR35538
Differential Revision: https://reviews.llvm.org/D95452
The existing test has less FMF than we might expect if
our FMF was fixed (on all FP values), so this additional
test is intended to check propagation in a more "normal"
example.
I have removed an unnecessary assert in LoopVectorizationCostModel::getInstructionCost
that prevented a cost being calculated for select instructions when using
scalable vectors. In addition, I have changed AArch64TTIImpl::getCmpSelInstrCost
to only do special cost calculations for fixed width vectors and fall
back to the base version for scalable vectors.
I have added a simple cost model test for cmps and selects:
test/Analysis/CostModel/sve-cmpsel.ll
and some simple tests that show we vectorize loops with cmp and select:
test/Transforms/LoopVectorize/AArch64/sve-basic-vec.ll
Differential Revision: https://reviews.llvm.org/D95039
We tend to assume that the AA pipeline is by default the default AA
pipeline and it's confusing when it's empty instead.
PR48779
Initially reverted due to BasicAA running analyses in an unspecified
order (multiple function calls as parameters), fixed by fetching
analyses before the call to construct BasicAA.
Reviewed By: asbirlea
Differential Revision: https://reviews.llvm.org/D95117
We tend to assume that the AA pipeline is by default the default AA
pipeline and it's confusing when it's empty instead.
PR48779
Reviewed By: asbirlea
Differential Revision: https://reviews.llvm.org/D95117
This adds cost modelling for the inloop vectorization added in
745bf6cf44. Up until now they have been modelled as the original
underlying instruction, usually an add. This happens to works OK for MVE
with instructions that are reducing into the same type as they are
working on. But MVE's instructions can perform the equivalent of an
extended MLA as a single instruction:
%sa = sext <16 x i8> A to <16 x i32>
%sb = sext <16 x i8> B to <16 x i32>
%m = mul <16 x i32> %sa, %sb
%r = vecreduce.add(%m)
->
R = VMLADAV A, B
There are other instructions for performing add reductions of
v4i32/v8i16/v16i8 into i32 (VADDV), for doing the same with v4i32->i64
(VADDLV) and for performing a v4i32/v8i16 MLA into an i64 (VMLALDAV).
The i64 are particularly interesting as there are no native i64 add/mul
instructions, leading to the i64 add and mul naturally getting very
high costs.
Also worth mentioning, under NEON there is the concept of a sdot/udot
instruction which performs a partial reduction from a v16i8 to a v4i32.
They extend and mul/sum the first four elements from the inputs into the
first element of the output, repeating for each of the four output
lanes. They could possibly be represented in the same way as above in
llvm, so long as a vecreduce.add could perform a partial reduction. The
vectorizer would then produce a combination of in and outer loop
reductions to efficiently use the sdot and udot instructions. Although
this patch does not do that yet, it does suggest that separating the
input reduction type from the produced result type is a useful concept
to model. It also shows that a MLA reduction as a single instruction is
fairly common.
This patch attempt to improve the costmodelling of in-loop reductions
by:
- Adding some pattern matching in the loop vectorizer cost model to
match extended reduction patterns that are optionally extended and/or
MLA patterns. This marks the cost of the reduction instruction correctly
and the sext/zext/mul leading up to it as free, which is otherwise
difficult to tell and may get a very high cost. (In the long run this
can hopefully be replaced by vplan producing a single node and costing
it correctly, but that is not yet something that vplan can do).
- getExtendedAddReductionCost is added to query the cost of these
extended reduction patterns.
- Expanded the ARM costs to account for these expanded sizes, which is a
fairly simple change in itself.
- Some minor alterations to allow inloop reduction larger than the highest
vector width and i64 MVE reductions.
- An extra InLoopReductionImmediateChains map was added to the vectorizer
for it to efficiently detect which instructions are reductions in the
cost model.
- The tests have some updates to show what I believe is optimal
vectorization and where we are now.
Put together this can greatly improve performance for reduction loop
under MVE.
Differential Revision: https://reviews.llvm.org/D93476
It turns out the vectorizer calls the getIntrinsicInstrCost functions
with a scalar return type and vector VF. This updates the costmodel to
handle that, still producing the correct vector costs.
A vectorizer test is added to show it vectorizing at the correct factor
again.
Just like llvm.assume, there are a lot of cases where we can just ignore llvm.experimental.noalias.scope.decl.
Reviewed By: nikic
Differential Revision: https://reviews.llvm.org/D93042
Keys matching the tombstone/empty special values cannot be inserted in a
DenseMap. Under some circumstances, LV tries to add members to an
interleave group that match the special values. Skip adding such
members. This is unlikely to have any impact in practice, because
interleave groups with such indices are very likely to not be
vectorized, due to gaps.
This issue has been surfaced by fuzzing, see
https://bugs.chromium.org/p/oss-fuzz/issues/detail?id=11638
This relates to the ongoing effort to support vectorization of multiple exit loops (see D93317).
The previous code assumed that LCSSA phis were always single entry before the vectorizer ran. This was correct, but only because the vectorizer allowed only a single exiting edge. There's nothing in the definition of LCSSA which requires single entry phis.
A common case where this comes up is with a loop with multiple exiting blocks which all reach a common exit block. (e.g. see the test updates)
Differential Revision: https://reviews.llvm.org/D93725
This patch unifies the way recipes and VPValues are printed after the
transition to VPDef.
VPSlotTracker has been updated to iterate over all recipes and all
their defined values to number those. There is no need to number
values in Value2VPValue.
It also updates a few places that only used slot numbers for
VPInstruction. All recipes now can produce numbered VPValues.
In the following loop:
void foo(int *a, int *b, int N) {
for (int i=0; i<N; ++i)
a[i + 4] = a[i] + b[i];
}
The loop dependence constrains the VF to a maximum of (4, fixed), which
would mean using <4 x i32> as the vector type in vectorization.
Extending this to scalable vectorization, a VF of (4, scalable) implies
a vector type of <vscale x 4 x i32>. To determine if this is legal
vscale must be taken into account. For this example, unless
max(vscale)=1, it's unsafe to vectorize.
For SVE, the number of bits in an SVE register is architecturally
defined to be a multiple of 128 bits with a maximum of 2048 bits, thus
the maximum vscale is 16. In the loop above it is therefore unfeasible
to vectorize with SVE. However, in this loop:
void foo(int *a, int *b, int N) {
#pragma clang loop vectorize_width(X, scalable)
for (int i=0; i<N; ++i)
a[i + 32] = a[i] + b[i];
}
As long as max(vscale) multiplied by the number of lanes 'X' doesn't
exceed the dependence distance, it is safe to vectorize. For SVE a VF of
(2, scalable) is within this constraint, since a vector of <16 x 2 x 32>
will have no dependencies between lanes. For any number of lanes larger
than this it would be unsafe to vectorize.
This patch extends 'computeFeasibleMaxVF' to legalize scalable VFs
specified as loop hints, implementing the following behaviour:
* If the backend does not support scalable vectors, ignore the hint.
* If scalable vectorization is unfeasible given the loop
dependence, like in the first example above for SVE, then use a
fixed VF.
* Accept scalable VFs if it's safe to do so.
* Otherwise, clamp scalable VFs that exceed the maximum safe VF.
Reviewed By: sdesmalen, fhahn, david-arm
Differential Revision: https://reviews.llvm.org/D91718
The new test case here contains a first order recurrences and an
instruction that is replicated. The first order recurrence forces an
instruction to be sunk _into_, as opposed to after the replication
region. That causes several things to go wrong including registering
vector instructions multiple times and failing to create dominance
relations correctly.
Instead we should be sinking to after the replication region, which is
what this patch makes sure happens.
Differential Revision: https://reviews.llvm.org/D93629
This patch makes SLP and LV emit operations with initial vectors set to poison constant instead of undef.
This is a part of efforts for using poison vector instead of undef to represent "doesn't care" vector.
The goal is to make nice shufflevector optimizations valid that is currently incorrect due to the tricky interaction between undef and poison (see https://bugs.llvm.org/show_bug.cgi?id=44185 ).
Reviewed By: fhahn
Differential Revision: https://reviews.llvm.org/D94061
Creating in-loop reductions relies on IR references to map
IR values to VPValues after interleave group creation.
Make sure we re-add the updated member to the plan, so the look-ups
still work as expected
This fixes a crash reported after D90562.
Let getTruncateExpr() short-circuit to zero when the value being truncated is
known to have at least as many trailing zeros as the target type.
Differential Revision: https://reviews.llvm.org/D93973
The loop vectorizer avoids folding the tail for loop's whose trip-count is
known to SCEV to be divisible by VF. In this case the assumption providing this
information is not taken into account, so the tail is needlessly folded.
If DoExtraAnalysis is true (e.g. because remarks are enabled), we
continue with the analysis rather than exiting. Update code to
conditionally check if the ExitBB has phis or not a single predecessor.
Otherwise a nullptr is dereferenced with DoExtraAnalysis.
As mentioned in D93793, there are quite a few places where unary `IRBuilder::CreateShuffleVector(X, Mask)` can be used
instead of `IRBuilder::CreateShuffleVector(X, Undef, Mask)`.
Let's update them.
Actually, it would have been more natural if the patches were made in this order:
(1) let them use unary CreateShuffleVector first
(2) update IRBuilder::CreateShuffleVector to use poison as a placeholder value (D93793)
The order is swapped, but in terms of correctness it is still fine.
Reviewed By: spatel
Differential Revision: https://reviews.llvm.org/D93923
This patch updates IRBuilder to create insertelement/shufflevector using poison as a placeholder.
Reviewed By: nikic
Differential Revision: https://reviews.llvm.org/D93793
This reverts commit 4ffcd4fe9a thus restoring e4df6a40da.
The only change from the original patch is to add "llvm::" before the call to empty(iterator_range). This is a speculative fix for the ambiguity reported on some builders.
This patch is a major step towards supporting multiple exit loops in the vectorizer. This patch on it's own extends the loop forms allowed in two ways:
single exit loops which are not bottom tested
multiple exit loops w/ a single exit block reached from all exits and no phis in the exit block (because of LCSSA this implies no values defined in the loop used later)
The restrictions on multiple exit loop structures will be removed in follow up patches; disallowing cases for now makes the code changes smaller and more obvious. As before, we can only handle loops with entirely analyzable exits. Removing that restriction is much harder, and is not part of currently planned efforts.
The basic idea here is that we can force the last iteration to run in the scalar epilogue loop (if we have one). From the definition of SCEV's backedge taken count, we know that no earlier iteration can exit the vector body. As such, we can leave the decision on which exit to be taken to the scalar code and generate a bottom tested vector loop which runs all but the last iteration.
The existing code already had the notion of requiring one iteration in the scalar epilogue, this patch is mainly about generalizing that support slightly, making sure we don't try to use this mechanism when tail folding, and updating the code to reflect the difference between a single exit block and a unique exit block (very mechanical).
Differential Revision: https://reviews.llvm.org/D93317
Currently undef is used as a don’t-care vector when constructing a vector using a series of insertelement.
However, this is problematic because undef isn’t undefined enough.
Especially, a sequence of insertelement can be optimized to shufflevector, but using undef as its placeholder makes shufflevector a poison-blocking instruction because undef cannot be optimized to poison.
This makes a few straightforward optimizations incorrect, such as:
```
; https://bugs.llvm.org/show_bug.cgi?id=44185
define <4 x float> @insert_not_undef_shuffle_translate_commute(float %x, <4 x float> %y, <4 x float> %q) {
%xv = insertelement <4 x float> %q, float %x, i32 2
%r = shufflevector <4 x float> %y, <4 x float> %xv, <4 x i32> { 0, 6, 2, undef }
ret <4 x float> %r ; %r[3] is undef
}
=>
define <4 x float> @insert_not_undef_shuffle_translate_commute(float %x, <4 x float> %y, <4 x float> %q) {
%r = insertelement <4 x float> %y, float %x, i32 1
ret <4 x float> %r ; %r[3] = %y[3], incorrect if %y[3] = poison
}
Transformation doesn't verify!
ERROR: Target is more poisonous than source
```
I’d like to suggest
1. Using poison as insertelement’s placeholder value (IRBuilder::CreateVectorSplat should be patched too)
2. Updating shufflevector’s semantics to return poison element if mask is undef
Note that poison is currently lowered into UNDEF in SelDag, so codegen part is okay.
m_Undef() matches PoisonValue as well, so existing optimizations will still fire.
The only concern is hidden miscompilations that will go incorrect when poison constant is given.
A conservative way is copying all tests having `insertelement undef` & replacing it with `insertelement poison` & run Alive2 on it, but it will create many tests and people won’t like it. :(
Instead, I’ll simply locally maintain the tests and run Alive2.
If there is any bug found, I’ll report it.
Relevant links: https://bugs.llvm.org/show_bug.cgi?id=43958 , http://lists.llvm.org/pipermail/llvm-dev/2019-November/137242.html
Reviewed By: nikic
Differential Revision: https://reviews.llvm.org/D93586
Previously the branch from the middle block to the scalar preheader & exit
was being set-up at the end of skeleton creation in completeLoopSkeleton.
Inserting SCEV or runtime checks may result in LCSSA phis being created,
if they are required. Adjusting branches afterwards may break those
PHIs.
To avoid this, we can instead create the branch from the middle block
to the exit after we created the middle block, so we have the final CFG
before potentially adjusting/creating PHIs.
This fixes a crash for the included test case. For the non-crashing
case, this is almost a NFC with respect to the generated code. The
only change is the order of the predecessors of the involved branch
targets.
Note an assertion was moved from LoopVersioning() to
LoopVersioning::versionLoop. Adjusting the branches means loop-simplify
form may be broken before constructing LoopVersioning. But LV only uses
LoopVersioning to annotate the loop instructions with !noalias metadata,
which does not require loop-simplify form.
This is a fix for an existing issue uncovered by D93317.
When the trip-count is provably divisible by the maximal/chosen VF, folding the
loop's tail during vectorization is redundant. This commit extends the existing
test for constant trip-counts to any trip-count known to be divisible by
maximal/selected VF by SCEV.
Differential Revision: https://reviews.llvm.org/D93615
And that exposes that a number of tests don't *actually* manage to
maintain DomTree validity, which is inline with my observations.
Once again, SimlifyCFG pass currently does not require/preserve DomTree
by default, so this is effectively NFC.
Temporarily revert commit 8b1c4e310c.
After 8b1c4e310c the compile-time for `MultiSource/Benchmarks/MiBench/consumer-lame`
dramatically increases with -O3 & LTO, causing issues for builders with
that configuration.
I filed PR48553 with a smallish reproducer that shows a 10-100x compile
time increase.
... so just ensure that we pass DomTreeUpdater it into it.
Fixes DomTree preservation for a large number of tests,
all of which are marked as such so that they do not regress.
... so just ensure that we pass DomTreeUpdater it into it.
Fixes DomTree preservation for a large number of tests,
all of which are marked as such so that they do not regress.
Florian Hahn