This PR reassociates logical ands in order to enable more
simplifications.
The driving motivation for this is that with tail folding all blocks
inside the loop body will end up using the header mask. However this can
end up nestled deep within a chain of logical ands from other edges.
Typically the header mask will be a leaf nested in the LHS, e.g.
(headermask & y) & z. So pulling it out allows it to be simplified
further, e.g. allows it to be optimised away to VP intrinsics with EVL
tail folding.
Introduce a simple common-subexpression-elimination pass at the
VPlan-level, running late during the execution of the VPlan. The
long-term vision is to get rid of the legacy non-VPlan-based cse routine
in LV, but this patch doesn't yet fully subsume it.
The InterleavedAccess pass already supports transforming
vector-predicated (vp) load/store intrinsics. With this patch, we start
enabling interleaved access under tail folding by EVL.
This patch introduces a new base class, VPInterleaveBase, and a concrete
class, VPInterleaveEVLRecipe. Both the existing VPInterleaveRecipe and
the new VPInterleaveEVLRecipe inherit from and implement
VPInterleaveBase.
Compared to VPInterleaveRecipe, VPInterleaveEVLRecipe adds an EVL
operand to emit vp.load/vp.store intrinsics.
Currently, tail folding by EVL is only supported for scalable
vectorization. Therefore, VPInterleaveEVLRecipe will only emit
interleave/deinterleave intrinsics. Reverse accesses are not yet
implemented, as masked reverse interleaved access under tail folding is
not yet supported.
Fixed#123201
This patch adds a new flag (-enable-wide-lane-mask) which allows
LoopVectorize to generate wider-than-VF active lane masks when it
is safe to do so (i.e. the mask is used for data and control flow).
The transform in extractFromWideActiveLaneMask creates vector
extracts from the first active lane mask in the header & loop body,
modifying the active lane mask phi operands to use the extracts.
An additional operand is passed to the ActiveLaneMask instruction,
the value of which is used as a multiplier of VF when generating the
mask.
By default this is 1, and is updated to UF by
extractFromWideActiveLaneMask.
The motivation for this change is to improve interleaved loops when
SVE2.1 is available, where we can make use of the whilelo instruction
which returns a predicate pair.
This is based on a PR that was created by @momchil-velikov (#81140)
and contains tests which were added there.
Update narrowInterleaveGroups to support scalable VFs. After the
transform, the vector loop will process a single iteration of the
original vector loop for fixed-width vectors and vscale iterations for
scalable vectors.
This patch adds a new VPlan-based addMinimumIterationCheck, which
replaced the ILV version for the non-epilogue case.
The VPlan-based version constructs a SCEV expression to compute the
minimum iterations, use that to check if the check is known true or
false. Otherwise it creates a VPExpandSCEV recipe and emits a
compare-and-branch.
When using epilogue vectorization, we still need to create the minimum
trip-count-check during the legacy skeleton creation. The patch moves
the definitions out of ILV.
PR: https://github.com/llvm/llvm-project/pull/153643
This changes the branch condition to use the AVL's backedge value
instead of the EVL-based IV.
This allows us to emit bnez on RISC-V and removes a use of the trip
count, which should reduce register pressure.
To match phis with VPlanPatternMatch I've had to relax the assert that
the number of operands must exactly match the pattern for the Phi
opcode, and I've copied over m_ZExtOrSelf from the LLVM IR
PatternMatch.h.
Fixes#151459
Extend [Specific]Cmp_match to handle floating-point compares, and
introduce m_Cmp that matches both integer and floating-point compares.
Use it in simplifyRecipe to match and simplify the general case of
compares. The change has necessitated a bugfix in
VPReplicateRecipe::execute.
Currently we only allow folding not (cmp eq) -> icmp ne if the not is
the only user of the compare.
However a common scenario is that some select might also use the
compare. We can still fold the not if we also swizzle the arms of the
selects.
This helps avoid regressions in #150368
Move the logic to expand SCEVs directly to a late VPlan transform that
expands SCEVs in the entry block. This turns VPExpandSCEVRecipe into an
abstract recipe without execute, which clarifies how the recipe is
handled, i.e. it is not executed like regular recipes.
It also helps to simplify construction, as now scalar evolution isn't
required to be passed to the recipe.
SimplifyBranchConditionForVFAndUF only recognized canonical IVs and a
few PHI
recipes in the loop header. With more IV-step optimizations,
the canonical widen-canonical-iv can be replaced by a canonical
VPWidenIntOrFpInduction,
which the pass did not handle, causing regressions (missed
simplifications).
This patch replaces canonical VPWidenIntOrFpInduction with a StepVector
in the vector preheader
since the vector loop region only executes once.
This is the first step in untangling the variable step transform and
header mask optimizations as described in #152541.
Currently we replace all VF users globally in the plan, including
VPVectorEndPointerRecipe. However this leaves reversed loads and stores
in an incorrect state until they are adjusted in optimizeMaskToEVL.
This moves the VPVectorEndPointerRecipe transform so that it is updated
in lockstep with the actual load/store recipe.
One thought that crossed my mind was that VPInterleaveRecipe could also
use VPVectorEndPointerRecipe, in which case we would have also been
computing the wrong address because we don't transform it to an EVL
recipe which accounts for the reversed address.
If we end up with a extract_element VPInstruction where both operands
are live-ins, we will try to fold the live-ins even though the first
operand is a vector whilst the live-in is scalar.
This fixes it by just returning the vector live-in instead of calling
the folder, and removes the handling for insertelement where we aren't
able to do the fold. From some quick testing we previously never hit
this fold anyway, and were probably just missing test coverage.
Fixes#154045
Materialze Build(Struct)Vectors explicitly for VPRecplicateRecipes, to
serve their users requiring a vector, instead of doing so when unrolling
by VF.
Now we only need to implicitly build vectors in VPTransformState::get
for VPInstructions. Once they are also unrolled by VF we can remove the
code-path alltogether.
PR: https://github.com/llvm/llvm-project/pull/151487
We almost only ever have one header mask, except with the data tail
folding style, i.e. with VPInstruction::ActiveLaneMask.
All we need to do is to make sure to erase the old header icmp based
header mask when replacing it.
This reverts commit 1c7c8e3ad39957285524ff116d9a6aec0d9b62f9.
Recommit with a fix for the verifier error caused for EVL recipes.
Extra test coverage added in 6f939da60e.
Materialize VF and VFxUF computation using VPInstruction
instead of directly creating IR.
This is one of the last few steps needed to model the full vector
skeleton in VPlan.
This is mostly NFC, although in some cases we remove some unused
computations.
PR: https://github.com/llvm/llvm-project/pull/152879
A lot of time getCanonicalIV() is used to get the canonical IV type,
e.g. to instantiate a VPTypeAnalysis or to get the LLVMContext.
However VPTypeAnalysis has a constructor that takes the VPlan directly
and there's a method on VPlan to get the LLVMContext directly, so use
those instead where possible.
This lets us remove a constructor on VPTypeAnalysis.
Also remove an unused LLVMContext argument in UnrollState whilst we're
here.
The EVL mask is always defined as `icmp ult (step-vector, EVL)`, so we
only need to generate it once per plan in the header. Then, we replace
all uses of the header mask with the EVL mask, and recursively optimize
the users of EVL mask into EVL recipes. This way, the transformation to
EVL recipes can be done with just a single loop.
Materialize the vector trip count computation using VPInstruction
instead of directly creating IR. This is one of the last few steps
needed to model the full vector skeleton in VPlan. It also simplifies
vector-trip count computations for scalable vectors, as we can re-use
the UF x VF computation.
PR: https://github.com/llvm/llvm-project/pull/151925
Now that VPWidenPointerInductionRecipes are modelled in VPlan in
#148274, we can support them in EVL tail folding.
We need to replace their VFxUF operand with EVL as the increment is not
guaranteed to always be VF on the penultimate iteration, and UF is
always 1 with EVL tail folding.
We also need to move the creation of the backedge value to the latch so
that EVL dominates it.
With this we will no longer fail to convert a VPlan to EVL tail folding,
so adjust tryAddExplicitVectorLength to account for this. This brings us
to 99.4% of all vector loops vectorized on SPEC CPU 2017 with tail
folding vs no tail folding.
The test in only-compute-cost-for-vplan-vfs.ll previously relied on
widened pointer inductions with EVL tail folding to end up in a scenario
with no vector VPlans, so this also replaces it with an unvectorizable
fixed-order recurrence test from
first-order-recurrence-multiply-recurrences.ll that also gets discarded.
The initial VPlan closely reflects the original scalar loop, so unsing
VPWidenPHIRecipe here is premature. Widened phi recipes should only be
introduced together with other widened recipes.
PR: https://github.com/llvm/llvm-project/pull/150847
