Most AArch64 cpus outside of Neoverse V1 (256) and A64FX (512) have an
SVE vector length of 128, and in environments like Android (where no
mcpu option is common) we would expect all cpus to match. This patch
changes the default vector length to 128 with -mcpu=generic, to match
the most common case.
This test checks the costs, not vectorization, so is better placed in the
existing gather/scatter cost modelling tests. An extra neoverse-v2 check line
has been added for both gathers and scatters.
If IVUpdateMayOverflow is false, we proved that the induction increment
cannot overflow in the vector loop. This allows setting NUW in some
cases when folding the tail.
PR: https://github.com/llvm/llvm-project/pull/111758
Update the test cases contains `any-of` printings from the
precomputeCost().
Origin message:
The any-of reduction contains phi and select instructions.
The select instruction might be optimized and removed in the vplan which
may cause VF difference between legacy and VPlan-based model. But if the
select instruction be removed, planContainsAdditionalSimplifications()
will catch it and disable the assertion.
Therefore, we can just remove the ayn-of reduction calculation in the
precomputeCost().
Recommit "[LV][VPlan] Remove any-of reduction from precomputeCost. NFC
(#117109)"
Set the maximum interleaving factor to 4, aligning with the number of available
SIMD pipelines. This increases the number of vector instructions in the vectorised
loop body, enhancing performance during its execution. However, for very low
iteration counts, the vectorised body might not execute at all, leaving only the
epilogue loop to run. This issue affects e.g. cam4_r from SPEC FP, which
experienced a performance regression. To address this, the patch reduces the
minimum epilogue vectorisation factor from 16 to 8, enabling the epilogue to be
vectorised and largely mitigating the regression.
Currently it's very difficult to improve the cost model for tail-folded
loops because as soon as you add a VPInstruction::computeCost function
that adds the costs of instructions such as
VPInstruction::ActiveLaneMask
and VPInstruction::ExplicitVectorLength the assert in
LoopVectorizationPlanner::computeBestVF fails for some tests. This is
because the VF chosen by the legacy cost model doesn't match the vplan
cost model. See PR #90191. This assert is currently making it difficult
to improve the cost model.
Hopefully we will be in a position to remove the assert soon, however
in order to do that we have to fix up a whole bunch of tests that rely
upon the legacy cost model output. I've tried my best to update
these tests to use vplan output instead.
There is still work needed for the VF=1 case because the vplan cost
model is not printed out in this case. I've not attempted to fix those
in this patch.
Instead of only trying to constant fold the select arms, try to simplify
them. This subsumes https://github.com/llvm/llvm-project/pull/115969
which implements this for extractvalue only.
This is still fairly limited in that we will usually only call
FoldOpIntoSelect in the first place if we have a constant operand. This
can be relaxed in the future if worthwhile.
- Consider MainLoopVF * IC when determining whether Epilogue
Vectorization is profitable
- Allow the same VF for the Epilogue as for the main loop
- Use an upper bound for the trip count of the Epilogue when choosing
the Epilogue VF
PR: https://github.com/llvm/llvm-project/pull/108190
---------
Co-authored-by: Florian Hahn <flo@fhahn.com>
If we have a pointer AddRec, the maximum increment is
2^(pointer-index-wdith - 1) - 1. This means that if incrementing the
AddRec wraps, the distance between the previously accessed location and
the wrapped location is > 2^(pointer-index-wdith - 1), i.e. if the GEP
for the AddRec is inbounds, this would be poison due to the object being
larger than half the pointer index type space. The poison would be
immediate UB when the memory access gets executed..
Similar reasoning can be applied for decrements.
PR: https://github.com/llvm/llvm-project/pull/113126
Update VPlan to include the scalar loop header. This allows retiring
VPLiveOut, as the remaining live-outs can now be handled by adding
operands to the wrapped phis in the scalar loop header.
Note that the current version only includes the scalar loop header, no
other loop blocks and also does not wrap it in a region block.
PR: https://github.com/llvm/llvm-project/pull/109975
Many tests that were in test/Analysis/CostModel were actually
loop vectoriser tests. I've moved them as follows:
Analysis/CostModel/X86 -> Transforms/LoopVectorize/X86/CostModel
Analysis/CostModel/AArch64/arith-fp-frem.ll ->
Transforms/LoopVectorize/AArch64/arith-fp-frem-costs.ll
Refactors VPVectorPointerRecipe to use the VF VPValue to obtain the
runtime VF, similar to #95305.
Since only reverse vector pointers require the runtime VF, the patch
sets VPUnrollPart::PartOpIndex to 1 for vector pointers and 2 for
reverse vector pointers. As a result, the generation of reverse vector
pointers is moved into a separate recipe.
This change is part of this proposal:
https://discourse.llvm.org/t/rfc-all-the-math-intrinsics/78294
- `VecFuncs.def`: define intrinsic to sleef/armpl mapping
- `LegalizerHelper.cpp`: add missing fewerElementsVector handling for
the new atan2 intrinsic
- `AArch64ISelLowering.cpp`: Add arch64 specializations for lowering
like neon instructions
- `AArch64LegalizerInfo.cpp`: Legalize atan2.
Part 5 for Implement the atan2 HLSL Function #70096.
Use SCEV to check if the minimum iteration check (TC < Step) is known to
be false.
This is a first step towards addressing
https://github.com/llvm/llvm-project/issues/111098. To catch the exact
case from the issue, we need to do extra work to make sure the wrap
flags on the shl are preserved and used by SCEV.
Note that skeleton creation will be gradually moved to VPlan and this
simplification should be done as VPlan transform eventually. The current
plan is to move skeleton creation to VPlan starting from parts closest
to the parts already created by VPlan, starting with induction resume
value creation (started with
https://github.com/llvm/llvm-project/pull/110577), then memory and SCEV
checks and finally minimum iteration checks.
PR: https://github.com/llvm/llvm-project/pull/111310
I realised we are missing tests to cover more loops with multiple early
exits - some countable and some uncountable.
I've also added a few SVE versions of the test in the AArch64 directory.
Once we can vectorise such early exit loops it's a good sanity check to
make sure they also vectorise for SVE. Also, for some of the tests I
expect there to be some divergence from the same tests in the top level
directory once we start vectorising them.
There are a number of places where we call getSmallConstantMaxTripCount
without passing a vector of predicates:
getSmallBestKnownTC
isIndvarOverflowCheckKnownFalse
computeMaxVF
isMoreProfitable
I've changed all of these to now pass in a predicate vector so that
we get the benefit of making better vectorisation choices when we
know the max trip count for loops that require SCEV predicate checks.
I've tried to add tests that cover all the cases affected by these
changes.
Update fixupIVUsers to compute the value for escaped inductions using
the already computed end value of the induction (EndValue), but
subtracting the step.
This results in slightly simpler codegen, as we avoid computing the full
transformed index at VectorTripCount - 1.
PR: https://github.com/llvm/llvm-project/pull/110576
This patch splits off intrinsic hanlding to a new
VPWidenIntrinsicRecipe. VPWidenIntrinsicRecipes only need access to the
intrinsic ID to widen and the scalar result type (in case the intrinsic
is overloaded on the result type). It does not need access to an
underlying IR call instruction or function.
This means VPWidenIntrinsicRecipe can be created easily without access
to underlying IR.
Implement VPBlendRecipe::computeCost. VPBlendRecipe is currently is also
used if only the first lane is used.
This also requires pre-computing costs for forced scalars and
instructions considered profitable to scalarize. For those, the cost
will be computed separately in the legacy cost model. This will also be
needed when implementing VPReplicateRecipe::computeCost.
Update VPInterleaveRecipe to always use the pointer to member 0 as
pointer argument. This in many cases helps to remove unneeded index
adjustments and simplifies VPInterleaveRecipe::execute.
In some rare cases, the address of member 0 does not dominate the insert
position of the interleave group. In those cases a PtrAdd VPInstruction
is emitted to compute the address of member 0 based on the address of
the insert position. Alternatively we could hoist the recipe computing
the address of member 0.
When expanding SCEV adds to geps, transfer the nuw flag to the resulting
gep. (Note that this doesn't apply to IV increment GEPs, which go
through a different code path.)
Update VPWidenCallRecipe to manage fast-math flags directly via
VPRecipeWithIRFlags. This addresses a TODO and allows adjusting the FMFs
directly on the recipe. Also fixes printing for flags for
VPWidenCallRecipe.
LoopAccessAnalysis currently does not check/track aliasing from the
output pointers, but assumes vectorizing library calls with a mapping is
safe.
This can result in incorrect codegen if something like the following is
vectorized:
```
for(int i=0; i<N; i++) {
// No aliasing between input and output pointers detected.
sincos(cos_out[0], sin_out+i, cos_out+i);
}
```
Where for VF >= 2 `cos_out[1]` to `cos_out[VF-1]` is the cosine of the
original value of `cos_out[0]` not the updated value.
When trying to maximize vector bandwidth we ask TTI for the number of
registers required for a given operation. If the type of that operation
happens to be something illegal for scalable vectors (e.g.
<vscale x 4 x fp128>) then we would see a crash.
Instead, just return a default value and let the cost model reject the
invalid operation later.
This patch implements explicit unrolling by UF as VPlan transform. In
follow up patches this will allow simplifying VPTransform state (no need
to store unrolled parts) as well as recipe execution (no need to
generate code for multiple parts in an each recipe). It also allows for
more general optimziations (e.g. avoid generating code for recipes that
are uniform-across parts).
It also unifies the logic dealing with unrolled parts in a single place,
rather than spreading it out across multiple places (e.g. VPlan post
processing for header-phi recipes previously.)
In the initial implementation, a number of recipes still take the
unrolled part as additional, optional argument, if their execution
depends on the unrolled part.
The computation for start/step values for scalable inductions changed
slightly. Previously the step would be computed as scalar and then
splatted, now vscale gets splatted and multiplied by the step in a
vector mul.
This has been split off https://github.com/llvm/llvm-project/pull/94339
which also includes changes to simplify VPTransfomState and recipes'
::execute.
The current version mostly leaves existing ::execute untouched and
instead sets VPTransfomState::UF to 1.
A follow-up patch will clean up all references to VPTransformState::UF.
Another follow-up patch will simplify VPTransformState to only store a
single vector value per VPValue.
PR: https://github.com/llvm/llvm-project/pull/95842
Update some tests with loop invariant instructions so the instructions
cannot be hoisted out.
This preserves the original test intention after
https://github.com/llvm/llvm-project/pull/107894.
At the moment, the full cost of all interleave group members is assigned
to the instruction at the group's insert position, even if the decision
was to not form an interleave group.
This can lead to inaccurate cost estimates, e.g. if the instruction at
the insert position is dead. If the decision is to not vectorize but
scalarize or scather/gather, then the cost will be to total cost for all
members. In those cases, assign individual the cost per member, to more
closely reflect to choice per instruction.
This fixes a divergence between legacy and VPlan-based cost model.
Fixes https://github.com/llvm/llvm-project/issues/108098.
Similar to VFxUF, also add a VF VPValue to VPlan and use it to get the
runtime VF in VPWidenIntOrFpInductionRecipe. Code for VF is only
generated if there are users of VF, to avoid unnecessary test changes.
PR: https://github.com/llvm/llvm-project/pull/95305
Update some tests with loop-invariant instructions, where hoisting them
out of the loop changes the vectorization decision. This should preserve
their original spirit when making further improvements.
