When calculating the cost of Instruction::Br in getInstructionCost
we query PredicatedBBsAfterVectorization to see if there is a
scalar predicated block. However, this meant that the decisions
being made for a given fixed-width VF were affecting the cost for a
scalable VF. As a result we were returning InstructionCost::Invalid
pointlessly for a scalable VF that should have a low cost. I
encountered this for some loops when enabling tail-folding for
scalable VFs.
Test added here:
Transforms/LoopVectorize/AArch64/sve-tail-folding-cost.ll
Differential Revision: https://reviews.llvm.org/D128272
Currently, for vectorised loops that use the get.active.lane.mask
intrinsic we only use the mask for predicated vector operations,
such as masked loads and stores, etc. The loop itself is still
controlled by comparing the canonical induction variable with the
trip count. However, for some targets this is inefficient when it's
cheap to use the mask itself to control the loop.
This patch adds support for using the active lane mask for control
flow by:
1. Generating the active lane mask for the next iteration of the
vector loop, rather than the current one. If there are still any
remaining iterations then at least the first bit of the mask will
be set.
2. Extract the first bit of this mask and use this bit for the
conditional branch.
I did this by creating a new VPActiveLaneMaskPHIRecipe that sets
up the initial PHI values in the vector loop pre-header. I've also
made use of the new BranchOnCond VPInstruction for the final
instruction in the loop region.
Differential Revision: https://reviews.llvm.org/D125301
This patch is a simple piece of refactoring that now permits users
to create VPInstructions and specify the name of the value being
generated. This is useful for creating more readable/meaningful
names in IR.
Differential Revision: https://reviews.llvm.org/D128982
Now that removeDeadRecipes can remove most dead recipes across a whole
VPlan, there is no need to first collect some dead instructions.
Instead removeDeadRecipes can simply clean them up.
Depends D127580.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D128408
This can enable additional region merging, while not losing
opportunities as region merging does not produce dead recipes.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D128831
As integer div/rem constant expressions are no longer supported,
constants can no longer trap and are always safe to speculate.
Remove the Constant::canTrap() method and its usages.
This in an extension to the code added in D123911 which added vector
combine folding of shuffle-select patterns, attempting to reduce the
total amount of shuffling required in patterns like:
%x = shuffle %i1, %i2
%y = shuffle %i1, %i2
%a = binop %x, %y
%b = binop %x, %y
shuffle %a, %b, selectmask
This patch extends the handing of shuffles that are dependent on one
another, which can arise from the SLP vectorizer, as-in:
%x = shuffle %i1, %i2
%y = shuffle %x
The input shuffles can also be emitted, in which case they are treated
like identity shuffles. This patch also attempts to calculate a better
ordering of input shuffles, which can help getting lower cost input
shuffles, pushing complex shuffles further down the tree.
This is a recommit with some additional checks for supported forms and
out-of-bounds mask elements, with some extra tests.
Differential Revision: https://reviews.llvm.org/D128732
For scalable VFs, the minimum assumed vscale needs to be included in the
cost-computation, otherwise a smaller VF may be used for RT check cost
computation than was used for earlier cost computations.
Fixes a RISCV test failing with UBSan due to both scalar and vector
loops having the same cost.
This reverts commit 19a1e20b8a0f69da2a871eae6cbd03d1314ee02d.
Clang crashes while linking bullet from llvm-test-suite in
ReleaseLTO-g cmake configuration.
This fixes an UBSan failure after 644a965c1efef. When using
user-provided VFs/ICs (via the force-vector-width /
force-vector-interleave options) the scalar cost is zero, which would
cause divide-by-zero.
When forcing vectorization using the options, the cost of the runtime
checks should not block vectorization.
This patch replaces the tight hard cut-off for the number of runtime
checks with a more accurate cost-driven approach.
The new approach allows vectorization with a larger number of runtime
checks in general, but only executes the vector loop (and runtime checks) if
considered profitable at runtime. Profitable here means that the cost-model
indicates that the runtime check cost + vector loop cost < scalar loop cost.
To do that, LV computes the minimum trip count for which runtime check cost
+ vector-loop-cost < scalar loop cost.
Note that there is still a hard cut-off to avoid excessive compile-time/code-size
increases, but it is much larger than the original limit.
The performance impact on standard test-suites like SPEC2006/SPEC2006/MultiSource
is mostly neutral, but the new approach can give substantial gains in cases where
we failed to vectorize before due to the over-aggressive cut-offs.
On AArch64 with -O3, I didn't observe any regressions outside the noise level (<0.4%)
and there are the following execution time improvements. Both `IRSmk` and `srad` are relatively short running, but the changes are far above the noise level for them on my benchmark system.
```
CFP2006/447.dealII/447.dealII -1.9%
CINT2017rate/525.x264_r/525.x264_r -2.2%
ASC_Sequoia/IRSmk/IRSmk -9.2%
Rodinia/srad/srad -36.1%
```
`size` regressions on AArch64 with -O3 are
```
MultiSource/Applications/hbd/hbd 90256.00 106768.00 18.3%
MultiSourc...ks/ASCI_Purple/SMG2000/smg2000 240676.00 257268.00 6.9%
MultiSourc...enchmarks/mafft/pairlocalalign 472603.00 489131.00 3.5%
External/S...2017rate/525.x264_r/525.x264_r 613831.00 630343.00 2.7%
External/S...NT2006/464.h264ref/464.h264ref 818920.00 835448.00 2.0%
External/S...te/538.imagick_r/538.imagick_r 1994730.00 2027754.00 1.7%
MultiSourc...nchmarks/tramp3d-v4/tramp3d-v4 1236471.00 1253015.00 1.3%
MultiSource/Applications/oggenc/oggenc 2108147.00 2124675.00 0.8%
External/S.../CFP2006/447.dealII/447.dealII 4742999.00 4759559.00 0.3%
External/S...rate/510.parest_r/510.parest_r 14206377.00 14239433.00 0.2%
```
Reviewed By: lebedev.ri, ebrevnov, dmgreen
Differential Revision: https://reviews.llvm.org/D109368
This patch slightly extends the limit on the RecursionMaxDepth inside
the SLP vectorizer. It does it only when it hits a load (or zext/sext of
a load), which allows it to peek through in the places where it will be
the most valuable, without ballooning out the O(..) by any 2^n factors.
Differential Revision: https://reviews.llvm.org/D122148
This in an extension to the code added in D123911 which added vector
combine folding of shuffle-select patterns, attempting to reduce the
total amount of shuffling required in patterns like:
%x = shuffle %i1, %i2
%y = shuffle %i1, %i2
%a = binop %x, %y
%b = binop %x, %y
shuffle %a, %b, selectmask
This patch extends the handing of shuffles that are dependent on one
another, which can arise from the SLP vectorizer, as-in:
%x = shuffle %i1, %i2
%y = shuffle %x
The input shuffles can also be emitted, in which case they are treated
like identity shuffles. This patch also attempts to calculate a better
ordering of input shuffles, which can help getting lower cost input
shuffles, pushing complex shuffles further down the tree.
Differential Revision: https://reviews.llvm.org/D128732
The moved helpers are only used for codegen. It will allow moving the
remaining ::execute implementations out of LoopVectorize.cpp.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D128657
At the moment, the same VPlan can be used code generation of both the
main vector and epilogue vector loop. This can lead to wrong results, if
the plan is optimized based on the VF of the main vector loop and then
re-used for the epilogue loop.
One example where this is problematic is if the scalar loops need to
execute at least one iteration, e.g. due to interleave groups.
To prevent mis-compiles in the short-term, disable optimizing exit
conditions for VPlans when using epilogue vectorization. The proper fix
is to avoid re-using the same plan for both loops, which will require
support for cloning plans first.
Fixes#56319.
The moved helpers are only used for codegen. It will allow moving the
remaining ::execute implementations out of LoopVectorize.cpp.
Depends on D127966.
Depends on D127965.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D127968
At the moment LoopVersioning is only created for inner-loop
vectorization. This patch moves it to LVP::execute, which means it will
also be added for epilogue vectorization. As a consequence, the proper
noalias metadata is now also added to epilogue vector loops.
LVer will be moved to VPTransformState as follow-up.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D127966
In some cases, there may be widened users of inductions even though the
plan includes the scalar VF. In those cases, make sure we still replace
the VPWidenIntOrFpInductionRecipe with scalar steps, as otherwise we may
try to execute a VPWidenIntOrFpInductionRecipe with a scalar VF.
Alternatively the patch could also split the range if needed.
This fixes a crash exposed by D123720.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D128755
If the root order itself does not require reordering, we can just
remove its reorder mask safely (e.g., if the root node is a vector of
phis). But if this node is used as an operand in the graph, we cannot
delete the reordering, need to keep it. Otherwise the graph nodes are
not synchronized with the operands. It may cause an extra gather
instruction(s) or a compiler crash.
Also, need to be very careful when selecting the gather nodes for
reordering since there might several gather nodes with the same scalars
and we can try to reorder just the same node many times instead of
different nodes.
Differential Revision: https://reviews.llvm.org/D128680
This patch moves the code for recipe implementations to a separate file.
The benefits are:
* Keep VPlan.cpp smaller => faster compile-time during parallel builds.
* Keep code for logical units together
As a follow-up I am also planning on moving all ::execute
implemetnations from LoopVectorize.cpp over to the new file, which
should help to reduce the size of the file a bit.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D127965
`commonAlignment` is a shortcut to pick the smallest of two `Align`
objects. As-is it doesn't bring much value compared to `std::min`.
Differential Revision: https://reviews.llvm.org/D128345
This change is a bit subtle. If we have a type like <vscale x 1 x i64>, the vectorizer will currently reject vectorization. The reason is that a type like <1 x i64> is likely to get simply rescalarized, and the vectorizer doesn't want to be in the game of simple unrolling.
(I've given the example in terms of 1 x types which use a single register, but the same issue exists for any N x types which use N registers. e.g. RISCV LMULs.)
This change distinguishes scalable types from fixed types under the reasoning that converting to a scalable type isn't unrolling. Because the actual vscale isn't known until runtime, using a vscale type is potentially very profitable.
This makes an important, but unchecked, assumption. Specifically, the scalable type is assumed to only be legal per the cost model if there's actually a scalable register class which is distinct from the scalar domain. This is, to my knowledge, true for all targets which return non-invalid costs for scalable vector ops today, but in theory, we could have a target decide to lower scalable to fixed length vector or even scalar registers. If that ever happens, we'd need to revisit this code.
In practice, this patch unblocks scalable vectorization for ELEN types on RISCV.
Let me sketch one alternate implementation I considered. We could have restricted this to when we know a minimum value for vscale. Specifically, for the default +v extension for RISCV, we actually know that vscale >= 2 for ELEN types. However, doing it this way means we can't generate scalable vectors when using the various embedded vector extensions which have a minimum vscale of 1.
Differential Revision: https://reviews.llvm.org/D128542
Improved/fixed cost modeling for shuffles by providing masks, improved
cost model for non-identity insertelements.
Differential Revision: https://reviews.llvm.org/D115462
This patch updates LV to generate runtime after the VF & IC are selected. It
allows deciding whether to vectorize with runtime checks or not based on
their cost compared to the vector loop.
It also updates VectorizationFactor to include the scalar cost.
Reviewed By: lebedev.ri, dmgreen
Differential Revision: https://reviews.llvm.org/D75981
If we have an unaligned uniform store, then when costing a scalable VF we can't emit code to scalarize it. (Well, we could, but we haven't implemented that case.) This change replaces an assert with a cost-model bailout such that we reject vectorization with the scalable VF instead of crashing.
If the masked gather nodes must be reordered, we can just reorder
scalars, just like for gather nodes. But if the node contains reused
scalars, it must be handled same way as a regular vectorizable node,
since need to reorder reused mask, not the scalars directly.
Differential Revision: https://reviews.llvm.org/D128360
This reverts commit cac60940b771a0685d058a5b471c84cea05fdc46.
Caused -Os -fsanitize=memory -march=haswell miscompile to pytorch/cpuinfo.
See my latest comment (may update) on D115462.
This reverts commit f1ee2738b3d70fea803ac1f3401c2fc9f61e514a.
Revert due to the revert of a dependent commit `[SLP]Improve shuffles cost estimation where possible.`
createInductionResumeValues creates a phi node placeholder
without filling incoming values. Then it generates the incoming values.
It includes triggering of SCEV expander which may invoke SSAUpdater.
SSAUpdater has an optimization to detect number of predecessors
basing on incoming values if there is phi node.
In case phi node is not filled with incoming values - the number of predecessors
is detected as 0 and this leads to segmentation fault.
In other words SSAUpdater expects that phi is in good shape while
LoopVectorizer breaks this requirement.
The fix is just prepare all incoming values first and then build a phi node.
Reviewed By: fhahn
Subscribers: llvm-commits
Differential Revision: https://reviews.llvm.org/D128033
