Use SetVector instead of SmallPtrSet for external definitions created for VPlan.
Doing this can help avoid non-determinism caused by iterating over unordered containers.
This bug was found with reverse iteration turning on,
--extra-llvm-cmake-variables="-DLLVM_REVERSE_ITERATION=ON".
Failing LLVM-Unit test VPRecipeTest.dump.
Reviewed By: MaskRay
Differential Revision: https://reviews.llvm.org/D99544
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 is a 2nd try of:
3c8473ba53
which was reverted at:
a26312f9d4
because of crashing.
This version includes extra code and tests to avoid the known
crashing examples as discussed in PR49730.
Original commit message:
As noted in D98152, we need to patch SLP to avoid regressions when
we start canonicalizing to integer min/max intrinsics.
Most of the real work to make this possible was in:
7202f47508
Differential Revision: https://reviews.llvm.org/D98981
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 reverts commit 3c8473ba53 and includes test diffs to
maintain testing status.
There's at least 1 place that was not updated with 7202f47508 ,
so we can crash mismatching select and intrinsics as shown in
PR49730.
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
The SCEV commit b46c085d2b [NFCI] SCEVExpander:
emit intrinsics for integral {u,s}{min,max} SCEV expressions
seems to reveal a new crash in SLPVectorizer.
SLP crashes expecting a SelectInst as an externally used value
but umin() call is found.
The patch relaxes the assumption to make the IR flag propagation safe.
Reviewed By: spatel
Differential Revision: https://reviews.llvm.org/D99328
We do not need to scan further if the upper end or lower end of the
basic block is reached already and the instruction is not found. It
means that the instruction is definitely in the lower part of basic
block or in the upper block relatively.
This should improve compile time for the very big basic blocks.
Differential Revision: https://reviews.llvm.org/D99266
This patch changes the interface to take a RegisterKind, to indicate
whether the register bitwidth of a scalar register, fixed-width vector
register, or scalable vector register must be returned.
Reviewed By: paulwalker-arm
Differential Revision: https://reviews.llvm.org/D98874
We know if the loop contains FP instructions preventing vectorization
after we are done with legality checks. This patch updates the code the
check for un-vectorizable FP operations earlier, to avoid unnecessarily
running the cost model and picking a vectorization factor. It also makes
the code more direct and moves the check to a position where similar
checks are done.
I might be missing something, but I don't see any reason to handle this
check differently to other, similar checks.
Reviewed By: lebedev.ri
Differential Revision: https://reviews.llvm.org/D98633
Added getPointersDiff function to LoopAccessAnalysis and used it instead
direct calculatoin of the distance between pointers and/or
isConsecutiveAccess function in SLP vectorizer to improve compile time
and detection of stores consecutive chains.
Part of D57059
Differential Revision: https://reviews.llvm.org/D98967
Added getPointersDiff function to LoopAccessAnalysis and used it instead
direct calculatoin of the distance between pointers and/or
isConsecutiveAccess function in SLP vectorizer to improve compile time
and detection of stores consecutive chains.
Part of D57059
Differential Revision: https://reviews.llvm.org/D98967
As noted in D98152, we need to patch SLP to avoid regressions when
we start canonicalizing to integer min/max intrinsics.
Most of the real work to make this possible was in:
7202f47508
Differential Revision: https://reviews.llvm.org/D98981
In places where we create a ConstantVector whose elements are a
linear sequence of the form <start, start + 1, start + 2, ...>
I've changed the code to make use of CreateStepVector, which creates
a vector with the sequence <0, 1, 2, ...>, and a vector addition
operation. This patch is a non-functional change, since the output
from the vectoriser remains unchanged for fixed length vectors and
there are existing asserts that still fire when attempting to use
scalable vectors for vectorising induction variables.
In a later patch we will enable support for scalable vectors
in InnerLoopVectorizer::getStepVector(), which relies upon the new
stepvector intrinsic in IRBuilder::CreateStepVector.
Differential Revision: https://reviews.llvm.org/D97861
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.
Make sure we use PowerOf2Floor instead of PowerOf2Ceil when
calculating max number of elements that fits inside a vector
register (otherwise we could end up creating vectors larger
than the maximum vector register size).
Also make sure we honor the min/max VF (as given by TTI or
cmd line parameters) when doing vectorizeStores.
Reviewed By: anton-afanasyev
Differential Revision: https://reviews.llvm.org/D97691
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 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
If SLP vectorizer tries to extend the scheduling region and runs out of
the budget too early, but still extends the region to the new ending
instructions (i.e., it was able to extend the region for the first
instruction in the bundle, but not for the second), the compiler need to
recalculate dependecies in full, just like if the extending was
successfull. Without it, the schedule data chunks may end up with the
wrong number of (unscheduled) dependecies and it may end up with the
incorrect function, where the vectorized instruction does not dominate
on the extractelement instruction.
Differential Revision: https://reviews.llvm.org/D98531
This adds an Mask ArrayRef to getShuffleCost, so that if an exact mask
can be provided a more accurate cost can be provided by the backend.
For example VREV costs could be returned by the ARM backend. This should
be an NFC until then, laying the groundwork for that to be added.
Differential Revision: https://reviews.llvm.org/D98206
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
Current SLP pass has this piece of code that inserts a trunc instruction
after the vectorized instruction. In the case that the vectorized instruction
is a phi node and not the last phi node in the BB, the trunc instruction
will be inserted between two phi nodes, which will trigger verify problem
in debug version or unpredictable error in another pass.
This patch changes the algorithm to 'if the last vectorized instruction
is a phi, insert it after the last phi node in current BB' to fix this problem.
The motivation is to handle integer min/max reductions independently
of whether they are in the current cmp+sel form or the planned intrinsic
form.
We assumed that min/max included a select instruction, but we can
decouple that implementation detail by checking the instructions
themselves rather than relying on the recurrence (reduction) type.
Instead of maintaining a separate map from predicated instructions to
recipes, we can instead directly look at the VP operands. If the operand
comes from a predicated instruction, the operand will be a
VPPredInstPHIRecipe with a VPReplicateRecipe as its operand.
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 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
Associative reduction matcher in SLP begins with select instruction but when
it reached call to llvm.umax (or alike) via def-use chain the latter also matched
as UMax kind. The routine's later code assumes matched instruction to be a select
and thus it merely died on the first encountered cast that did not fit.
Differential Revision: https://reviews.llvm.org/D98432
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
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
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
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'.
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 seems possible.
The motivation is to clean up the interactions between FMF and
function-level attributes in these classes and their callers.
It is possible to merge reuse and reorder shuffles and reduce the total
cost of the vectorization tree/number of final instructions.
Differential Revision: https://reviews.llvm.org/D94992
Huihui Zhang