Summary:
Added a pair of APIs for encoding/decoding the 3 components of a DWARF discriminator described in http://lists.llvm.org/pipermail/llvm-dev/2016-October/106532.html: the base discriminator, the duplication factor (useful in profile-guided optimization) and the copy index (used to identify copies of code in cases like loop unrolling)
The encoding packs 3 unsigned values in 32 bits. This CL addresses 2 issues:
- communicates overflow back to the user
- supports encoding all 3 components together. Current APIs assume a sequencing of events. For example, creating a new discriminator based on an existing one by changing the base discriminator was not supported.
Reviewers: davidxl, danielcdh, wmi, dblaikie
Reviewed By: dblaikie
Subscribers: zzheng, dmgreen, aprantl, JDevlieghere, llvm-commits
Differential Revision: https://reviews.llvm.org/D55681
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Rename:
NoUnrolling to InterleaveOnlyWhenForced
and
AlwaysVectorize to !VectorizeOnlyWhenForced
Contrary to what the name 'AlwaysVectorize' suggests, it does not
unconditionally vectorize all loops, but applies a cost model to
determine whether vectorization is profitable to all loops. Hence,
passing false will disable the cost model, except when a loop is marked
with llvm.loop.vectorize.enable. The 'OnlyWhenForced' suffix (suggested
by @hfinkel in D55716) better matches this behavior.
Similarly, 'NoUnrolling' disables the profitability cost model for
interleaving (a term to distinguish it from unrolling by the
LoopUnrollPass); rename it for consistency.
Differential Revision: https://reviews.llvm.org/D55785
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When multiple loop transformation are defined in a loop's metadata, their order of execution is defined by the order of their respective passes in the pass pipeline. For instance, e.g.
#pragma clang loop unroll_and_jam(enable)
#pragma clang loop distribute(enable)
is the same as
#pragma clang loop distribute(enable)
#pragma clang loop unroll_and_jam(enable)
and will try to loop-distribute before Unroll-And-Jam because the LoopDistribute pass is scheduled after UnrollAndJam pass. UnrollAndJamPass only supports one inner loop, i.e. it will necessarily fail after loop distribution. It is not possible to specify another execution order. Also,t the order of passes in the pipeline is subject to change between versions of LLVM, optimization options and which pass manager is used.
This patch adds 'followup' attributes to various loop transformation passes. These attributes define which attributes the resulting loop of a transformation should have. For instance,
!0 = !{!0, !1, !2}
!1 = !{!"llvm.loop.unroll_and_jam.enable"}
!2 = !{!"llvm.loop.unroll_and_jam.followup_inner", !3}
!3 = !{!"llvm.loop.distribute.enable"}
defines a loop ID (!0) to be unrolled-and-jammed (!1) and then the attribute !3 to be added to the jammed inner loop, which contains the instruction to distribute the inner loop.
Currently, in both pass managers, pass execution is in a fixed order and UnrollAndJamPass will not execute again after LoopDistribute. We hope to fix this in the future by allowing pass managers to run passes until a fixpoint is reached, use Polly to perform these transformations, or add a loop transformation pass which takes the order issue into account.
For mandatory/forced transformations (e.g. by having been declared by #pragma omp simd), the user must be notified when a transformation could not be performed. It is not possible that the responsible pass emits such a warning because the transformation might be 'hidden' in a followup attribute when it is executed, or it is not present in the pipeline at all. For this reason, this patche introduces a WarnMissedTransformations pass, to warn about orphaned transformations.
Since this changes the user-visible diagnostic message when a transformation is applied, two test cases in the clang repository need to be updated.
To ensure that no other transformation is executed before the intended one, the attribute `llvm.loop.disable_nonforced` can be added which should disable transformation heuristics before the intended transformation is applied. E.g. it would be surprising if a loop is distributed before a #pragma unroll_and_jam is applied.
With more supported code transformations (loop fusion, interchange, stripmining, offloading, etc.), transformations can be used as building blocks for more complex transformations (e.g. stripmining+stripmining+interchange -> tiling).
Reviewed By: hfinkel, dmgreen
Differential Revision: https://reviews.llvm.org/D49281
Differential Revision: https://reviews.llvm.org/D55288
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Summary:
An additional fix for PR39774. Need to update the references for the
RedcutionRoot instruction when it is replaced during the vectorization
phase to avoid compiler crash on reduction vectorization.
Reviewers: RKSimon, spatel
Subscribers: llvm-commits
Differential Revision: https://reviews.llvm.org/D55017
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Summary:
If the original reduction root instruction was vectorized, it might be
removed from the tree. It means that the insertion point may become
invalidated and the whole vectorization of the reduction leads to the
incorrect output result.
The ReductionRoot instruction must be marked as externally used so it
could not be removed. Otherwise it might cause inconsistency with the
cost model and we may end up with too optimistic optimization.
Reviewers: RKSimon, spatel, hfinkel, mkuper
Subscribers: llvm-commits
Differential Revision: https://reviews.llvm.org/D54955
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Add methods to BasicBlock which make it easier to efficiently check
whether a block has N (or more) predecessors.
This can be more efficient than using pred_size(), which is a linear
time operation.
We might consider adding similar methods for successors. I haven't done
so in this patch because succ_size() is already O(1).
With this patch applied, I measured a 0.065% compile-time reduction in
user time for running `opt -O3` on the sqlite3 amalgamation (30 trials).
The change in mergeStoreIntoSuccessor alone saves 45 million linked list
iterations in a stage2 Release build of llc.
See llvm.org/PR39702 for a harder but more general way of achieving
similar results.
Differential Revision: https://reviews.llvm.org/D54686
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Summary:
Currently, when vectorizing stores to uniform addresses, the only
instance we prevent vectorization is if there are multiple stores to the
same uniform address causing an unsafe dependency.
This patch teaches LAA to avoid vectorizing loops that have an unsafe
cross-iteration dependency between a load and a store to the same uniform address.
Fixes PR39653.
Reviewers: Ayal, efriedma
Subscribers: rkruppe, llvm-commits
Differential Revision: https://reviews.llvm.org/D54538
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This patch adds an initial implementation of the look-ahead SLP tree
construction described in 'Look-Ahead SLP: Auto-vectorization in the Presence
of Commutative Operations, CGO 2018 by Vasileios Porpodas, Rodrigo C. O. Rocha,
Luís F. W. Góes'.
It returns an SLP tree represented as VPInstructions, with combined
instructions represented as a single, wider VPInstruction.
This initial version does not support instructions with multiple
different users (either inside or outside the SLP tree) or
non-instruction operands; it won't generate any shuffles or
insertelement instructions.
It also just adds the analysis that builds an SLP tree rooted in a set
of stores. It does not include any cost modeling or memory legality
checks. The plan is to integrate it with VPlan based cost modeling, once
available and to only apply it to operations that can be widened.
A follow-up patch will add a support for replacing instructions in a
VPlan with their SLP counter parts.
Reviewers: Ayal, mssimpso, rengolin, mkuper, hfinkel, hsaito, dcaballe, vporpo, RKSimon, ABataev
Reviewed By: rengolin
Differential Revision: https://reviews.llvm.org/D4949
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This patch turns InterleaveGroup into a template with the instruction type
being a template parameter. It also adds a VPInterleavedAccessInfo class, which
only contains a mapping from VPInstructions to their respective InterleaveGroup.
As we do not have access to scalar evolution in VPlan, we can re-use
convert InterleavedAccessInfo to VPInterleavedAccess info.
Reviewers: Ayal, mssimpso, hfinkel, dcaballe, rengolin, mkuper, hsaito
Reviewed By: rengolin
Differential Revision: https://reviews.llvm.org/D49489
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Instead of defaulting to a cost = 1, expand to element extract/insert like we do for other shuffles.
This exposes an issue in LoopVectorize which could call SK_ExtractSubvector with a scalar subvector type.
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Fix PR39417, PR39497
The loop vectorizer may generate runtime SCEV checks for overflow and stride==1
cases, leading to execution of original scalar loop. The latter is forbidden
when optimizing for size. An assert introduced in r344743 triggered the above
PR's showing it does happen. This patch fixes this behavior by preventing
vectorization in such cases.
Differential Revision: https://reviews.llvm.org/D53612
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optsize using masked wide loads
Under Opt for Size, the vectorizer does not vectorize interleave-groups that
have gaps at the end of the group (such as a loop that reads only the even
elements: a[2*i]) because that implies that we'll require a scalar epilogue
(which is not allowed under Opt for Size). This patch extends the support for
masked-interleave-groups (introduced by D53011 for conditional accesses) to
also cover the case of gaps in a group of loads; Targets that enable the
masked-interleave-group feature don't have to invalidate interleave-groups of
loads with gaps; they could now use masked wide-loads and shuffles (if that's
what the cost model selects).
Reviewers: Ayal, hsaito, dcaballe, fhahn
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D53668
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Correct costings of SK_ExtractSubvector requires the SubTy argument to indicate the type/size of the extracted subvector.
Unlike the rest of the shuffle kinds this means that the main Ty argument represents the source vector type not the destination!
I've done my best to fix a number of vectorizer uses:
SLP - the reduction epilogue costs should be using a SK_PermuteSingleSrc shuffle as these all occur at the hardware vector width - we're not extracting (illegal) subvector types. This is causing the cost model diffs as SK_ExtractSubvector costs are poorly handled and tend to just return 1 at the moment.
LV - I'm not clear on what the SK_ExtractSubvector should represents for recurrences - I've used a <1 x ?> subvector extraction as that seems to match the VF delta.
Differential Revision: https://reviews.llvm.org/D53573
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This commit is a combination of two patches:
* "Fix in getScalarizationOverhead()"
If target returns false in TTI.prefersVectorizedAddressing(), it means the
address registers will not need to be extracted. Therefore, there should
be no operands scalarization overhead for a load instruction.
* "Don't pass the instruction pointer from getMemInstScalarizationCost."
Since VF is always > 1, this is a cost query for an instruction in the
vectorized loop and it should not be evaluated within the scalar
context of the instruction.
Review: Ulrich Weigand, Hal Finkel
https://reviews.llvm.org/D52351https://reviews.llvm.org/D52417
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masked-interleaving is enabled
Enable interleave-groups under fold-tail scenario for Opt for size compilation;
D50480 added support for vectorizing loops of arbitrary trip-count without a
remiander, which in turn makes everything in the loop conditional, including
interleave-groups if any. It therefore invalidated all interleave-groups
because we didn't have support for vectorizing predicated interleaved-groups
at the time. In the meantime, D53011 introduced this support, so we don't
have to invalidate interleave-groups when masked-interleaved support is enabled.
Reviewers: Ayal, hsaito, dcaballe, fhahn
Reviewed By: hsaito
Differential Revision: https://reviews.llvm.org/D53559
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Expand arithmetic reduction to include mul/and/or/xor instructions.
This patch just fixes the SLPVectorizer - the effective reduction costs for AVX1+ are still poor (see rL344846) and will need to be improved before SLP sees this as a valid transform - but we can already see the effect on SSE2 tests.
This partially helps PR37731, but doesn't fix it all as it still falls over on the extraction/reduction order for some reason.
Differential Revision: https://reviews.llvm.org/D53473
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optimizing for size
LV is careful to respect -Os and not to create a scalar epilog in all cases
(runtime tests, trip-counts that require a remainder loop) except for peeling
due to gaps in interleave-groups. This patch fixes that; -Os will now have us
invalidate such interleave-groups and vectorize without an epilog.
The patch also removes a related FIXME comment that is now obsolete, and was
also inaccurate:
"FIXME: return None if loop requiresScalarEpilog(<MaxVF>), or look for a smaller
MaxVF that does not require a scalar epilog."
(requiresScalarEpilog() has nothing to do with VF).
Reviewers: Ayal, hsaito, dcaballe, fhahn
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D53420
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When optimizing for size, a loop is vectorized only if the resulting vector loop
completely replaces the original scalar loop. This holds if no runtime guards
are needed, if the original trip-count TC does not overflow, and if TC is a
known constant that is a multiple of the VF. The last two TC-related conditions
can be overcome by
1. rounding the trip-count of the vector loop up from TC to a multiple of VF;
2. masking the vector body under a newly introduced "if (i <= TC-1)" condition.
The patch allows loops with arbitrary trip counts to be vectorized under -Os,
subject to the existing cost model considerations. It also applies to loops with
small trip counts (under -O2) which are currently handled as if under -Os.
The patch does not handle loops with reductions, live-outs, or w/o a primary
induction variable, and disallows interleave groups.
(Third, final and main part of -)
Differential Revision: https://reviews.llvm.org/D50480
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Summary:
Teach vectorizer about vectorizing variant value stores to uniform
address. Similar to rL343028, we do not allow vectorization if we have
multiple stores to the same uniform address.
Cost model already has the change for considering the extract
instruction cost for a variant value store. See added test cases for how
vectorization is done.
The patch also contains changes to the ORE messages.
Reviewers: Ayal, mkuper, anemet, hsaito
Subscribers: rkruppe, llvm-commits
Differential Revision: https://reviews.llvm.org/D52656
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This removes the primary remaining API producing `TerminatorInst` which
will reduce the rate at which code is introduced trying to use it and
generally make it much easier to remove the remaining APIs across the
codebase.
Also clean up some of the stragglers that the previous mechanical update
of variables missed.
Users of LLVM and out-of-tree code generally will need to update any
explicit variable types to handle this. Replacing `TerminatorInst` with
`Instruction` (or `auto`) almost always works. Most of these edits were
made in prior commits using the perl one-liner:
```
perl -i -ple 's/TerminatorInst(\b.* = .*getTerminator\(\))/Instruction\1/g'
```
This also my break some rare use cases where people overload for both
`Instruction` and `TerminatorInst`, but these should be easily fixed by
removing the `TerminatorInst` overload.
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by `getTerminator()` calls instead be declared as `Instruction`.
This is the biggest remaining chunk of the usage of `getTerminator()`
that insists on the narrow type and so is an easy batch of updates.
Several files saw more extensive updates where this would cascade to
requiring API updates within the file to use `Instruction` instead of
`TerminatorInst`. All of these were trivial in nature (pervasively using
`Instruction` instead just worked).
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interleave-group
The vectorizer currently does not attempt to create interleave-groups that
contain predicated loads/stores; predicated strided accesses can currently be
vectorized only using masked gather/scatter or scalarization. This patch makes
predicated loads/stores candidates for forming interleave-groups during the
Loop-Vectorizer's analysis, and adds the proper support for masked-interleave-
groups to the Loop-Vectorizer's planning and transformation stages. The patch
also extends the TTI API to allow querying the cost of masked interleave groups
(which each target can control); Targets that support masked vector loads/
stores may choose to enable this feature and allow vectorizing predicated
strided loads/stores using masked wide loads/stores and shuffles.
Reviewers: Ayal, hsaito, dcaballe, fhahn, javed.absar
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D53011
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We assign indices sequentially for seen instructions, so we can just use
a vector and push back the seen instructions. No need for using a
DenseMap.
Reviewers: hsaito, rengolin, nadav, dcaballe
Reviewed By: rengolin
Differential Revision: https://reviews.llvm.org/D53089
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We can avoid doing some unnecessary work by skipping debug instructions
in a few loops. It also helps to ensure debug instructions do not
prevent vectorization, although I do not have any concrete test cases
for that.
Reviewers: rengolin, hsaito, dcaballe, aprantl, vsk
Reviewed By: rengolin, dcaballe
Differential Revision: https://reviews.llvm.org/D53091
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At the point when we perform `emitTransformedIndex`, we have a broken IR (in
particular, we have Phis for which not every incoming value is properly set). On
such IR, it is illegal to create SCEV expressions, because their internal
simplification process may try to prove some predicates and break when it
stumbles across some broken IR.
The only purpose of using SCEV in this particular place is attempt to simplify
the generated code slightly. It seems that the result isn't worth it, because
some trivial cases (like addition of zero and multiplication by 1) can be
handled separately if needed, but more generally InstCombine is able to achieve
the goals we want to achieve by using SCEV.
This patch fixes a functional crash described in PR39160, and as side-effect it
also generates a bit smarter code in some simple cases. It also may cause some
optimality loss (i.e. we will now generate `mul` by power of `2` instead of
shift etc), but there is nothing what InstCombine could not handle later. In
case of dire need, we can support more trivial cases just in place.
Note that this patch only fixes one particular case of the general problem that
LV misuses SCEV, attempting to create SCEVs or prove predicates on invalid IR.
The general solution, however, seems complex enough.
Differential Revision: https://reviews.llvm.org/D52881
Reviewed By: fhahn, hsaito
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@343954 91177308-0d34-0410-b5e6-96231b3b80d8
Call getOperandInfo() instead of using (near) duplicated code in
LoopVectorizationCostModel::getInstructionCost().
This gets the OperandValueKind and OperandValueProperties values for a Value
passed as operand to an arithmetic instruction.
getOperandInfo() used to be a static method in TargetTransformInfo.cpp, but
is now instead a public member.
Review: Florian Hahn
https://reviews.llvm.org/D52883
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Summary:
We are overly conservative in loop vectorizer with respect to stores to loop
invariant addresses.
More details in https://bugs.llvm.org/show_bug.cgi?id=38546
This is the first part of the fix where we start with vectorizing loop invariant
values to loop invariant addresses.
This also includes changes to ORE for stores to invariant address.
Reviewers: anemet, Ayal, mkuper, mssimpso
Subscribers: llvm-commits
Differential Revision: https://reviews.llvm.org/D50665
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Support for vectorizing loops with secondary floating-point induction
variables was added in r276554. A primary integer IV is still required
for vectorization to be done. If an FP IV was found, but no integer IV
was found at all (primary or secondary), the attempt to vectorize still
went forward, causing a compiler-crash. This change abandons that
attempt when no integer IV is found. (Vectorizing FP-only cases like
this, rather than bailing out, is discussed as possible future work
in D52327.)
See PR38800 for more information.
Differential Revision: https://reviews.llvm.org/D52327
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This was checking the hardcoded address space 0 for the stack.
Additionally, this should be checking for legality with
the adjusted alignment, so defer the alignment check.
Also try to split if the unaligned access isn't allowed.
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Summary:
[VPlan] Implement vector code generation support for simple outer loops.
Context: Patch Series #1 for outer loop vectorization support in LV using VPlan. (RFC: http://lists.llvm.org/pipermail/llvm-dev/2017-December/119523.html).
This patch introduces vector code generation support for simple outer loops that are currently supported in the VPlanNativePath. Changes here essentially do the following:
- force vector code generation using explicit vectorize_width
- add conservative early returns in cost model and other places for VPlanNativePath
- add code for setting up outer loop inductions
- support for widening non-induction PHIs that can result from inner loops and uniform conditional branches
- support for generating uniform inner branches
We plan to add a handful C outer loop executable tests once the initial code generation support is committed. This patch is expected to be NFC for the inner loop vectorizer path. Since we are moving in the direction of supporting outer loop vectorization in LV, it may also be time to rename classes such as InnerLoopVectorizer.
Reviewers: fhahn, rengolin, hsaito, dcaballe, mkuper, hfinkel, Ayal
Reviewed By: fhahn, hsaito
Subscribers: dmgreen, bollu, tschuett, rkruppe, rogfer01, llvm-commits
Differential Revision: https://reviews.llvm.org/D50820
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Move the 2 classes out of LoopVectorize.cpp to make it easier to re-use
them for VPlan outside LoopVectorize.cpp
Reviewers: Ayal, mssimpso, rengolin, dcaballe, mkuper, hsaito, hfinkel, xbolva00
Reviewed By: rengolin, xbolva00
Differential Revision: https://reviews.llvm.org/D49488
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Summary:
Move InductionDescriptor::transform() routine from LoopUtils to its only uses in LoopVectorize.cpp.
Specifically, the function is renamed as InnerLoopVectorizer::emitTransformedIndex().
This is a child to D51153.
Reviewers: dmgreen, llvm-commits
Reviewed By: dmgreen
Differential Revision: https://reviews.llvm.org/D51837
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Fix a latent bug in loop vectorizer which generates incorrect code for
memory accesses that are executed conditionally. As pointed in review,
this bug definitely affects uniform loads and may affect conditional
stores that should have turned into scatters as well).
The code gen for conditionally executed uniform loads on architectures
that support masked gather instructions is broken.
Without this patch, we were unconditionally executing the *conditional*
load in the vectorized version.
This patch does the following:
1. Uniform conditional loads on architectures with gather support will
have correct code generated. In particular, the cost model
(setCostBasedWideningDecision) is fixed.
2. For the recipes which are handled after the widening decision is set,
we use the isScalarWithPredication(I, VF) form which is added in the
patch.
3. Fix the vectorization cost model for scalarization
(getMemInstScalarizationCost): implement and use isPredicatedInst to
identify *all* predicated instructions, not just scalar+predicated. So,
now the cost for scalarization will be increased for maskedloads/stores
and gather/scatter operations. In short, we should be choosing the
gather/scatter in place of scalarization on archs where it is
profitable.
4. We needed to weaken the assert in useEmulatedMaskMemRefHack.
Reviewers: Ayal, hsaito, mkuper
Differential Revision: https://reviews.llvm.org/D51313
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@341673 91177308-0d34-0410-b5e6-96231b3b80d8
This is fix for PR38786.
First order recurrence phis were incorrectly treated as uniform,
which caused them to be vectorized as uniform instructions.
Patch by Ayal Zaks and Orivej Desh!
Reviewed by: Anna
Differential Revision: https://reviews.llvm.org/D51639
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@341416 91177308-0d34-0410-b5e6-96231b3b80d8
Summary:
Avoid "count" if possible -> use "find" to check for the existence of keys.
Passed llvm test suite.
Reviewers: fhahn, dcaballe, mkuper, rengolin
Reviewed By: fhahn
Subscribers: llvm-commits
Differential Revision: https://reviews.llvm.org/D51054
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@340563 91177308-0d34-0410-b5e6-96231b3b80d8
Summary:
Follow up change to rL339703, where we now vectorize loops with non-phi
instructions used outside the loop. Note that the cyclic dependency
identification occurs when identifying reduction/induction vars.
We also need to identify that we do not allow users where the PSCEV information
within and outside the loop are different. This was the fix added in rL307837
for PR33706.
Reviewers: Ayal, mkuper, fhahn
Subscribers: javed.absar, llvm-commits
Differential Revision: https://reviews.llvm.org/D50778
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@340278 91177308-0d34-0410-b5e6-96231b3b80d8
