The input LoopCost value can be zero, but if so it should be recalculated with the current VF. After that it should always be non-zero.
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This reduces the number of parameters we need to pass in and they seem a
natural fit in LoopVectorizationCostModel. Also simplifies things for
D59995.
As a follow up refactoring, we could only expose a expose a
shouldUseVectorIntrinsic() helper in LoopVectorizationCostModel, instead
of calling getVectorCallCost/getVectorIntrinsicCost in
InnerLoopVectorizer/VPRecipeBuilder.
Reviewers: Ayal, hsaito, dcaballe, rengolin
Reviewed By: rengolin
Differential Revision: https://reviews.llvm.org/D61638
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Summary:
Preserve MemorySSA in LoopSimplify, in the old pass manager, if the analysis is available.
Do not preserve it in the new pass manager.
Update tests.
Subscribers: nemanjai, jlebar, javed.absar, Prazek, kbarton, zzheng, jsji, llvm-commits, george.burgess.iv, chandlerc
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D60833
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Summary:
Bug: https://bugs.llvm.org/show_bug.cgi?id=39024
The bug reports that a vectorized loop is stepped through 4 times and each step through the loop seemed to show a different path. I found two problems here:
A) An incorrect line number on a preheader block (for.body.preheader) instruction causes a step into the loop before it begins.
B) Instructions in the middle block have different line numbers which give the impression of another iteration.
In this patch I give all of the middle block instructions the line number of the scalar loop latch terminator branch. This seems to provide the smoothest debugging experience because the vectorized loops will always end on this line before dropping into the scalar loop. To solve problem A I have altered llvm::SplitBlockPredecessors to accommodate loop header blocks.
Reviewers: samsonov, vsk, aprantl, probinson, anemet, hfinkel
Reviewed By: hfinkel
Subscribers: bjope, jmellorcrummey, hfinkel, gbedwell, hiraditya, zzheng, llvm-commits
Tags: #llvm, #debug-info
Differential Revision: https://reviews.llvm.org/D60831
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Summary:
When refactoring vectorization flags, vectorization was disabled by default in the new pass manager.
This patch re-enables is for both managers, and changes the assumptions opt makes, based on the new defaults.
Comments in opt.cpp should clarify the intended use of all flags to enable/disable vectorization.
Reviewers: chandlerc, jgorbe
Subscribers: jlebar, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D61091
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Summary:
Trying to add the plumbing necessary to add tuning options to the new pass manager.
Testing with the flags for loop vectorize.
Reviewers: chandlerc
Subscribers: sanjoy, mehdi_amini, jlebar, steven_wu, dexonsmith, dang, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D59723
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Summary:
Enable some of the existing size optimizations for cold code under PGO.
A ~5% code size saving in big internal app under PGO.
The way it gets BFI/PSI is discussed in the RFC thread
http://lists.llvm.org/pipermail/llvm-dev/2019-March/130894.html
Note it doesn't currently touch loop passes.
Reviewers: davidxl, eraman
Reviewed By: eraman
Subscribers: mgorny, javed.absar, smeenai, mehdi_amini, eraman, zzheng, steven_wu, dexonsmith, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D59514
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1. Use computed VF for stress testing.
2. If the computed VF does not produce vector code (VF smaller than 2), force VF to be 4.
3. Test vectorization of i64 data on AArch64 to make sure we generate VF != 4 (on X86 that was already tested on AVX).
Patch by Francesco Petrogalli <francesco.petrogalli@arm.com>
Differential Revision: https://reviews.llvm.org/D59952
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Bug: https://bugs.llvm.org/show_bug.cgi?id=41180
In the bug test case the debug location was missing for the cmp instruction in
the "middle block" BB. This patch fixes the bug by copying the debug location
from the cmp of the scalar loop's terminator branch, if it exists.
The patch also fixes the debug location on the subsequent branch instruction.
It was previously using the location of the of the original loop's pre-header
block terminator. Both of these instructions will now map to the source line of
the conditional branch in the original loop.
A regression test has been added that covers these issues.
Patch by Orlando Cazalet-Hyams!
Differential Revision: https://reviews.llvm.org/D59944
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With this change, the VPlan native path is triggered with the directive:
#pragma clang loop vectorize(enable)
There is no need to specify the vectorize_width(N) clause.
Patch by Francesco Petrogalli <francesco.petrogalli@arm.com>
Differential Revision: https://reviews.llvm.org/D57598
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Change from original commit: move test (that uses an X86 triple) into the X86
subdirectory.
Original description:
Gating vectorizing reductions on *all* fastmath flags seems unnecessary;
`reassoc` should be sufficient.
Reviewers: tvvikram, mkuper, kristof.beyls, sdesmalen, Ayal
Reviewed By: sdesmalen
Subscribers: dcaballe, huntergr, jmolloy, mcrosier, jlebar, bixia, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D57728
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Add plumbing to get MemorySSA in the remaining loop passes.
Also update unit test to add the dependency.
[EnableMSSALoopDependency remains disabled].
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Summary:
Renamed setBaseDiscriminator to cloneWithBaseDiscriminator, to match
similar APIs. Also changed its behavior to copy over the other
discriminator components, instead of eliding them.
Renamed cloneWithDuplicationFactor to
cloneByMultiplyingDuplicationFactor, which more closely matches what
this API does.
Reviewers: dblaikie, wmi
Reviewed By: dblaikie
Subscribers: zzheng, llvm-commits
Differential Revision: https://reviews.llvm.org/D56220
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VPlan-native path
Context: Patch Series #2 for outer loop vectorization support in LV
using VPlan. (RFC:
http://lists.llvm.org/pipermail/llvm-dev/2017-December/119523.html).
Patch series #2 checks that inner loops are still trivially lock-step
among all vector elements. Non-loop branches are blindly assumed as
divergent.
Changes here implement VPlan based predication algorithm to compute
predicates for blocks that need predication. Predicates are computed
for the VPLoop region in reverse post order. A block's predicate is
computed as OR of the masks of all incoming edges. The mask for an
incoming edge is computed as AND of predecessor block's predicate and
either predecessor's Condition bit or NOT(Condition bit) depending on
whether the edge from predecessor block to the current block is true
or false edge.
Reviewers: fhahn, rengolin, hsaito, dcaballe
Reviewed By: fhahn
Patch by Satish Guggilla, thanks!
Differential Revision: https://reviews.llvm.org/D53349
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to reflect the new license.
We understand that people may be surprised that we're moving the header
entirely to discuss the new license. We checked this carefully with the
Foundation's lawyer and we believe this is the correct approach.
Essentially, all code in the project is now made available by the LLVM
project under our new license, so you will see that the license headers
include that license only. Some of our contributors have contributed
code under our old license, and accordingly, we have retained a copy of
our old license notice in the top-level files in each project and
repository.
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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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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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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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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
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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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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
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@342197 91177308-0d34-0410-b5e6-96231b3b80d8
