This patch changes ElementCount so that the Min and Scalable
members are now private and can only be accessed via the get
functions getKnownMinValue() and isScalable(). In addition I've
added some other member functions for more commonly used operations.
Hopefully this makes the class more useful and will reduce the
need for calling getKnownMinValue().
Differential Revision: https://reviews.llvm.org/D86065
Changes:
* Change `ToVectorTy` to deal directly with `ElementCount` instances.
* `VF == 1` replaced with `VF.isScalar()`.
* `VF > 1` and `VF >=2` replaced with `VF.isVector()`.
* `VF <=1` is replaced with `VF.isZero() || VF.isScalar()`.
* Replaced the uses of `llvm::SmallSet<ElementCount, ...>` with
`llvm::SmallSetVector<ElementCount, ...>`. This avoids the need of an
ordering function for the `ElementCount` class.
* Bits and pieces around printing the `ElementCount` to string streams.
To guarantee that this change is a NFC, `VF.Min` and asserts are used
in the following places:
1. When it doesn't make sense to deal with the scalable property, for
example:
a. When computing unrolling factors.
b. When shuffle masks are built for fixed width vector types
In this cases, an
assert(!VF.Scalable && "<mgs>") has been added to make sure we don't
enter coepaths that don't make sense for scalable vectors.
2. When there is a conscious decision to use `FixedVectorType`. These
uses of `FixedVectorType` will likely be removed in favour of
`VectorType` once the vectorizer is generic enough to deal with both
fixed vector types and scalable vector types.
3. When dealing with building constants out of the value of VF, for
example when computing the vectorization `step`, or building vectors
of indices. These operation _make sense_ for scalable vectors too,
but changing the code in these places to be generic and make it work
for scalable vectors is to be submitted in a separate patch, as it is
a functional change.
4. When building the potential VFs in VPlan. Making the VPlan generic
enough to handle scalable vectorization factors is a functional change
that needs a separate patch. See for example `void
LoopVectorizationPlanner::buildVPlans(unsigned MinVF, unsigned
MaxVF)`.
5. The class `IntrinsicCostAttribute`: this class still uses `unsigned
VF` as updating the field to use `ElementCount` woudl require changes
that could result in changing the behavior of the compiler. Will be done
in a separate patch.
7. When dealing with user input for forcing the vectorization
factor. In this case, adding support for scalable vectorization is a
functional change that migh require changes at command line.
Note that in some places the idiom
```
unsigned VF = ...
auto VTy = FixedVectorType::get(ScalarTy, VF)
```
has been replaced with
```
ElementCount VF = ...
assert(!VF.Scalable && ...);
auto VTy = VectorType::get(ScalarTy, VF)
```
The assertion guarantees that the new code is (at least in debug mode)
functionally equivalent to the old version. Notice that this change had been
possible because none of the methods that are specific to `FixedVectorType`
were used after the instantiation of `VTy`.
Reviewed By: rengolin, ctetreau
Differential Revision: https://reviews.llvm.org/D85794
Changes:
* Change `ToVectorTy` to deal directly with `ElementCount` instances.
* `VF == 1` replaced with `VF.isScalar()`.
* `VF > 1` and `VF >=2` replaced with `VF.isVector()`.
* `VF <=1` is replaced with `VF.isZero() || VF.isScalar()`.
* Add `<` operator to `ElementCount` to be able to use
`llvm::SmallSetVector<ElementCount, ...>`.
* Bits and pieces around printing the ElementCount to string streams.
* Added a static method to `ElementCount` to represent a scalar.
To guarantee that this change is a NFC, `VF.Min` and asserts are used
in the following places:
1. When it doesn't make sense to deal with the scalable property, for
example:
a. When computing unrolling factors.
b. When shuffle masks are built for fixed width vector types
In this cases, an
assert(!VF.Scalable && "<mgs>") has been added to make sure we don't
enter coepaths that don't make sense for scalable vectors.
2. When there is a conscious decision to use `FixedVectorType`. These
uses of `FixedVectorType` will likely be removed in favour of
`VectorType` once the vectorizer is generic enough to deal with both
fixed vector types and scalable vector types.
3. When dealing with building constants out of the value of VF, for
example when computing the vectorization `step`, or building vectors
of indices. These operation _make sense_ for scalable vectors too,
but changing the code in these places to be generic and make it work
for scalable vectors is to be submitted in a separate patch, as it is
a functional change.
4. When building the potential VFs in VPlan. Making the VPlan generic
enough to handle scalable vectorization factors is a functional change
that needs a separate patch. See for example `void
LoopVectorizationPlanner::buildVPlans(unsigned MinVF, unsigned
MaxVF)`.
5. The class `IntrinsicCostAttribute`: this class still uses `unsigned
VF` as updating the field to use `ElementCount` woudl require changes
that could result in changing the behavior of the compiler. Will be done
in a separate patch.
7. When dealing with user input for forcing the vectorization
factor. In this case, adding support for scalable vectorization is a
functional change that migh require changes at command line.
Differential Revision: https://reviews.llvm.org/D85794
Arm MVE has multiple instructions such as VMLAVA.s8, which (in this
case) can take two 128bit vectors, sign extend the inputs to i32,
multiplying them together and sum the result into a 32bit general
purpose register. So taking 16 i8's as inputs, they can multiply and
accumulate the result into a single i32 without any rounding/truncating
along the way. There are also reduction instructions for plain integer
add and min/max, and operations that sum into a pair of 32bit registers
together treated as a 64bit integer (even though MVE does not have a
plain 64bit addition instruction). So giving the vectorizer the ability
to use these instructions both enables us to vectorize at higher
bitwidths, and to vectorize things we previously could not.
In order to do that we need a way to represent that the reduction
operation, specified with a llvm.experimental.vector.reduce when
vectorizing for Arm, occurs inside the loop not after it like most
reductions. This patch attempts to do that, teaching the vectorizer
about in-loop reductions. It does this through a vplan recipe
representing the reductions that the original chain of reduction
operations is replaced by. Cost modelling is currently just done through
a prefersInloopReduction TTI hook (which follows in a later patch).
Differential Revision: https://reviews.llvm.org/D75069
This reverts commit e9761688e4. It breaks the build:
```
~/src/llvm-project/llvm/lib/Analysis/IVDescriptors.cpp:868:10: error: no viable conversion from returned value of type 'SmallVector<[...], 8>' to function return type 'SmallVector<[...], 4>'
return ReductionOperations;
```
Arm MVE has multiple instructions such as VMLAVA.s8, which (in this
case) can take two 128bit vectors, sign extend the inputs to i32,
multiplying them together and sum the result into a 32bit general
purpose register. So taking 16 i8's as inputs, they can multiply and
accumulate the result into a single i32 without any rounding/truncating
along the way. There are also reduction instructions for plain integer
add and min/max, and operations that sum into a pair of 32bit registers
together treated as a 64bit integer (even though MVE does not have a
plain 64bit addition instruction). So giving the vectorizer the ability
to use these instructions both enables us to vectorize at higher
bitwidths, and to vectorize things we previously could not.
In order to do that we need a way to represent that the reduction
operation, specified with a llvm.experimental.vector.reduce when
vectorizing for Arm, occurs inside the loop not after it like most
reductions. This patch attempts to do that, teaching the vectorizer
about in-loop reductions. It does this through a vplan recipe
representing the reductions that the original chain of reduction
operations is replaced by. Cost modelling is currently just done through
a prefersInloopReduction TTI hook (which follows in a later patch).
Differential Revision: https://reviews.llvm.org/D75069
This patch adds VPValue version of the GEP's operands to
VPWidenGEPRecipe and uses them during code-generation.
Reviewers: Ayal, gilr, rengolin
Reviewed By: gilr
Differential Revision: https://reviews.llvm.org/D80220
This emits new IR intrinsic @llvm.get.active.mask for tail-folded vectorised
loops if the intrinsic is supported by the backend, which is checked by
querying TargetTransform hook emitGetActiveLaneMask.
This intrinsic creates a mask representing active and inactive vector lanes,
which is used by the masked load/store instructions that are created for
tail-folded loops. The semantics of @llvm.get.active.mask are described here in
LangRef:
https://llvm.org/docs/LangRef.html#llvm-get-active-lane-mask-intrinsics
This intrinsic is also used to provide a hint to the backend. That is, the
second argument of the intrinsic represents the back-edge taken count of the
loop. For MVE, for example, we use that to set up tail-predication, which is a
new form of predication in MVE for vector loops that implicitely predicates the
last vector loop iteration by implicitely setting active/inactive lanes, i.e.
the tail loop is predicated. In order to set up a tail-predicated vector loop,
we need to know the number of data elements processed by the vector loop, which
corresponds the the tripcount of the scalar loop, which we can now reconstruct
using @llvm.get.active.mask.
Differential Revision: https://reviews.llvm.org/D79100
Currently extracting a lane for a VPValue def is not supported, if it is
managed directly by VPTransformState (e.g. because it is created by a
VPInstruction or an external VPValue def).
For now, simply extract the requested lane. In the future, we should
also cache the extracted scalar values, similar to LV.
Reviewers: Ayal, rengolin, gilr, SjoerdMeijer
Reviewed By: SjoerdMeijer
Differential Revision: https://reviews.llvm.org/D80787
VPWidenSelectRecipe already contains a VPUser, but it is not used. This
patch updates the code related to VPWidenSelectRecipe to use VPUser for
its operands.
Reviewers: Ayal, gilr, rengolin
Reviewed By: gilr
Differential Revision: https://reviews.llvm.org/D80219
This patch adds VPValue version of the instruction operands to
VPReplicateRecipe and uses them during code-generation.
Reviewers: Ayal, gilr, rengolin
Reviewed By: gilr
Differential Revision: https://reviews.llvm.org/D80114
We can remove a dynamic memory allocation, by checking the number of
operands: no operands = all true, 1 operand = mask.
Reviewers: Ayal, gilr, rengolin
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D80110
The crash that caused the original revert has been fixed in
a3c964a278. I also added a reduced version of the crash reproducer.
This reverts the revert commit 2107af9ccf.
When folding tail, branch taken count is computed during initial VPlan execution
and recorded to be used by the compare computing the loop's mask. This recording
should directly set the State, instead of reusing Value2VPValue mapping which
serves original Values present prior to vectorization.
The branch taken count may be a constant Value, which may be used elsewhere in
the loop; trying to employ Value2VPValue for both leads to the issue reported in
https://reviews.llvm.org/D76992#inline-721028
Differential Revision: https://reviews.llvm.org/D78847
This reverts commit 9245c7ac13.
This is triggering a segfault in XLA downstream, we'll follow-up with
a reproducer, it is likely influenced by TTI/TLI settings or other
options as a simple `opt -loop-vectorize` invocation on the IR
before the crash does not reproduce immediately.
This patch adds VPValue version of the instruction operands to
VPWidenRecipe and uses them during code-generation.
Similar to D76373 this reduces ingredient def-use usage by ILV as
a step towards full VPlan-based def-use relations.
Reviewers: rengolin, Ayal, gilr
Reviewed By: gilr
Differential Revision: https://reviews.llvm.org/D76992
Fix an assert introduced in 41ed5d856c1: a phi with a single predecessor and a
mask is a valid case which is already supported by the code.
Differential Revision: https://reviews.llvm.org/D78115
Widening a selects depends on whether the condition is loop invariant or
not. Rather than checking during codegen-time, the information can be
recorded at the VPlan construction time.
This was suggested as part of D76992, to reduce the reliance on
accessing the original underlying IR values.
Reviewers: gilr, rengolin, Ayal, hsaito
Reviewed By: gilr
Differential Revision: https://reviews.llvm.org/D77869
Default visibility for classes is private, so the private: at the top of
various class definitions is redundant.
Reviewers: gilr, rengolin, Ayal, hsaito
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D77810
InnerLoopVectorizer's code called during VPlan execution still relies on
original IR's def-use relations to decide which vector code to generate,
limiting VPlan transformations ability to modify def-use relations and still
have ILV generate the vector code.
This commit introduces VPValues for VPBlendRecipe to use as the values to
blend. The recipe is generated with VPValues wrapping the phi's incoming values
of the scalar phi. This reduces ingredient def-use usage by ILV as a step
towards full VPlan-based def-use relations.
Differential Revision: https://reviews.llvm.org/D77539
Introduce a new VPWidenCanonicalIVRecipe to generate a canonical vector
induction for use in fold-tail-with-masking, if a primary induction is absent.
The canonical scalar IV having start = 0 and step = VF*UF, created during code
-gen to control the vector loop, is widened into a canonical vector IV having
start = {<Part*VF, Part*VF+1, ..., Part*VF+VF-1> for 0 <= Part < UF} and
step = <VF*UF, VF*UF, ..., VF*UF>.
Differential Revision: https://reviews.llvm.org/D77635
This patch adds VPValue versions for the arguments of the call to
VPWidenCallRecipe and uses them during code-generation.
Similar to D76373 this reduces ingredient def-use usage by ILV as
a step towards full VPlan-based def-use relations.
Reviewers: Ayal, gilr, rengolin
Reviewed By: gilr
Differential Revision: https://reviews.llvm.org/D77655
This patch moves calls to their own recipe, to simplify the transition
to VPUser for operands of VPWidenRecipe, as discussed in D76992.
Subsequently additional information can be added to the recipe rather
than computing it during the execute step.
Reviewers: rengolin, Ayal, gilr, hsaito
Reviewed By: gilr
Differential Revision: https://reviews.llvm.org/D77467
This patch changes VPWidenRecipe to only store a single original IR
instruction. This is the first required step towards modeling it's
operands as VPValues and also towards breaking it up into a
VPInstruction.
Discussed as part of D74695.
Reviewers: Ayal, gilr, rengolin
Reviewed By: gilr
Differential Revision: https://reviews.llvm.org/D76988
InnerLoopVectorizer's code called during VPlan execution still relies on
original IR's def-use relations to decide which vector code to generate,
limiting VPlan transformations ability to modify def-use relations and still
have ILV generate the vector code.
This commit introduces a VPValue for VPWidenMemoryInstructionRecipe to use as
the stored value. The recipe is generated with a VPValue wrapping the stored
value of the scalar store. This reduces ingredient def-use usage by ILV as a
step towards full VPlan-based def-use relations.
Differential Revision: https://reviews.llvm.org/D76373
Now that printing VPValues uses the underlying IR value name, if
available, recording the underlying value here improves printing.
Reviewers: rengolin, hsaito, Ayal, gilr
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D76374
When the an underlying value is available, we can use its name for
printing, as discussed in D73078.
Reviewers: rengolin, hsaito, Ayal, gilr
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D76200
Currently when printing VPValues we use the object address, which makes
it hard to distinguish VPValues as they usually are large numbers with
varying distance between them.
This patch adds a simple slot tracker, similar to the ModuleSlotTracker
used for IR values. In order to dump a VPValue or anything containing a
VPValue, a slot tracker for the enclosing VPlan needs to be created. The
existing VPlanPrinter can take care of that for the existing code. We
assign consecutive numbers to each VPValue we encounter in a reverse
post order traversal of the VPlan.
Reviewers: rengolin, hsaito, fhahn, Ayal, dorit, gilr
Reviewed By: gilr
Differential Revision: https://reviews.llvm.org/D73078
This patch adds a getPlan accessor to VPBlockBase, which finds the entry
block of the plan containing the block and returns the plan set for this
block.
VPBlockBase contains a VPlan pointer, but it should only be set for
the entry block of a plan. This allows moving blocks without updating
the pointer for each moved block and in the future we might introduce a
parent relationship between plans and blocks, similar to the one in LLVM IR.
Reviewers: rengolin, hsaito, fhahn, Ayal, dorit, gilr
Reviewed By: gilr
Differential Revision: https://reviews.llvm.org/D74445
Memory instruction widening recipes use the pointer operand of their load/store
ingredient for generating the needed GEPs, making it difficult to feed these
recipes with pointers based on other ingredients or none at all.
This patch modifies these recipes to use a VPValue for the pointer instead, in
order to reduce ingredient def-use usage by ILV as a step towards full
VPlan-based def-use relations. The recipes are constructed with VPValues bound
to these ingredients, maintaining current behavior.
Differential revision: https://reviews.llvm.org/D70865
The file is intended to gather various VPlan transformations, not only
CFG related transforms. Actually, the only transformation there is not
CFG related.
Reviewers: Ayal, gilr, hsaito, rengolin
Reviewed By: gilr
Differential Revision: https://reviews.llvm.org/D70732
InnerLoopVectorizer's code called during VPlan execution still relies on
original IR's def-use relations to decide which vector code to generate,
limiting VPlan transformations ability to modify def-use relations and still
have ILV generate the vector code.
This commit moves GEP operand queries controlling how GEPs are widened to a
dedicated recipe and extracts GEP widening code to its own ILV method taking
those recorded decisions as arguments. This reduces ingredient def-use usage by
ILV as a step towards full VPlan-based def-use relations.
Differential revision: https://reviews.llvm.org/D69067
This adds a dump() function to VPlan, which uses the existing
operator<<.
This method provides a convenient way to dump a VPlan while debugging,
e.g. from lldb.
Reviewers: hsaito, Ayal, gilr, rengolin
Reviewed By: hsaito
Differential Revision: https://reviews.llvm.org/D70920
By defining the graph traits right after the VPBlockBase definitions, we
can make use of them earlier in the file.
Reviewers: hsaito, Ayal, gilr
Reviewed By: gilr
Differential Revision: https://reviews.llvm.org/D70733
This recommits 11ed1c0239 (reverted in
9f08ce0d21 for failing an assert) with a fix:
tryToWidenMemory() now first checks if the widening decision is to interleave,
thus maintaining previous behavior where tryToInterleaveMemory() was called
first, giving priority to interleave decisions over widening/scalarization. This
commit adds the test case that exposed this bug as a LIT.
This recommits 100e797adb (reverted in
009e032634 for failing an assert). While the
root cause was independently reverted in eaff300401,
this commit includes a LIT to make sure IVDescriptor's SinkAfter logic does not
try to sink branch instructions.
This recommits 2be17087f8 (reverted in
d3ec06d219 for heap-use-after-free) with a fix
in IAI's reset() which was not clearing the set of interleave groups after
deleting them.
The sink-after and interleave-group vectorization decisions were so far applied to
VPlan during initial VPlan construction, which complicates VPlan construction – also because of
their inter-dependence. This patch refactors buildVPlanWithRecipes() to construct a simpler
initial VPlan and later apply both these vectorization decisions, in order, as VPlan-to-VPlan
transformations.
Differential Revision: https://reviews.llvm.org/D68577
Simon Pilgrim