Original commit r311077 of D32871 was reverted in r311304 due to failures
reported in PR34248.
This recommit fixes PR34248 by restricting the packing of predicated scalars
into vectors only when vectorizing, avoiding doing so when unrolling w/o
vectorizing. Added a test derived from the reproducer of PR34248.
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VPlan is an ongoing effort to refactor and extend the Loop Vectorizer. This
patch introduces the VPlan model into LV and uses it to represent the vectorized
code and drive the generation of vectorized IR.
In this patch VPlan models the vectorized loop body: the vectorized control-flow
is represented using VPlan's Hierarchical CFG, with predication refactored from
being a post-vectorization-step into a vectorization planning step modeling
if-then VPRegionBlocks, and generating code inline with non-predicated code. The
vectorized code within each VPBasicBlock is represented as a sequence of
Recipes, each responsible for modelling and generating a sequence of IR
instructions. To keep the size of this commit manageable the Recipes in this
patch are coarse-grained and capture large chunks of LV's code-generation logic.
The constructed VPlans are dumped in dot format under -debug.
This commit retains current vectorizer output, except for minor instruction
reorderings; see associated modifications to lit tests.
For further details on the VPlan model see docs/Proposals/VectorizationPlan.rst
and its references.
Authors: Gil Rapaport and Ayal Zaks
Differential Revision: https://reviews.llvm.org/D32871
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The Loop Vectorizer generates redundant operations when manipulating masks:
AND with true, OR with false, compare equal to true. Instead of relying on
a subsequent pass to clean them up, this patch avoids generating them.
Use null (no-mask) to represent all-one full masks, instead of a constant
all-one vector, following the convention of masked gathers and scatters.
Preparing for a follow-up VPlan patch in which these mask manipulating
operations are modeled using recipes.
Differential Revision: https://reviews.llvm.org/D35725
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This patch attempts to scalarize the operand expressions of predicated
instructions if they were conditionally executed in the original loop. After
scalarization, the expressions will be sunk inside the blocks created for the
predicated instructions. The transformation essentially performs
un-if-conversion on the operands.
The cost model has been updated to determine if scalarization is profitable. It
compares the cost of a vectorized instruction, assuming it will be
if-converted, to the cost of the scalarized instruction, assuming that the
instructions corresponding to each vector lane will be sunk inside a predicated
block, possibly avoiding execution. If it's more profitable to scalarize the
entire expression tree feeding the predicated instruction, the expression will
be scalarized; otherwise, it will be vectorized. We only consider the cost of
the entire expression to accurately estimate the cost of the required
insertelement and extractelement instructions.
Differential Revision: https://reviews.llvm.org/D26083
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Vectorizer tests in the target-independent directory should not have a target
triple. If a test really needs to query a specific backend, it belongs in the
right target subdirectory (which "REQUIRES" the right backend). Otherwise, it
should not specify a triple.
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This patch unifies the data structures we use for mapping instructions from the
original loop to their corresponding instructions in the new loop. Previously,
we maintained two distinct maps for this purpose: WidenMap and ScalarIVMap.
WidenMap maintained the vector values each instruction from the old loop was
represented with, and ScalarIVMap maintained the scalar values each scalarized
induction variable was represented with. With this patch, all values created
for the new loop are maintained in VectorLoopValueMap.
The change allows for several simplifications. Previously, when an instruction
was scalarized, we had to insert the scalar values into vectors in order to
maintain the mapping in WidenMap. Then, if a user of the scalarized value was
also scalar, we had to extract the scalar values from the temporary vector we
created. We now aovid these unnecessary scalar-to-vector-to-scalar conversions.
If a scalarized value is used by a scalar instruction, the scalar value is used
directly. However, if the scalarized value is needed by a vector instruction,
we generate the needed insertelement instructions on-demand.
A common idiom in several locations in the code (including the scalarization
code), is to first get the vector values an instruction from the original loop
maps to, and then extract a particular scalar value. This patch adds
getScalarValue for this purpose along side getVectorValue as an interface into
VectorLoopValueMap. These functions work together to return the requested
values if they're available or to produce them if they're not.
The mapping has also be made less permissive. Entries can be added to
VectorLoopValue map with the new initVector and initScalar functions.
getVectorValue has been modified to return a constant reference to the mapped
entries.
There's no real functional change with this patch; however, in some cases we
will generate slightly different code. For example, instead of an insertelement
sequence following the definition of an instruction, it will now precede the
first use of that instruction. This can be seen in the test case changes.
Differential Revision: https://reviews.llvm.org/D23169
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div/rem instructions in basic blocks that require predication currently prevent
vectorization. This patch extends the existing mechanism for predicating stores
to handle other instructions and leverages it to predicate divs and rems.
Differential Revision: https://reviews.llvm.org/D22918
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