VTypeAnalysis contains some assertions which can be useful for reasoning
that the types of various operands match.
This patch teaches VPlanVerifier to invoke VTypeAnalysis to check them,
and catches some issues with VPInstruction types that are also fixed
here:
* Handles the missing cases for CalculateTripCountMinusVF,
CanonicalIVIncrementForPart and AnyOf
* Fixes ICmp and ActiveLaneMask to return i1 (to align with `icmp` and
`@llvm.get.active.lane.mask` in the LangRef)
The VPlanVerifier unit tests also need to be fleshed out a bit more to
satisfy the stricter assertions
This relands the reverted #120721 with a fix for cases where neither
reduction operand are the reduction phi. Only
63114239cc8d26225a0ef9920baacfc7cc00fc58 and
63114239cc8d26225a0ef9920baacfc7cc00fc58 are new on top of the reverted
PR.
---------
Co-authored-by: Nicholas Guy <nicholas.guy@arm.com>
This re-lands the reverted #92418
When the VF is small enough so that dividing the VF by the scaling
factor results in 1, the reduction phi execution thinks the VF is scalar
and sets the reduction's output as a scalar value, tripping assertions
expecting a vector value. The latest commit in this PR fixes that by
using `State.VF` in the scalar check, rather than the divided VF.
---------
Co-authored-by: Nicholas Guy <nicholas.guy@arm.com>
Following on from https://github.com/llvm/llvm-project/pull/94499, this
patch adds support to the Loop Vectorizer to emit the partial reduction
intrinsics where they may be beneficial for the target.
---------
Co-authored-by: Samuel Tebbs <samuel.tebbs@arm.com>
Introduce a general recipe to generate a scalar phi. Lower
VPCanonicalIVPHIRecipe and VPEVLBasedIVRecipe to VPScalarIVPHIrecipe
before plan execution, avoiding the need for duplicated ::execute
implementations. There are other cases that could benefit, including
in-loop reduction phis and pointer induction phis.
Builds on a similar idea as
https://github.com/llvm/llvm-project/pull/82270.
PR: https://github.com/llvm/llvm-project/pull/114305
Refactors VPVectorPointerRecipe to use the VF VPValue to obtain the
runtime VF, similar to #95305.
Since only reverse vector pointers require the runtime VF, the patch
sets VPUnrollPart::PartOpIndex to 1 for vector pointers and 2 for
reverse vector pointers. As a result, the generation of reverse vector
pointers is moved into a separate recipe.
Use VPWidenIntrinsicRecipe
(https://github.com/llvm/llvm-project/pull/110486)
to create vp.select intrinsics. This potentially offers an alternative
to duplicating EVL recipes for all existing recipes.
There are some recipes that will need duplicates (at least at the
moment), due to extra code-gen needs (e.g. widening loads and stores).
But in cases the intrinsic can directly be used, creating the widened
intrinsic directly would reduce the need to duplicate some recipes.
PR: https://github.com/llvm/llvm-project/pull/110489
This patch splits off intrinsic hanlding to a new
VPWidenIntrinsicRecipe. VPWidenIntrinsicRecipes only need access to the
intrinsic ID to widen and the scalar result type (in case the intrinsic
is overloaded on the result type). It does not need access to an
underlying IR call instruction or function.
This means VPWidenIntrinsicRecipe can be created easily without access
to underlying IR.
Add a new getSCEVExprForVPValue utility which can be used to get a SCEV
expression for a VPValue. The initial implementation only returns SCEVs
for live-in IR values (by constructing a SCEV based on the live-in IR
value) and VPExpandSCEVRecipe. This is enough to serve its first use,
getting a SCEV for a VPlan's trip count, but will be extended in the
future.
It also removes createTripCountSCEV, as the new helper can be used to
retrieve the SCEV from the VPlan.
PR: https://github.com/llvm/llvm-project/pull/94464
The patch adds `VPWidenEVLRecipe` which represents `VPWidenRecipe` + EVL
argument. The new recipe replaces `VPWidenRecipe` in
`tryAddExplicitVectorLength` for each binary and unary operations.
Follow up patches will extend support for remaining cases, like `FCmp`
and `ICmp`
Port collectEphemeralValues to VPlan as collectEphemeralRecipesForVPlan,
use it in willGenerateVectors. This fixes a regression caused by
29b8b72117 for loops where the only vector values are ephemeral.
This patch moves the check if any vector instructions will be generated
from getInstructionCost to be based on VPlan. This simplifies
getInstructionCost, is more accurate as we check the final result and
also allows us to exit early once we visit a recipe that generates
vector instructions.
The helper can then be re-used by the VPlan-based cost model to match
the legacy selectVectorizationFactor behavior, this fixing a crash and
paving the way to recommit
https://github.com/llvm/llvm-project/pull/92555.
PR: https://github.com/llvm/llvm-project/pull/96622
VPTypeAnalysis::inferScalarTypeForRecipe is missing the case for
VPInstruction::LogicalAnd, due to which the test
vplan-incomplete-cases.ll crashes. Add this missing case, and move the
test in vplan-infer-not-or-type.ll to vplan-incomplete-cases.ll, showing
correct codegen for trip-counts 2 and 3.
This patch introduces a new ExtractFromEnd VPInstruction opcode to
extract the value of a FOR for users outside the loop (i.e. in the
scalar loop's exits). This moves the first part of fixing first order
recurrences to VPlan, and removes some additional code to patch up
live-outs, which is now handled automatically.
The majority of test changes is due to changes in the order of which the
extracts are generated now. As we are now using VPTransformState to
generate the extracts, we may be able to re-use existing extracts in the
loop body in some cases. For scalable vectors, in some cases we now have
to compute the runtime VF twice, as each extract is now independent, but
those should be trivial to clean up for later passes (and in line with
other places in the code that also liberally re-compute runtime VFs).
PR: https://github.com/llvm/llvm-project/pull/93395
Introduce new subclasses of VPWidenMemoryRecipe for VP
(vector-predicated) loads and stores to address multiple TODOs from
https://github.com/llvm/llvm-project/pull/76172
Note that the introduction of the new recipes also improves code-gen for
VP gather/scatters by removing the redundant header mask. With the new
approach, it is not sufficient to look at users of the widened canonical
IV to find all uses of the header mask.
In some cases, a widened IV is used instead of separately widening the
canonical IV. To handle that, first collect all VPValues representing header
masks (by looking at users of both the canonical IV and widened inductions
that are canonical) and then checking all users (recursively) of those header
masks.
Depends on https://github.com/llvm/llvm-project/pull/87411.
PR: https://github.com/llvm/llvm-project/pull/87816
This patch introduces a new VPWidenMemoryRecipe base class and distinct
sub-classes to model loads and stores.
This is a first step in an effort to simplify and modularize code
generation for widened loads and stores and enable adding further more
specialized memory recipes.
PR: https://github.com/llvm/llvm-project/pull/87411
This patch introduces generating VP intrinsics in the Loop Vectorizer.
Currently the Loop Vectorizer supports vector predication in a very
limited capacity via tail-folding and masked load/store/gather/scatter
intrinsics. However, this does not let architectures with active vector
length predication support take advantage of their capabilities.
Architectures with general masked predication support also can only take
advantage of predication on memory operations. By having a way for the
Loop Vectorizer to generate Vector Predication intrinsics, which (will)
provide a target-independent way to model predicated vector
instructions. These architectures can make better use of their
predication capabilities.
Our first approach (implemented in this patch) builds on top of the
existing tail-folding mechanism in the LV (just adds a new tail-folding
mode using EVL), but instead of generating masked intrinsics for memory
operations it generates VP intrinsics for loads/stores instructions. The
patch adds a new VPlanTransforms to replace the wide header predicate
compare with EVL and updates codegen for load/stores to use VP
store/load with EVL.
Other important part of this approach is how the Explicit Vector Length
is computed. (VP intrinsics define this vector length parameter as
Explicit Vector Length (EVL)). We use an experimental intrinsic
`get_vector_length`, that can be lowered to architecture specific
instruction(s) to compute EVL.
Also, added a new recipe to emit instructions for computing EVL. Using
VPlan in this way will eventually help build and compare VPlans
corresponding to different strategies and alternatives.
Differential Revision: https://reviews.llvm.org/D99750
Add a new PtrAdd opcode to VPInstruction that corresponds to
IRBuilder::CreatePtrAdd, which creates a GEP with source element type
i8.
This is then used to model scalarizing VPWidenPointerInductionRecipe by
introducing scalar-steps to model the index increment followed by a
PtrAdd.
Note that PtrAdd needs to be able to generate code for only the first
lane or for all lanes. This may warrant introducing a separate recipe
for scalarizing that can be created without relying on the underlying
IR.
Depends on https://github.com/llvm/llvm-project/pull/80271
PR: https://github.com/llvm/llvm-project/pull/83068
A VPlan contains multiple live-ins without underlying IR, like VFxUF or
VectorTripCount. Trying to infer the scalar type of those causes a crash
at the moment.
Update VPTypeAnalysis to take a VPlan in its constructor and assign
types to those live-ins up front. All those live-ins share the type of
the canonical IV.
PR: https://github.com/llvm/llvm-project/pull/80723
Add a new recipe to model scalar cast instructions, without relying on
an underlying instruction.
This allows creating scalar casts, without relying on an underlying
instruction (like the current VPReplicateRecipe). The new recipe is
used to explicitly model both truncating the induction step and the
VPDerivedIVRecipe, thus simplifying both the recipe and code
needed to introduce it.
Truncating VPWidenIntOrFpInductionRecipes should also be modeled using
the new recipe, as follow-up.
PR: https://github.com/llvm/llvm-project/pull/78113
This patch adds initial type inferrence for VPValues. It infers the
scalar type of a VPValue, by bottom-up traversing through defining
recipes until root nodes with known types are reached (e.g. live-ins or
load recipes). The types are then propagated top down through
operations.
This is intended as building block for a VPlan-based cost model, which
will need access to type information for VPValues/recipes.
Initial testing is done by asserting the inferred type matches the type
of the result value generated for a widen and replicate recipes.
