This commit relands the changes from "[LV]: Teach LV to recursively
(de)interleave. #89018"
Reason for revert:
- The patch exposed a bug in the IA pass, the bug is now fixed and landed by commit: #122643
Currently available intrinsics are only ld2/st2, which don't support interleaving factor > 2.
This patch teaches the LV to use ld2/st2 recursively to support high
interleaving factors.
Update VPInterleaveRecipe to always use the pointer to member 0 as
pointer argument. This in many cases helps to remove unneeded index
adjustments and simplifies VPInterleaveRecipe::execute.
In some rare cases, the address of member 0 does not dominate the insert
position of the interleave group. In those cases a PtrAdd VPInstruction
is emitted to compute the address of member 0 based on the address of
the insert position. Alternatively we could hoist the recipe computing
the address of member 0.
This patch implements explicit unrolling by UF as VPlan transform. In
follow up patches this will allow simplifying VPTransform state (no need
to store unrolled parts) as well as recipe execution (no need to
generate code for multiple parts in an each recipe). It also allows for
more general optimziations (e.g. avoid generating code for recipes that
are uniform-across parts).
It also unifies the logic dealing with unrolled parts in a single place,
rather than spreading it out across multiple places (e.g. VPlan post
processing for header-phi recipes previously.)
In the initial implementation, a number of recipes still take the
unrolled part as additional, optional argument, if their execution
depends on the unrolled part.
The computation for start/step values for scalable inductions changed
slightly. Previously the step would be computed as scalar and then
splatted, now vscale gets splatted and multiplied by the step in a
vector mul.
This has been split off https://github.com/llvm/llvm-project/pull/94339
which also includes changes to simplify VPTransfomState and recipes'
::execute.
The current version mostly leaves existing ::execute untouched and
instead sets VPTransfomState::UF to 1.
A follow-up patch will clean up all references to VPTransformState::UF.
Another follow-up patch will simplify VPTransformState to only store a
single vector value per VPValue.
PR: https://github.com/llvm/llvm-project/pull/95842
isLegalInterleavedAccessType expects the subvector type, but
getInterleavedMemoryOpCost is called with the full vector type. So we
need to divide by Factor.
The support for interleaved accesses for scalable vector with a factor
of 2 is enabled in vectorizer. Therefore, the patch removed the
restriction for scalable vector with a factor of 2.
Move vector pointer generation to a separate VPVectorPointerRecipe.
This untangles address computation from the memory recipes future
and is also needed to enable explicit unrolling in VPlan.
https://github.com/llvm/llvm-project/pull/72164
This patch starts initial modeling of VF * UF in VPlan.
Initially, introduce a dedicated VFxUF VPValue, which is then
populated during VPlan::prepareToExecute. Initially, the VF * UF
applies only to the main vector loop region. Once we extend the
scope of VPlan in the future, we may want to associate different VFxUFs
with different vector loop regions (e.g. the epilogue vector loop)
This allows explicitly parameterizing recipes that rely on the
VF * UF, like the canonical induction increment. At the moment, this
mainly helps to avoid generating some duplicated calls to vscale with
scalable vectors. It should also allow using EVL as induction increments
explicitly in D99750. Referring to VF * UF is also needed in other
places that we plan to migrate to VPlan, like the minimum trip count
check during skeleton creation.
The first version creates the value for VF * UF directly in
prepareToExecute to limit the scope of the patch. A follow-on patch will
model VF * UF computation explicitly in VPlan using recipes.
Moved from Phabricator (https://reviews.llvm.org/D157322)
There are many tests that specify a target triple/CPU flags but no
DataLayout which can lead to IR being generated that has unusual
behaviour. This commit attempts to use the default DataLayout based
on the relevant flags if there is no explicit override on the command
line or in the IR file.
One thing that is not currently possible to differentiate from a missing
datalayout `target datalayout = ""` in the IR file since the current
APIs don't allow detecting this case. If it is considered useful to
support this case (instead of passing "-data-layout=" on the command
line), I can change IR parsers to track whether they have seen such a
directive and change the callback type.
Differential Revision: https://reviews.llvm.org/D141060
Need to add NumSrcElts param to is..Mask functions in
ShuffleVectorInstruction class for better mask analysis. Mask.size() not
always matches the sizes of the permuted vector(s). Allows to better
estimate the cost in SLP and fix uses of the functions in other cases.
Differential Revision: https://reviews.llvm.org/D158449
Need to add NumSrcElts param to is..Mask functions in
ShuffleVectorInstruction class for better mask analysis. Mask.size() not
always matches the sizes of the permuted vector(s). Allows to better
estimate the cost in SLP and fix uses of the functions in other cases.
Differential Revision: https://reviews.llvm.org/D158449
Need to add NumSrcElts param to is..Mask functions in
ShuffleVectorInstruction class for better mask analysis. Mask.size() not
always matches the sizes of the permuted vector(s). Allows to better
estimate the cost in SLP and fix uses of the functions in other cases.
Differential Revision: https://reviews.llvm.org/D158449
Need to add NumSrcElts param to is..Mask functions in
ShuffleVectorInstruction class for better mask analysis. Mask.size() not
always matches the sizes of the permuted vector(s). Allows to better
estimate the cost in SLP and fix uses of the functions in other cases.
Differential Revision: https://reviews.llvm.org/D158449
Need to add NumSrcElts param to is..Mask functions in
ShuffleVectorInstruction class for better mask analysis. Mask.size() not
always matches the sizes of the permuted vector(s). Allows to better
estimate the cost in SLP and fix uses of the functions in other cases.
Differential Revision: https://reviews.llvm.org/D158449
Split off from D150398 to avoid builder-related diff changes there.
Using IRBuilder to create ICmps simplifies the result if both operands
are constants.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D158332
vrgather.vv across multiple vector registers (i.e. LMUL > 1) requires all to all data movement. This includes two conceptual sets of changes:
For permutes, we were modeling these as being linear in LMUL.
For reverse, we were modeling them as being fixed cost in LMUL.
Both were wrong, and have been adjusted to O(LMUL^2). Noticed via code inspection while looking at something else.
Its worth asking whether we should be lowering reverse to something other than a vrgather at high LMULs. That shuffle is quite expensive. (Future work)
Differential Revision: https://reviews.llvm.org/D152019
With this patch an undefined mask in a shufflevector will be printed as poison.
This change is done to support the new shufflevector semantics
for undefined mask elements.
Differential Revision: https://reviews.llvm.org/D149210
If the legalized type is a legal interleaved access type (i.e. there's a
supported vlseg/vsseg instruction for it), the interleaved access pass
will pick any interleaved memory op (wide load + shuffles) and lower it
into a vlseg/vsseg intrinsic.
Reviewed By: reames
Differential Revision: https://reviews.llvm.org/D146522
The cost model was not accounting for the fact that we can generate vrgather + an index expression.
Two cases to call out.
1) I did not model the difference between vrgather and vrgatherei16. The result is the constant pool cost can be slightly understated on RV32. I don't think we care, but if someone disagrees, this would be easy to add.
2) Our current codegen for i8 vectors longer than 256 (which is the limit of what this costs) has some room for improvement.
Differential Revision: https://reviews.llvm.org/D147000
After some discussion and experimentation, we have seen that changing the default number of vector register bits to LMUL=2 strikes a sweet spot.
Whilst we could be clever here and make the vectorizer smarter about dynamically selecting an LMUL that
a) Doesn't affect register pressure
b) Suitable for the microarchitecture
we would need to teach its heuristics about RISC-V register grouping specifics.
Instead this just does the easy, pragmatic thing by changing the default to a safe value that doesn't affect register pressure signifcantly[1], but should increase throughput and unlock more interleaving.
[1] Register spilling when compiling sqlite at various levels of `-riscv-v-register-bit-width-lmul`:
LMUL=1 2573 spills
LMUL=2 2583 spills
LMUL=4 2819 spills
LMUL=8 3256 spills
Reviewed By: craig.topper
Differential Revision: https://reviews.llvm.org/D143723
The previous test case stored the result of a deinterleaved load and add
into the same source address, which resulted in some scatters which we
weren't testing for and made the tests harder to understand.
Store it at a separate address, which will make the tests easier to read
when the cost model is changed after D145085 is landed
Reviewed By: reames
Differential Revision: https://reviews.llvm.org/D146442
The loop vectorizer supports generating interleaved loads and stores via
shuffle patterns for fixed length vectors.
This enables it for RISC-V, since interleaved shuffle patterns can be
lowered to vlseg/vsseg in https://reviews.llvm.org/D145022
Reviewed By: reames
Differential Revision: https://reviews.llvm.org/D145155
The loop vectorizer supports generating interleaved loads and stores via
shuffle patterns for fixed length vectors.
This enables it for RISC-V, since interleaved shuffle patterns can be
lowered to vlseg/vsseg in https://reviews.llvm.org/D145022
Reviewed By: reames
Differential Revision: https://reviews.llvm.org/D145155
