This patch adds initial support for a pointer diff based runtime check
scheme for vectorization. This scheme requires fewer computations and
checks than the existing full overlap checking, if it is applicable.
The main idea is to only check if source and sink of a dependency are
far enough apart so the accesses won't overlap in the vector loop. To do
so, it is sufficient to compute the difference and compare it to the
`VF * UF * AccessSize`. It is sufficient to check
`(Sink - Src) <u VF * UF * AccessSize` to rule out a backwards
dependence in the vector loop with the given VF and UF. If Src >=u Sink,
there is not dependence preventing vectorization, hence the overflow
should not matter and using the ULT should be sufficient.
Note that the initial version is restricted in multiple ways:
1. Pointers must only either be read or written, by a single
instruction (this allows re-constructing source/sink for
dependences with the available information)
2. Source and sink pointers must be add-recs, with matching steps
3. The step must be a constant.
3. abs(step) == AccessSize.
Most of those restrictions can be relaxed in the future.
See https://github.com/llvm/llvm-project/issues/53590.
Reviewed By: dmgreen
Differential Revision: https://reviews.llvm.org/D119078
When the loop vectoriser encounters a known low trip count it tries
to create a single predicated loop in order to get the benefit of
vectorisation and eliminate the scalar tail. However, until now the
vectoriser prevented the use of scalable vectors in this case due
to concerns in the past about stability. I believe that tail-folded
loops using scalable vectors are now sufficiently well tested that
we can enable this. For the same reason I've also enabled it when
optimising for code size too.
Tests added here:
Transforms/LoopVectorize/AArch64/sve-low-trip-count.ll
Transforms/LoopVectorize/AArch64/sve-tail-folding-optsize.ll
Transforms/LoopVectorize/RISCV/low-trip-count.ll
Differential Revision: https://reviews.llvm.org/D121595
Under some circumstances, SCEVExpander will insert new instructions when
expanding a predicate, but the final result of the expansion can be a
false constant.
In those cases, the expanded instructions may later be used by other
expansions, e.g. the trip count. This may trigger an assertion during
SCEVExpander cleanup. To avoid this, always mark the result as used.
Fixes#55100.
If alternate node has only 2 instructions and the tree is already big
enough, better to skip the vectorization of such nodes, they are not
very profitable (the resulting code cotains 3 instructions instead of
original 2 scalars). SLP can try to vectorize the buildvector sequence
in the next attempt, if it is profitable.
Metric: SLP.NumVectorInstructions
Program SLP.NumVectorInstructions
results results0 diff
test-suite :: MultiSource/Benchmarks/DOE-ProxyApps-C/miniAMR/miniAMR.test 72.00 73.00 1.4%
test-suite :: MultiSource/Benchmarks/Prolangs-C/TimberWolfMC/timberwolfmc.test 1186.00 1198.00 1.0%
test-suite :: MultiSource/Benchmarks/DOE-ProxyApps-C++/miniFE/miniFE.test 241.00 242.00 0.4%
test-suite :: MultiSource/Applications/JM/lencod/lencod.test 2131.00 2139.00 0.4%
test-suite :: External/SPEC/CINT2017rate/523.xalancbmk_r/523.xalancbmk_r.test 6377.00 6384.00 0.1%
test-suite :: External/SPEC/CINT2017speed/623.xalancbmk_s/623.xalancbmk_s.test 6377.00 6384.00 0.1%
test-suite :: External/SPEC/CFP2017rate/510.parest_r/510.parest_r.test 12650.00 12658.00 0.1%
test-suite :: External/SPEC/CFP2017rate/526.blender_r/526.blender_r.test 26169.00 26147.00 -0.1%
test-suite :: MultiSource/Benchmarks/Trimaran/enc-3des/enc-3des.test 99.00 86.00 -13.1%
Gains:
526.blender_r - more vectorized trees.
enc-3des - same.
Others:
510.parest_r - no changes.
miniFE - same
623.xalancbmk_s - some (non-profitable) parts of the trees are not
vectorized.
523.xalancbmk_r - same
lencod - same
timberwolfmc - same
miniAMR - same
Differential Revision: https://reviews.llvm.org/D125571
If the insert indes was used already or is not constant, we should stop
looking for unique buildvector sequence, it mustbe splitted to
2 different buildvectors.
In InnerLoopVectorizer::getOrCreateVectorTripCount there is an
assert that the known minimum value for the VF is a power of 2
when tail-folding is enabled. However, for scalable vectors the
value of vscale may not be a power of 2, which means we have
to worry about the possibility of overflow. I have solved this
problem by adding preheader checks that prevent us from entering
the vector body if the canonical IV would overflow, i.e.
if ((IntMax - TripCount) < (VF * UF)) ... skip vector loop ...
Differential Revision: https://reviews.llvm.org/D125235
We commonly want to create either an inbounds or non-inbounds GEP
based on a boolean value, e.g. when preserving inbounds from
existing GEPs. Directly accept such a boolean in the API, rather
than requiring a ternary between CreateGEP and CreateInBoundsGEP.
This change is not entirely NFC, because we now preserve an
inbounds flag in a constant expression edge-case in InstCombine.
Further improvement of the cost model for the scalars used in
buildvectors sequences. The main functionality is outlined into
a separate function.
The cost is calculated in the following way:
1. If the Base vector is not undef vector, resizing the very first mask to
have common VF and perform action for 2 input vectors (including non-undef
Base). Other shuffle masks are combined with the resulting after the 1 stage and processed as a shuffle of 2 elements.
2. If the Base is undef vector and have only 1 shuffle mask, perform the
action only for 1 vector with the given mask, if it is not the identity
mask.
3. If > 2 masks are used, perform serie of shuffle actions for 2 vectors,
combing the masks properly between the steps.
The original implementation misses the very first analysis for the Base
vector, so the cost might too optimistic in some cases. But it improves
the cost for the insertelements which are part of the current SLP graph.
Part of D107966.
Differential Revision: https://reviews.llvm.org/D115750
With opaque pointers, both the stored value and the address can be the
same. Only consider the recipe using the first lane only *if* the
address is not stored.
Fixes#55375.
The current reordering scheme only checks the ordering of in-tree operands.
There are some cases, however, where we need to adjust the ordering based on
the ordering of a future SLP-tree who's instructions are not part of the
current tree, but are external users.
This patch is a simple implementation of this. We keep track of scalar stores
that are users of TreeEntries and if they look profitable to vectorize, then
we keep track of their ordering. During the reordering step we take this new
index order into account. This can remove some shuffles in cases like in the
lit test.
Differential Revision: https://reviews.llvm.org/D125111
If the same scalar is inserted several times into the same buildvector,
the mask index can be used already. In this case need to check, that
this scalar is already part of the vectorized buildvector.
We can try to vectorize number of stores less than MinVecRegSize
/ scalar_value_size, if it is allowed by target. Gives an extra
opportunity for the vectorization.
Fixes PR54985.
Differential Revision: https://reviews.llvm.org/D124284
Need to use actual index instead of the tree entry position, since the
insert index may be different than 0. It mean, that we vectorized part
of the buildvector starting from not initial insertelement instruction
beause of some reason.
Given a commutative reduction leading from a shuffle, the order of the
lanes on the shuffle are not important for the result. This means we can
reorder the shuffle to something simpler, which we try shuffling the
first vector lanes first. This was D123494.
The new shuffle may not be profitable though, and if it is not we can
try the folding of select shuffles from D123911. This, with some
adjustment as the output lane ordering is now unimportant, can allow the
final shuffle to simplify given the inputs to the patterns from D123911.
Where as each transformation on their own are not profitable, the
combination is.
We can only support a single shuffle when called from reductions, but we
are able to sort the ReconstructMask, potentially allowing it to
simplify to an identity or concat mask.
Differential Revision: https://reviews.llvm.org/D125086
Given a load without a better order, this patch partially sorts the
elements to form clusters of adjacent elements in memory. These clusters
can potentially be loaded in fewer loads, meaning less overall shuffling
(for example loading v4i8 clusters of a v16i8 as a single f32 loads, as
opposed to multiple independent bytes loads and inserts).
Differential Revision: https://reviews.llvm.org/D122145
This patch adds a combine to attempt to reduce the costs of certain
select-shuffle patterns. The form of code it attempts to detect is:
%x = shuffle ...
%y = shuffle ...
%a = binop %x, %y
%b = binop %x, %y
shuffle %a, %b, selectmask
A classic select-mask will pick items from each lane of a or b. These
do not always have a great lowering on many architectures. This patch
attempts to pack a and b into the lower elements, creating a differently
ordered shuffle for reconstructing the orignal which may be better than
the select mask. This can be better for performance, especially if less
elements of a and b need to be computed and the input shuffles are
cheaper.
Because select-masks are just one form of shuffle, we generalize to any
mask. So long as the backend has decent costmodel for the shuffles, this
can generally improve things when they come up. For more basic cost
models the folds do not appear to be profitable, not getting past the
cost checks.
Differential Revision: https://reviews.llvm.org/D123911
Further improvement of the cost model for the scalars used in
buildvectors sequences. The main functionality is outlined into
a separate function.
The cost is calculated in the following way:
1. If the Base vector is not undef vector, resizing the very first mask to
have common VF and perform action for 2 input vectors (including non-undef
Base). Other shuffle masks are combined with the resulting after the 1 stage and processed as a shuffle of 2 elements.
2. If the Base is undef vector and have only 1 shuffle mask, perform the
action only for 1 vector with the given mask, if it is not the identity
mask.
3. If > 2 masks are used, perform serie of shuffle actions for 2 vectors,
combing the masks properly between the steps.
The original implementation misses the very first analysis for the Base
vector, so the cost might too optimistic in some cases. But it improves
the cost for the insertelements which are part of the current SLP graph.
Part of D107966.
Differential Revision: https://reviews.llvm.org/D115750
Adds ability to vectorize loops containing a store to a loop-invariant
address as part of a reduction that isn't converted to SSA form due to
lack of aliasing info. Runtime checks are generated to ensure the store
does not alias any other accesses in the loop.
Ordered fadd reductions are not yet supported.
Differential Revision: https://reviews.llvm.org/D110235
This adds fptosi_sat and fptoui_sat to the list of trivially
vectorizable functions, mainly so that the loop vectorizer can vectorize
the instruction. Marking them as trivially vectorizable also allows them
to be SLP vectorized, and Scalarized.
The signature of a fptosi_sat requires two type overrides
(@llvm.fptosi.sat.v2i32.v2f32), unlike other intrinsics that often only
take a single. This patch alters hasVectorInstrinsicOverloadedScalarOpd
to isVectorIntrinsicWithOverloadTypeAtArg, so that it can mark the first
operand of the intrinsic as a overloaded (but not scalar) operand.
Differential Revision: https://reviews.llvm.org/D124358
Currently SLP vectorizer walks through the instructions and selects
3 main classes of values: 1) reduction operations - instructions with same
reduction opcode (add, mul, min/max, etc.), which build the reduction,
2) reduced values - instructions with the same opcodes, but different
from the reduction opcode, 3) extra arguments - all other values,
instructions from the different basic block rather than the root node,
instructions with to many/less uses.
This scheme is not very efficient. It excludes some instructions and all
non-instruction values from the reductions (constants, proficient
gathers), to many possibly reduced values are marked as extra arguments.
Patch improves this process by introducing a bit extended analysis
stage. During this stage, we still try to select 3 classes of the
values: 1) reduction operations - same as before, 2) possibly reduced
values - all instructions from the current block/non-instructions, which
may build a vectorization tree, 3) extra arguments - instructions from
the different basic blocks. Additionally, an extra sorting of the
possibly reduced values occurs to build the scalar sequences which
highly likely will bed vectorized, e.g. loads are grouped by the
distance between them, constants are grouped together, cmp instructions
are sorted by their compare types and predicates, extractelement
instructions are sorted by the vector operand, etc. Also, these groups
are reordered by their length so the longest group is the first in the
list of the possibly reduced values.
The vectorization process tries to emit the reductions for all these
groups. These reductions, remaining non-vectorized possible reduced
values and extra arguments are then combined into the final expression
just like it was before.
Differential Revision: https://reviews.llvm.org/D114171
'Widen' recipe are only used when actual vector values are generated.
Fix tryToWidenCall to do not create VPWidenCallRecipes for scalar vector
factors.
This was exposed by D123720, because the widened recipes are considered
vector users.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D124718
Similar to c515b2f39e, If there are no loops in the function as seen
through LI, we should avoid computing the remaining expensive analyses
(such as SCEV, BPI). Reordered the analyses requests and early return
if there are no loops.
The logic of avoiding expensive analyses is applied to LoopVectorizer,
LoopLoadElimination and LoopUnrollPass, i.e. all function passes which operate
on loops.
This is an NFC with compile time improvement.
Differential Revision: https://reviews.llvm.org/D124529
The name CountRoundDown is potentially misleading, as the number of
iterations can be rounded up when folding the tail.
Reviewed By: fhahn
Differential Revision: https://reviews.llvm.org/D119681
I think this sort comparator was overly complex, and the windows
expensive check bot agreed, failing as it was not giving a strict weak
ordering. Change it to use the comparison of the mask values as unsigned
integers. This should sort the undef elements to the end whilst keeping
X<Y otherwise.
Given a shuffle feeding a commutative reduction, the lane ordering of
the shuffle will not alter the result. This is also true if there are a
number of operations between the reduction and the shuffle, providing
they only operate lane-wise. This patch searches for cases like that in
Vector Combine, allowing us to check the cost of the shuffle vs an
in-order identity shuffle and replace the order if possible. This only
handles a single shuffle at the moment to keep things simple, and is
able to ignore splats that produce results where every result is the
same.
This is a more powerful version of a combine that already happens in
instrcombine, capable of optimizing more cases by looking through more
instructions and being able to cost the shuffle.
Differential Revision: https://reviews.llvm.org/D123494
Introduced masks where they are not added and improved target dependent
cost models to avoid returning of the incorrect cost results after
adding masks.
Differential Revision: https://reviews.llvm.org/D100486
Remove one of the last remaining uses of ::needsVectorIV, preparing for
its removal. Now that usesScalars is available and based on the
information explicit in VPlan, there is no need to use the pre-computed
needsVectorIV.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D123720
Introduced masks where they are not added and improved target dependent
cost models to avoid returning of the incorrect cost results after
adding masks.
Differential Revision: https://reviews.llvm.org/D100486
Before this patch `Args` was used to pass a broadcat's arguments by SLP.
This patch changes this. `Args` is now used for passing the operands of
the shuffle.
Differential Revision: https://reviews.llvm.org/D124202
tryToVectorize() method implements one of searching paths for vectorizable tree roots in SLP vectorizer,
specifically for binary and comparison operations. Order of making probes for various scalar pairs
was defined by its implementation: the instruction operands, then climb over one operand if
the instruction is its sole user and then perform same actions for another operand if previous
attempts failed. Problem with this approach is that among these options we can have more than a
single vectorizable tree candidate and it is not necessarily the one that encountered first.
Trying to build vectorizable tree for each possible combination for just evaluation is expensive.
But we already have lookahead heuristics mechanism which we use for finding best pick among
operands of commutative instructions. It calculates cumulative score for candidates in two
consecutive lanes. This patch introduces use of the heuristics for choosing the best pair among
several combinations. We only try one that looks as most promising for vectorization.
Additional benefit is that we reduce total number of vectorization trees built for probes
because we skip those looking non-profitable early.
Reviewed By: Alexey Bataev (ABataev), Vasileios Porpodas (vporpo)
Differential Revision: https://reviews.llvm.org/D124309
Minor refactoring to reduce size of functional change D124309:
look-ahead scoring routines pulled out of VLOperands and formed
new LookAheadHeuristics helper class.
Reviewed By: Alexey Bataev (ABataev), Vasileios Porpodas (vporpo)
Differential Revision: https://reviews.llvm.org/D124313
This patch extends the scope of VPlan to also include the exit (aka
middle) block.
For now, the exit block remains empty, but handling of exit values will
subsequently be moved to VPlan, by adding recipes to model exit values
in the exit block.
As a first step, this will allow fixing #51366.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D123457
This patch moves SCEV expansion of steps used by
VPWidenIntOrFpInductionRecipes to the pre-header using
VPExpandSCEVRecipe. This ensures that those steps are expanded while the
CFG is in a valid state. Previously, SCEV expansion may happen during
vector body code-generation, during which the CFG may be invalid,
causing issues with SCEV expansion.
Depends on D122095.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D122096
Until now we would only accept a broadcast load pattern if it is only used
by a single vector of instructions.
This patch relaxes this, and allows for the broadcast to have more than one
user vector, as long as all of its uses are internal to the SLP graph and
vectorized.
Differential Revision: https://reviews.llvm.org/D121940
With opaque pointers, the stored value and address can be the same.
Previously the code in VPWidenMemoryInstructionRecipe::onlyFirstLaneDemanded
incorrectly considers stores with matching store and pointer operands as
only demanding the first lane, causing a crash.
This addresses an existing TODO by keeping a mapping of external IR
Value * definitions wrapped in VPValues for use in a VPlan.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D123700
Currently SLP vectorizer walks through the instructions and selects
3 main classes of values: 1) reduction operations - instructions with same
reduction opcode (add, mul, min/max, etc.), which build the reduction,
2) reduced values - instructions with the same opcodes, but different
from the reduction opcode, 3) extra arguments - all other values,
instructions from the different basic block rather than the root node,
instructions with to many/less uses.
This scheme is not very efficient. It excludes some instructions and all
non-instruction values from the reductions (constants, proficient
gathers), to many possibly reduced values are marked as extra arguments.
Patch improves this process by introducing a bit extended analysis
stage. During this stage, we still try to select 3 classes of the
values: 1) reduction operations - same as before, 2) possibly reduced
values - all instructions from the current block/non-instructions, which
may build a vectorization tree, 3) extra arguments - instructions from
the different basic blocks. Additionally, an extra sorting of the
possibly reduced values occurs to build the scalar sequences which
highly likely will bed vectorized, e.g. loads are grouped by the
distance between them, constants are grouped together, cmp instructions
are sorted by their compare types and predicates, extractelement
instructions are sorted by the vector operand, etc. Also, these groups
are reordered by their length so the longest group is the first in the
list of the possibly reduced values.
The vectorization process tries to emit the reductions for all these
groups. These reductions, remaining non-vectorized possible reduced
values and extra arguments are then combined into the final expression
just like it was before.
Differential Revision: https://reviews.llvm.org/D114171
After D121624 models the pre-header in VPlan, VPExpandSCEVRecipes can be
placed there. This ensures SCEV expansion happens before modifying the
CFG during VPlan execution, when CFG is incomplete.
Depends on D121624.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D122095
This patch extends the scope of VPlan to also model the pre-header.
The pre-header can be used to place recipes that should be code-gen'd
outside the loop, like SCEV expansion.
Depends on D121623.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D121624
This fixes the code to actually use the location of the instruction, if
available. Previously, SetInsertPoint would overwrite the insert point
set from the instruction.
When creating induction resume values, SCEV queries may rely on
LoopInfo. Make sure vector.body gets added to the loop of the pre-header
during skeleton construction.
%vector.body will be moved to the vector preheader during VPlan
execution.
Fixes#54745.
Update VPInterleavedAccessInfo to use the generic getVectorLoopRegion
helper instead of relying on the entry block being the top-most vector
loop region.
This was exposed by 14e3650f. The recommit of 14e3650f will hit the
problematic code path requiring the workaround.
test case that crashes without the workaround.
During skeleton construction for the epilogue vector loop, generic
helpers use getOrCreateTripCount, which will re-expand the trip count
computation. Instead, re-use the TripCount created during main loop
vectorization.
This reverts the revert commit 2760cdc9c6.
This version pulls in the code to create the vector loop object in VPlan
from D121624.
This is needed because otherwise existing LoopInfo verification will
fail, as a loop block doesn't have in-loop successors now that we
do not replace the branch.
Now that we do not add new loops during skeleton construction, there's
also no need to verify LI there.
The only remaining use was to get the exit block of the loop. Instead of
relying on the loop, use the successor of VectorHeaderBB
(LoopMiddleBlock) directly to set VPTransformState::CFG::ExitB
Depends on D121621.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D121623
When MaximizeVectorBandwidth is enabled, we can end up (via calls to
collectUniformsAndScalars/setCostBasedWideningDecision through
calculateRegisterUsage) making widening decisions before we have decided
whether to fold the tail by masking. These decisions will be wrong if we
later decided to fold the tail, for example when the trip count is very
low. It will use incorrect costs for loads that should get masked, using
standard memory operation costs instead.
This still at the moment uses the EmulatedMaskMemRefHack costs (a bit
unfortunately), but the old costs without this change were 1, leading to
too optimistic vectorization.
This slightly changes the way that the MaximizeVectorBandwidth option
works to make it easier to test, always honouring the option if it is
set.
Differential Revision: https://reviews.llvm.org/D120215
Instead of looking up the vector loop using the header, keep track of
the current vector loop in VPTransformState. This removes the
requirement for the vector header block being part of the loop up front.
A follow-up patch will move the code to generate the Loop object for the
vector loop to VPRegionBlock.
Depends on D121619.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D121621
Now that all dependencies on creating the latch block up-front have been
removed, there is no need to create it early.
Depends on D121618.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D121619
In some case, like in the added test case, we can reach
selectInterleaveCount with loops that actually have a cost of 0.
Unfortunately a loop cost of 0 is also used to communicate that the cost
has not been computed yet. To resolve the crash, bail out if the cost
remains zero after computing it.
This seems like the best option, as there are multiple code paths that
return a cost of 0 to force a computation in selectInterleaveCount.
Computing the cost at multiple places up front there would unnecessarily
complicate the logic.
Fixes#54413.
This patch moves the code to set the correct incoming block for the
backedge value to VPlan::execute.
When generating the phi node, the backedge value is temporarily added
using the pre-header as incoming block. The invalid phi node will be
fixed up during VPlan::execute after main VPlan code generation.
At the same time, the backedge value is also moved to the latch.
This change removes the requirement to create the latch block up-front
for VPWidenInductionPHIRecipe::execute, which in turn will enable
modeling the pre-header in VPlan.
Depends on D121617.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D121618
If we vectorize a e.g. store, we leave around a bunch of getelementptrs for the individual scalar stores which we removed. We can go ahead and delete them as well.
This is purely for test output quality and readability. It should have no effect in any sane pipeline.
Differential Revision: https://reviews.llvm.org/D122493
This patch moves the code to set the correct incoming block for the
backedge value to VPlan::execute.
When generating the phi node, the backedge value is temporarily added
using the pre-header as incoming block. The invalid phi node will be
fixed up during VPlan::execute after main VPlan code generation.
At the same time, the backedge value is also moved to the latch.
This change removes the requirement to create the latch block up-front
for VPWidenIntOrFpInductionRecipe::execute, which in turn will enable
modeling the pre-header in VPlan.
As an alternative, the increment could be modeled as separate recipe,
but that would require more work and a bit of redundant code, as we need
to create the step-vector during VPWidenIntOrFpInductionRecipe::execute
anyways, to create the values for different parts.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D121617
This simplifies the implementation of eraseInstruction by moving the odd-replace-users-with-undef handling back to the only caller which uses it. This handling was not obviously correct, so add the asserts which make it clear why this is safe to do at all. The result is simpler code and stronger assertions.
The original commit exposed several missing dependencies (e.g. latent bugs in SLP scheduling). Most of these were fixed over the weekend and have had several days to bake. The last was fixed this morning after being noticed in manual review of test changes yesterday. See the review thread for links to each change.
Original commit message follows:
SLP currently schedules all instructions within a scheduling window which stretches from the first instruction potentially vectorized to the last. This window can include a very large number of unrelated instructions which are not being considered for vectorization. This change switches the code to only schedule the sub-graph consisting of the instructions being vectorized and their transitive users.
This has the effect of greatly reducing the amount of work performed in large basic blocks, and thus greatly improves compile time on degenerate examples. To understand the effects, I added some statistics (not planned for upstream contribution). Here's an illustration from my motivating example:
Before this patch:
704357 SLP - Number of calcDeps actions
699021 SLP - Number of schedule calls
5598 SLP - Number of ReSchedule actions
59 SLP - Number of ReScheduleOnFail actions
10084 SLP - Number of schedule resets
8523 SLP - Number of vector instructions generated
After this patch:
102895 SLP - Number of calcDeps actions
161916 SLP - Number of schedule calls
5637 SLP - Number of ReSchedule actions
55 SLP - Number of ReScheduleOnFail actions
10083 SLP - Number of schedule resets
8403 SLP - Number of vector instructions generated
I do want to highlight that there is a small difference in number of generated vector instructions. This example is hitting the bailout due to maximum window size, and the change in scheduling is slightly perturbing when and how we hit it. This can be seen in the RescheduleOnFail counter change. Given that, I think we can safely ignore.
The downside of this change can be seen in the large test diff. We group all vectorizable instructions together at the bottom of the scheduling region. This means that vector instructions can move quite far from their original point in code. While maybe undesirable, I don't see this as being a major problem as this pass is not intended to be a general scheduling pass.
For context, it's worth noting that the pre-scheduling that SLP does while building the vector tree is exactly the sub-graph scheduling implemented by this patch.
Differential Revision: https://reviews.llvm.org/D118538
After writing the commit message for 4b1bace28, realized that the mentioned optimization was rather straight forward. We already have the code for scanning a block during region initialization, we can simply keep track if we've seen a stacksave or stackrestore. If we haven't, none of these dependencies are relevant and we can avoid the relatively expensive scans entirely.
This is an extension of commit b7806c to handle one last case noticed in test changes for D118538. Again, this is thought to be a latent bug in the existing code, though this time I have not managed to reduce tests for the original algoritthm.
The prior attempt had failed to account for this case:
%a = alloca i8
stacksave
stackrestore
store i8 0, i8* %a
If we allow '%a' to reorder into the stacksave/restore region, then the alloca will be deallocated before the use. We will have taken a well defined program, and introduced a use-after-free bug.
There's also an inverse case where the alloca originally follows the stackrestore, and we need to prevent the reordering it above the restore.
Compile time wise, we potentially do an extra scan of the block for each alloca seen in a bundle. This is significantly more expensive than the stacksave rooted version and is why I'd tried to avoid this in the initial patch. There is room to optimize this (by essentially caching a "has stacksave" bit per block), but I'm leaving that to future work if it actually shows up in practice. Since allocas in bundles should be rare in practice, I suspect we can defer the complexity for a long while.
Update all places that currently assume the entry block to the plan is
also the vector loop header to use getVectorLoopRegion instead.
getVectorLoopRegion will keep doing the right thing when the pre-header
is modeled explicitly (and becomes the new entry block in the plan).
We can not bitcast pointers across different address spaces. This was
previously fixed in D89577 but then in D93229 an enhancement was added
which peeks further through the ponter operand, opening up the
possibility that address-space violations could be introduced.
Instead of bailing as the previous fix did, simply insert an
addrspacecast cast instruction.
Reviewed By: lebedev.ri
Differential Revision: https://reviews.llvm.org/D121787
This patch moves pointer induction handling from VPWidenPHIRecipe to its
own recipe. In the process, it adds all information required to generate
code for pointer inductions without relying on Legal to access the list
of induction phis.
Alternatively VPWidenPHIRecipe could also take an optional pointer to InductionDescriptor.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D121615
createInductionResumeValues only uses its loop argument only to get the
pre-header, but the pre-header is already known (we created/cached it
earlier). Remove the unneeded loop argument.
completeLoopSkeleton only uses its loop argument only to get the
pre-header, but the pre-header is already known (we created/cached it
earlier). Remove the unneeded loop argument.
The semantics of an inalloca alloca instruction requires that it not be reordered with a preceeding stacksave intrinsic call. Unfortunately, there's no def/use edge or memory dependence edge. (THe memory point is slightly subtle, but in general a new allocation can't alias with a call which executes strictly before it comes into existance.)
I'd tried to tackle this same case previously in 689babdf6, but the fix chosen there turned out to be incomplete. As such, this change contains a fully revert of the first fix attempt.
This was noticed when investigating problems which surfaced with D118538, but this is definitely an existing bug. This time around, I managed to reduce a couple of additional cases, including one which was being actively miscompiled even without the new scheduling change. (See test diffs)
Compile time wise, we only spend extra time when seeing a stacksave (rare), and even then we walk the block at most once per schedule window extension. Likely a non-issue.
This fixes an active miscompile visible in the test changes. The basic problem is that the scheduling dependency graph didn't have any edges for control dependence within a single basic block. The result is that we could (and in some rare cases *did*) perform reorderings within a block which could introduce new undefined behavior along paths which didn't previously contain any.
Impact wise, we have two major cases where control is not guaranteed to reach a later instruction in the block: may throw calls, and calls containing infinite loops.
* The former case was mostly covered by the memory dependencies, and to trigger require a function which can throw, but not write to memory. In theory, such a case is possible, but not likely in practice.
* The later case is likely more of an issue in practice. After this code was first written, we changed the IR semantics to allow well defined infinite loops without satisifying mustprogress. Even for C/C++ - which do imply mustprogress - recent changes to how we treat atomics (e.g. an atomic read does not always imply a write) could expose this issue. I'm a bit shocked we don't seem to have a bug report which hit this in real code actually.
Compile time wise, this results in a single extra scan of the scheduling window in the common case. Since we stop scanning at the next instruction which isn't guaranteed to execute, no matter what order we traverse instructions in, we scan the block once. The exception to this is that when we extend the scheduling window downwards, we invalidate all dependencies, and thus rescan. So the potentially expensive case is when we a call in a big schedule window which is frequently extended. We could optimize this case (by caching the last instruction not guaranteeed to transfer execution and scanning only the extended window) and starting there), but I decided to leave the complexity until it mattered. That same case is already degenerate with memory dependences which is more expensive than the control dependence scan.
We could also consider combining the memory dependence and control dependence sets to reduce memory usage, but since it complicates the code slightly and makes debugging a bit harder, I went with the simplest scheme for now.
This was noticed while trying to understand the failures reported against D118538, but is not otherwise related to that change.
Update functions that previously took a loop pointer but only to get the
pre-header. Instead, pass the block directly. This removes the
requirement for the loop object to be created up-front.
I keep thinking this assumption is probably exploitable for a bug in the existing implementation, but all of my attempts at writing a test case have failed. So for the moment, just document this very subtle assumption.
This patch fixes:
llvm/lib/Transforms/Vectorize/SLPVectorizer.cpp:3917:13: error:
unused function 'needToScheduleSingleInstruction'
[-Werror,-Wunused-function]
This reverts commit 1cfa986d68. See https://github.com/llvm/llvm-project/issues/54256 for why I'm discontinuing the project.
Seperately, it turns out that while this patch does correctly preserve MSSA, it's correct only at the end of the pass; not between vectorization attempts. Even if we decide to resurrect this, we'll need to fix that before reapplying.
Splat loads are inexpensive in X86. For a 2-lane vector we need just one
instruction: `movddup (%reg), xmm0`. Using the standard Splat score leads
to worse code. This patch adds a new score dedicated for splat loads.
Please note that a splat is usually three IR instructions:
- It is usually a load and 2 inserts:
%ld = load double, double* %gep
%ins1 = insertelement <2 x double> poison, double %ld, i32 0
%ins2 = insertelement <2 x double> %ins1, double %ld, i32 1
- But it can also be a load, an insert and a shuffle:
%ld = load double, double* %gep
%ins = insertelement <2 x double> poison, double %ld, i32 0
%shf = shufflevector <2 x double> %ins, <2 x double> poison, <2 x i32> zeroinitializer
Because of this some of the lit tests contain more IR instructions.
Differential Revision: https://reviews.llvm.org/D121354
No need to schedule entry nodes where all instructions are not memory
read/write instructions and their operands are either constants, or
arguments, or phis, or instructions from others blocks, or their users
are phis or from the other blocks.
The resulting vector instructions can be placed at
the beginning of the basic block without scheduling (if operands does
not need to be scheduled) or at the end of the block (if users are
outside of the block).
It may save some compile time and scheduling resources.
Differential Revision: https://reviews.llvm.org/D121121
This uses the existing VPlan helpers to check whether there are scalar
uses of a phi recipe. It remove one of the few remaining dependencies on
the cost model from VPlan code generation.
Depends on D121612.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D121613
VPInterleaveRecipe only uses the first lane of the address. Add
onlyFirstLaneUsed implementation. This is needed for a follow-up patch.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D121612
This patch ensures scalars (except for uniforms) are no
longer collected (prior to LVP planning phase) for
scalable vectorization.
This is to avoid the chances of generating scalarized
instructions later (during LVP execute phase) as they
are not supported for scalable vectorization.
Relevant test has also been added.
Differential Revision: https://reviews.llvm.org/D121452
No need to schedule entry nodes where all instructions are not memory
read/write instructions and their operands are either constants, or
arguments, or phis, or instructions from others blocks, or their users
are phis or from the other blocks.
The resulting vector instructions can be placed at
the beginning of the basic block without scheduling (if operands does
not need to be scheduled) or at the end of the block (if users are
outside of the block).
It may save some compile time and scheduling resources.
Differential Revision: https://reviews.llvm.org/D121121
This initial patch adds code to preserve MemorySSA through a run of SLP vectorizer. The eventual plan is to use MemorySSA to accelerate SLP's memory dependence checking, but we're a ways from that. In particular, this patch is correct, but really slow. It's being landed so that we can work incrementally in tree, not because it's expected to be useful to anyone just yet.
The broader effort is being tracked in https://github.com/llvm/llvm-project/issues/54256. Its worth noting expicitly that this may not work out, and if not, we will be reverting all of the MSSA support in SLP at some point in the next few weeks.
Differential Revision: https://reviews.llvm.org/D117926
Update places still referencing LoopVectorBody to use the vector loop to
get the vector loop header. This is needed to move vector loop
code-generation to VPlan completely, which in turn is needed to model
pre-header & exit blocks in VPlan as well.
The insertion point for the builder used during VPlan code generation is
set during code generation. Setting the insert point here is dead code
and can be removed.
This patch is a follow-up to D115953. It updates optimizeInductions
to also introduce new VPScalarIVStepsRecipes if an IV has both vector
and scalar uses.
It updates all uses that only need scalar values to use the newly
created recipe for the scalar steps.
This completes untangling of VPWidenIntOrFpInductionRecipe
code-generation. Now the recipe *only* creates the widened vector
values, as it says on the tin.
The code to genereate IR has been moved directly to
VPWidenIntOrFpInductionRecipe::execute.
Note that the recipe has been updated to hold a reference to
ScalarEvolution, which is needed to expand the step, until we can place
the corresponding SCEV expansion in the pre-header.
Depends on D120827.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D120828
This patch adds a helper to check if a recipe only uses scalars of a
given operand. This is similar to onlyFirstLaneUsed, which was
introduced earlier.
By default, usesScalars falls back on onlyFirstLaneUsed.
Will be used by D120828.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D120827
Single value phis won't be modeled in VPlan. If the phi only gets used
outside the loop, the current code misses the fact that the incoming
value is not dead. Update the code to also look through such phis to
check for outside users.
Fixes#54266
The analysis passes output function name encapsulated in `'` braces,
but LV uses `"`. Harmonizing this may help in creating an update script
for the LV costmodel test checks.
Reviewed By: fhahn
Differential Revision: https://reviews.llvm.org/D121105
Root issue which triggered the revert was fixed in 689bab. No changes in the reapplied patch.
Original commit message follows:
SLP currently schedules all instructions within a scheduling window which stretches from the first instr
uction potentially vectorized to the last. This window can include a very large number of unrelated instruct
ions which are not being considered for vectorization. This change switches the code to only schedule the su
b-graph consisting of the instructions being vectorized and their transitive users.
This has the effect of greatly reducing the amount of work performed in large basic blocks, and thus greatly improves compile time on degenerate examples. To understand the effects, I added some statistics (not planned for upstream contribution). Here's an illustration from my motivating example:
Before this patch:
704357 SLP - Number of calcDeps actions
699021 SLP - Number of schedule calls
5598 SLP - Number of ReSchedule actions
59 SLP - Number of ReScheduleOnFail actions
10084 SLP - Number of schedule resets
8523 SLP - Number of vector instructions generated
After this patch:
102895 SLP - Number of calcDeps actions
161916 SLP - Number of schedule calls
5637 SLP - Number of ReSchedule actions
55 SLP - Number of ReScheduleOnFail actions
10083 SLP - Number of schedule resets
8403 SLP - Number of vector instructions generated
I do want to highlight that there is a small difference in number of generated vector instructions. This example is hitting the bailout due to maximum window size, and the change in scheduling is slightly perturbing when and how we hit it. This can be seen in the RescheduleOnFail counter change. Given that, I think we can safely ignore.
The downside of this change can be seen in the large test diff. We group all vectorizable instructions together at the bottom of the scheduling region. This means that vector instructions can move quite far from their original point in code. While maybe undesirable, I don't see this as being a major problem as this pass is not intended to be a general scheduling pass.
For context, it's worth noting that the pre-scheduling that SLP does while building the vector tree is exactly the sub-graph scheduling implemented by this patch.
Differential Revision: https://reviews.llvm.org/D118538
While a collection of allocas are technically vectorizeable - by forming a wider alloca - this was not a transform SLP actually knows how to do. Instead, we were forming a bundle with missing dependencies, and then relying on the scheduling code to preserve program order if multiple instructions were scheduleable at once. I haven't been able to write a test case, but I'm 99% sure this was wrong in some edge case.
The unknown op case was flowing down the shufflevector path. This did result in some splat handling being lost with this change, but the same lack of splat handling is visible in a whole bunch of simple examples for the gather path. I didn't consider this interesting to fix given how narrow the splat of allocas case is.
Instead of relying on underlying instructions, this patch updates
VPScalarIVStepsRecipe to only store the required type information.
This removes access to unrelated information, as well as avoiding issues
with the same underlying instruction being shared by multiple recipes.
This change should only change the debug output and not cause any
codegen changes, hence NFCI.
Currently bottom-to-top reordering analysis counts orders of the
operands and then adds natural order counts for the operand users. It is
very conservative, this the user nodes themselves may require
reordering. Patch improves bottom-to-top analysis by checking for the
user nodes if they require/allows the reordring. If the user node must
be reordered, has reused scalars, is an alternate op vectorization node,
is a non-ordered gather node or may allow reordering because of the
reordered operands, such node is considered as the node that allows
reodring and is not counted as a node with the natural order.
Differential Revision: https://reviews.llvm.org/D120492
This reverts the revert commit ff93260bf6.
The underlying issue causing the PPC bot failures has been fixed in
cbaac14734 and a corresponding test case has been added in
ad2cad1c52.
Original message:
This patch adds a new VPScalarIVStepsRecipe to handle building scalar
steps.
In the first patch, it only handles the case where there is no vector
induction variable needed.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D115953
Exit values of vector inductions are generated completely independent of
the induction recipes. Consider them for removal, if they are not used
in loop.
This fixes a crash exposed by 49b23f451c.
SLP makes very heavy use of aliasing queries to construct pointer dependencies for scheduling purposes. AA internally usings pointerMayBeCaptured to prove some noalias results. In a local profile, we were spending about 4% of total O2 time in capture tracking. By using BatchAA interface - which caches capture results - this drops to 2%.
Note that there is no invalidation of BatchAA here. This assumes that no transformation done by SLP invalidates alias or capture results. This is the same assumption made by the existing AliasCache, so this is not a new assumption in the code.
This patch adds a new VPScalarIVStepsRecipe to handle building scalar
steps.
In the first patch, it only handles the case where there is no vector
induction variable needed.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D115953
This can be used to explicitly model VPValues that depend on SCEV
expansion, like the step for inductions.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D116288
This patch adds a new transform to remove dead recipes. For now, it only
removes dead recipes in the header, to keep the number tests that require
updating manageable. Future patches will extend this to remove dead
recipes across the whole plan.
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D118051
Currently, SLP can insert "shuffle" instruction beween PHI and Landing pad instruction. The problem is demonstrated by LIT test. The solution is to adjust insertion point once we are done with PHI generation.
Differential Revision: https://reviews.llvm.org/D120552
The min/max intrinsic cost is currently too low because in the cost calculation
we subtract the cost of the vector compare as we will not emit it.
For the cost of the vector compare we are currently passing BAD_ICMP_PREDICATE
which returns 3, the worst case cost.
I think we should be passing VecPred instead, since we know the predicates of
the compare instr.
I think this is related to commit b3b993a7ad which introduced the predicate
argument to getCmpSelInstrCost().
https://reviews.llvm.org/rGb3b993a7ad817c3c5801341fa78f34332900eb83
Differential Revision: https://reviews.llvm.org/D120439
This change uses instruction's comesBefore method to simplify the code significantly. There's little compile time concern here because getSpillCost already calls comesBefore on every basic block which contains a vectorization candidate. The only additional times we'll build basic block ordering is when we can't schedule a vector candidate anywhere in the containing block.
Differential Revision: https://reviews.llvm.org/D120364
This cap was first added in 848c1aa45 (back in 2015). Per the original commit message, the purpose was to avoid a compile time explosion in long basic blocks. The algorithmic problem in scheduling has now been fixed in 0539a26d.
In the meantime, the code has rotten fairly badly. Some intermediate refactoring caused the size to only be incremented if *both* iterators advance in the window search. This causes the size to be badly undercounted when near one end of a basic block. We no longer have any test which exercises the logic in an intentional way; there's one test which differs with this change, but the changes appear fairly orthoganol to the purpose of the test file.
Unfortunately, we no longer have the original motivating example, so it's possible that it also hits some other issue. I tested locally with a large example, but even at it's worst, that one doesn't demonstrate anything too extreme even without the algorithmic fix. It's clearly faster with, but only by ~20% which doesn't seem in line with the original commit message. If regressions with this patch are seen, please file a bug and I'll try to fix any other algorithmic problems which fall out.
A call to getInsertIndex() in getTreeCost() is returning None,
which causes an assert because a non-constant index value for
insertelement was not expected. This case occurs when the
insertelement index value is defined with a PHI.
Differential Revision: https://reviews.llvm.org/D120223
SLP currently schedules all instructions within a scheduling window which stretches from the first instruction potentially vectorized to the last. This window can include a very large number of unrelated instructions which are not being considered for vectorization. This change switches the code to only schedule the sub-graph consisting of the instructions being vectorized and their transitive users.
This has the effect of greatly reducing the amount of work performed in large basic blocks, and thus greatly improves compile time on degenerate examples. To understand the effects, I added some statistics (not planned for upstream contribution). Here's an illustration from my motivating example:
Before this patch:
704357 SLP - Number of calcDeps actions
699021 SLP - Number of schedule calls
5598 SLP - Number of ReSchedule actions
59 SLP - Number of ReScheduleOnFail actions
10084 SLP - Number of schedule resets
8523 SLP - Number of vector instructions generated
After this patch:
102895 SLP - Number of calcDeps actions
161916 SLP - Number of schedule calls
5637 SLP - Number of ReSchedule actions
55 SLP - Number of ReScheduleOnFail actions
10083 SLP - Number of schedule resets
8403 SLP - Number of vector instructions generated
I do want to highlight that there is a small difference in number of generated vector instructions. This example is hitting the bailout due to maximum window size, and the change in scheduling is slightly perturbing when and how we hit it. This can be seen in the RescheduleOnFail counter change. Given that, I think we can safely ignore.
The downside of this change can be seen in the large test diff. We group all vectorizable instructions together at the bottom of the scheduling region. This means that vector instructions can move quite far from their original point in code. While maybe undesirable, I don't see this as being a major problem as this pass is not intended to be a general scheduling pass.
For context, it's worth noting that the pre-scheduling that SLP does while building the vector tree is exactly the sub-graph scheduling implemented by this patch.
Differential Revision: https://reviews.llvm.org/D118538
Extends getReductionOpChain to look through Phis which may be part of
the reduction chain. adjustRecipesForReductions will now also create a
CondOp for VPReductionRecipe if the block is predicated and not only if
foldTailByMasking is true.
Changes were required in tryToBlend to ensure that we don't attempt
to convert the reduction Phi into a select by returning a VPBlendRecipe.
The VPReductionRecipe will create a select between the Phi and the reduction.
Reviewed By: david-arm
Differential Revision: https://reviews.llvm.org/D117580
If the alternate cmp instruction is a swapped predicate of the main cmp
instruction, need to generate alternate instruction, not the one with
the swapped predicate. Also, the lane with the alternate opcode should
be selected only, if the corresponding operands are not compatible.
Correctness confirmed:
https://alive2.llvm.org/ce/z/94BG66
Differential Revision: https://reviews.llvm.org/D119855
Particularly this breaks vectorization of insertelements where some of
intermediate (i.e. not last) insertelements are used externally.
Fixes PR52275
Fixes#51617
Differential Revision: https://reviews.llvm.org/D119679
Note that this doesn't actually cause the top level predicate to become a non-union just yet.
The * above comes from a case in the LoopVectorizer where a predicate which is later proven no longer blocks vectorization due to a change from checking if predicates exists to whether the predicate is possibly false.
This reverts commit 77a0da926c as we've
received multiple reports of this significantly impacting performance,
in ways that don't seem to just be target specific cost models going
wrong. I would offer some reproducers, but the test changes here seem to
be full of them!
Reverting for now and hopefully we can remove the "hack" more carefully
as we go.
Move out the induction step creation from emitTransformedIndex to the
callers. In some places (e.g. widenIntOrFpInduction) the step is already
created. Passing the step in ensures the steps are kept in sync.
This makes the function independent of shared state in ILV (ensures no
new dependencies on things like the cost model are introduced) and allows
for use directly in recipe's ::execute functions.
The vectorizer will choose at times to "vectorize" loops with a scalar
factor (VF=1) with interleaving (IC > 1). This can occasionally produce
better code than the unroller (notable for reductions where it can
produce independent reduction chains that are combined after the loop).
At times this is not very beneficial though, for example when runtime
checks are needed or when the scalar code requires predication.
This addresses the second point, preventing the vectorizer from
interleaving when the scalar loop will require predication. This
prevents it from making a bit of a mess, that is worse than the original
and better left for the unroller to unroll if beneficial. It helps
reverse some of the regressions from D118090.
Differential Revision: https://reviews.llvm.org/D118566
Florian Hahn