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
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
The costs of vector shifts was 2 as opposed to 1, as the nodes are
marked custom. Fix this like the others and mark the nodes as cheap.
Differential Revision: https://reviews.llvm.org/D120773
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.
This reverts commit 0539a26d91a1b7c74022fa9cf33bd7faca87544d.
Causes a miscompile, see comments on D118538.
Required updating bottom-to-top-reorder.ll.
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
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 b3b993a7ad817 which introduced the predicate
argument to getCmpSelInstrCost().
https://reviews.llvm.org/rGb3b993a7ad817c3c5801341fa78f34332900eb83
Differential Revision: https://reviews.llvm.org/D120439
Now that integer min/max intrinsics have good support in both
InstCombine and other passes, start canonicalizing SPF min/max
to intrinsic min/max.
Once this sticks, we can stop matching SPF min/max in various
places, and can remove hacks we have for preventing infinite loops
and breaking of SPF canonicalization.
Differential Revision: https://reviews.llvm.org/D98152
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
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
Compiler adds the estimation for the external uses during operands
reordering analysis, which makes it tend to prefer duplicates in the
lanes rather than diamond/shuffled match in the graph. It changes the sizes of
the vector operands and may prevent some vectorization. We don't need
this kind of estimation for the analysis phase, because we just need to
choose the most compatible instruction and it does not matter if it has
external user or used in the non-matching lane. Instead, we count the number
of unique instruction in the lane and see if the reassociation changes
the number of unique scalars to be power of 2 or not. If we have power
of 2 unique scalars in the lane, it is considered more profitable rather
than having non-power-of-2 number of unique scalars.
Metric: SLP.NumVectorInstructions
test-suite :: MultiSource/Benchmarks/FreeBench/distray/distray.test 70.00 86.00 22.9%
test-suite :: External/SPEC/CFP2017rate/544.nab_r/544.nab_r.test 346.00 353.00 2.0%
test-suite :: External/SPEC/CFP2017speed/644.nab_s/644.nab_s.test 346.00 353.00 2.0%
test-suite :: MultiSource/Benchmarks/mediabench/gsm/toast/toast.test 235.00 239.00 1.7%
test-suite :: MultiSource/Benchmarks/MiBench/telecomm-gsm/telecomm-gsm.test 235.00 239.00 1.7%
test-suite :: External/SPEC/CFP2017rate/526.blender_r/526.blender_r.test 8723.00 8834.00 1.3%
test-suite :: MultiSource/Applications/JM/ldecod/ldecod.test 1051.00 1064.00 1.2%
test-suite :: External/SPEC/CINT2017speed/625.x264_s/625.x264_s.test 1628.00 1646.00 1.1%
test-suite :: External/SPEC/CINT2017rate/525.x264_r/525.x264_r.test 1628.00 1646.00 1.1%
test-suite :: External/SPEC/CFP2017rate/510.parest_r/510.parest_r.test 9100.00 9184.00 0.9%
test-suite :: External/SPEC/CFP2017rate/538.imagick_r/538.imagick_r.test 3565.00 3577.00 0.3%
test-suite :: External/SPEC/CFP2017speed/638.imagick_s/638.imagick_s.test 3565.00 3577.00 0.3%
test-suite :: External/SPEC/CFP2017rate/511.povray_r/511.povray_r.test 4235.00 4245.00 0.2%
test-suite :: MultiSource/Benchmarks/tramp3d-v4/tramp3d-v4.test 1996.00 1998.00 0.1%
test-suite :: MultiSource/Applications/JM/lencod/lencod.test 1671.00 1672.00 0.1%
test-suite :: MultiSource/Benchmarks/Prolangs-C/TimberWolfMC/timberwolfmc.test 783.00 782.00 -0.1%
test-suite :: SingleSource/Benchmarks/Misc/oourafft.test 69.00 68.00 -1.4%
test-suite :: External/SPEC/CINT2017speed/641.leela_s/641.leela_s.test 207.00 192.00 -7.2%
test-suite :: External/SPEC/CINT2017rate/541.leela_r/541.leela_r.test 207.00 192.00 -7.2%
test-suite :: External/SPEC/CINT2017rate/531.deepsjeng_r/531.deepsjeng_r.test 89.00 80.00 -10.1%
test-suite :: External/SPEC/CINT2017speed/631.deepsjeng_s/631.deepsjeng_s.test 89.00 80.00 -10.1%
test-suite :: MultiSource/Benchmarks/mediabench/jpeg/jpeg-6a/cjpeg.test 260.00 215.00 -17.3%
test-suite :: MultiSource/Benchmarks/MiBench/consumer-jpeg/consumer-jpeg.test 256.00 211.00 -17.6%
MultiSource/Benchmarks/Prolangs-C/TimberWolfMC - pretty the same.
SingleSource/Benchmarks/Misc/oourafft.test - 2 <2 x > loads replaced by
one <4 x> load.
External/SPEC/CINT2017speed/641.leela_s - function gets vectorized and
not inlined anymore.
External/SPEC/CINT2017rate/541.leela_r - same
xternal/SPEC/CINT2017rate/531.deepsjeng_r - changed the order in
multi-block tree, the result is pretty the same.
External/SPEC/CINT2017speed/631.deepsjeng_s - same.
MultiSource/Benchmarks/mediabench/jpeg/jpeg-6a - the result is the same
as before.
MultiSource/Benchmarks/MiBench/consumer-jpeg - same.
Differential Revision: https://reviews.llvm.org/D116688
Added support for alternate ops vectorization of the cmp instructions.
It allows to vectorize either cmp instructions with same/swapped
predicate but different (swapped) operands kinds or cmp instructions
with different predicates and compatible operands kinds.
Differential Revision: https://reviews.llvm.org/D115955
Added support for alternate ops vectorization of the cmp instructions.
It allows to vectorize either cmp instructions with same/swapped
predicate but different (swapped) operands kinds or cmp instructions
with different predicates and compatible operands kinds.
Differential Revision: https://reviews.llvm.org/D115955
Added support for alternate ops vectorization of the cmp instructions.
It allows to vectorize either cmp instructions with same/swapped
predicate but different (swapped) operands kinds or cmp instructions
with different predicates and compatible operands kinds.
Differential Revision: https://reviews.llvm.org/D115955
Added support for alternate ops vectorization of the cmp instructions.
It allows to vectorize either cmp instructions with same/swapped
predicate but different (swapped) operands kinds or cmp instructions
with different predicates and compatible operands kinds.
Differential Revision: https://reviews.llvm.org/D115955
No need to reorder the top nodes, if they are not stores or
insertelement instructions and each node should be analized only
once, when the bottom-to-top analysis is performed.
We still endup with extractelements for the top node scalars and
the final shuffle just adds an extra cost and currently
crashes the compiler for PHI nodes.
Differential Revision: https://reviews.llvm.org/D116760
This is required to query the legality more precisely in the LoopVectorizer.
This adds another TTI function named 'forceScalarizeMaskedGather/Scatter'
function to work around the hack introduced for MVE, where
isLegalMaskedGather/Scatter would return an answer by second-guessing
where the function was called from, based on the Type passed in (vector
vs scalar). The new interface makes this explicit. It is also used by
X86 to check for vector widths where gather/scatters aren't profitable
(or don't exist) for certain subtargets.
Differential Revision: https://reviews.llvm.org/D115329
getMinVectorRegisterBitWidth means what vector types is supported in
this target, and actually RISC-V support all fixed length vector types with
vector length less than `getMinRVVVectorSizeInBits`, so set it to 16,
means 2 x i8, that is minimal fixed length vector size in theory.
That also fixed one issue, some testcase migth become non-vectorizable
when `-riscv-v-vector-bits-min` set to larger value, because the vector size is
smaller than `-riscv-v-vector-bits-min`.
For example, following code can vectorize by SLP with
`-riscv-v-vector-bits-min=128` or `-riscv-v-vector-bits-min=256`, but
can't vectorize `-riscv-v-vector-bits-min=512` or larger:
```
void foo(double *da) {
da[0] = 0;
da[1] = 1;
da[2] = 2;
da[3] = 3;
}
```
Reviewed By: craig.topper
Differential Revision: https://reviews.llvm.org/D116534
No need to include the order of the scalars beeing used as part of the
alternate vectorization into account when trying to reorder the whole
graph. Such elements better to reorder in the following phase because
the subtree still ends up in shuffle.
Part of D116688, fixes the regression in D116690.
Differential Revision: https://reviews.llvm.org/D116740
There is a bug in the reordering analysis stage. If the element with the
given hash is not added to the map but has the same number of APOs and
instructions with same parent, but different instruction opcode, it will
be initalized with default values and then the counter is increased by
1. But the lane is not updated and default to 0 instead of the actual
`Lane` value. It leads to the fact that the analysis is useless in
many cases and default to lane 0 instead of actual lane with the
minimum amount of APO operands.
Differential Revision: https://reviews.llvm.org/D116690
