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
Need to check for the number of the unique non-constant values since the
unique values may include several constants.
Differential Revision: https://reviews.llvm.org/D115939
Need to check for the number of the unique non-constant values since the
unique values may include several constants.
Differential Revision: https://reviews.llvm.org/D115939
Need to early exit out of the reordering process if the perfect/shuffled match is found in the operands. Such pattern will result in not profitable reordering because of (false positive) external use of scalars.
Differential Revision: https://reviews.llvm.org/D115811
No need to represent splats as a node with the reused scalars, it may
increase the cost (currently pass just ignores extra shuffle cost and it
is still not correct).
Differential Revision: https://reviews.llvm.org/D115800
Changes the preliminary multinode analysis:
1. Introduced scores for reversed loads/extractelements.
2. Improved shallow score calculation.
3. Lowered the cost of external uses (no need to consider it several times, just ones).
4. The initial lane for analysis is the one with the minimal possible
reorderings.
These changes in general shall reduce compile time and improve the
reordering in many cases.
Part of D57059.
Differential Revision: https://reviews.llvm.org/D101109
The basic idea to this is that a) having a single canonical type makes CSE easier, and b) many of our transforms are inconsistent about which types we end up with based on visit order.
I'm restricting this to constants as for non-constants, we'd have to decide whether the simplicity was worth extra instructions. For constants, there are no extra instructions.
We chose the canonical type as i64 arbitrarily. We might consider changing this to something else in the future if we have cause.
Differential Revision: https://reviews.llvm.org/D115387
If the gather node is a mix of undefvalues and exractelement
instructions, need to take the ordering for such nodes into account too.
It allows to reorder some (sub)trees and remove some extra shuffles,
improving overall vectorization.
Also, outlined common functionality into a separate function.
Differential Revision: https://reviews.llvm.org/D115358
The comparator for the sort functions should provide strict weak
ordering relation between parameters. Current solution causes compiler
crash with some standard c++ library implementations, because it does
not meet this criteria. Tried to fix it + it improves the iverall
vectorization result.
Differential Revision: https://reviews.llvm.org/D115268
Need to add an extra check for potential undef values in
computeExtractCost function to avoid compiler crash on casting to
instructon.
Differential Revision: https://reviews.llvm.org/D115162
If the extractelement instruction is used multiple times in the
different tree entries (either vectorized, or gathered), need to
compensate the scalar cost of such instructions. They are completely
removed if all users are part of the tree but we need to compensate the
cost only once for each instruction.
Differential Revision: https://reviews.llvm.org/D114958
Need to outline the code for finding common vectors in insertelement
instructions into a separate function for future patches. It also
improves the process by adding some extra checks for early exit and
fixes a bug where it always finds the match because of erroneous compare
of the same values.
Differential Revision: https://reviews.llvm.org/D114909
If several shuffle instructions are emitted, some of them might
same/compatible (less defined) with the previously emitted ones. Such
shuffles can be removed safely, improving the total cost of the
vectorized code.
Differential Revision: https://reviews.llvm.org/D114087
Improved the calculation of the shuffled extracts, where possible. Need
to calculate the cost for the extracted scalars if some users are not
insertelements + improved the total estimation of the shuffled scalars
used in insertelements build vectors.
Differential Revision: https://reviews.llvm.org/D113782
Brendon Cahoon