Currently, we try to vectorize values, feeding into stores, only if
slp-vectorize-hor-store option is provided. We can safely enable
vectorization of the value operand of a single store in the basic block,
if the operand value is used only in store.
It should enable extra vectorization and should not increase compile
time significantly.
Fixes https://github.com/llvm/llvm-project/issues/51320
Differential Revision: https://reviews.llvm.org/D131894
2xi64 is the legalized type for wide reductions (like 16xi64) and setting the
cost to 2 makes `load-reduce` and `load-zext-reduce` patterns profitable.
The few performance measurments that I did on an aarch64 machine confirm that
these patterns are actually faster when vectorized.
Differential Revision: https://reviews.llvm.org/D130740
We currently assert in vectorizeTree(TreeEntry*) when processing a PHI
bundle in a block containing a catchswitch. We attempt to set the
IRBuilder insertion point following the catchswitch, which is invalid.
This is done so that ShuffleBuilder.finalize() knows where to insert
a shuffle if one is needed.
To avoid this occurring, watch out for catchswitch blocks during
buildTree_rec() processing, and avoid adding PHIs in such blocks to
the vectorizable tree. It is unlikely that constraining vectorization
over an exception path will cause a noticeable performance loss, so
this seems preferable to trying to anticipate when a shuffle will and
will not be required.
This patch slightly extends the limit on the RecursionMaxDepth inside
the SLP vectorizer. It does it only when it hits a load (or zext/sext of
a load), which allows it to peek through in the places where it will be
the most valuable, without ballooning out the O(..) by any 2^n factors.
Differential Revision: https://reviews.llvm.org/D122148
Building on the work on D124284, this patch tags v4i8 and v2i16 vector loads as custom, enabling SLP to try to vectorize these types ending in a partial store (using the SSE MOVD instruction) - we already do something similar for 64-bit vector types.
Differential Revision: https://reviews.llvm.org/D127604
If the root order itself does not require reordering, we can just
remove its reorder mask safely (e.g., if the root node is a vector of
phis). But if this node is used as an operand in the graph, we cannot
delete the reordering, need to keep it. Otherwise the graph nodes are
not synchronized with the operands. It may cause an extra gather
instruction(s) or a compiler crash.
Also, need to be very careful when selecting the gather nodes for
reordering since there might several gather nodes with the same scalars
and we can try to reorder just the same node many times instead of
different nodes.
Differential Revision: https://reviews.llvm.org/D128680
Improved/fixed cost modeling for shuffles by providing masks, improved
cost model for non-identity insertelements.
Differential Revision: https://reviews.llvm.org/D115462
Patch was reverted in 4c5f10a due to buildbot failures, now being
reapplied with updated AArch64 and RISCV tests.
This patch adds handling for the llvm.powi.* intrinsics in
BasicTTIImplBase::getIntrinsicInstrCost() and improves vectorization.
Closes#53887.
Differential Revision: https://reviews.llvm.org/D128172
If the masked gather nodes must be reordered, we can just reorder
scalars, just like for gather nodes. But if the node contains reused
scalars, it must be handled same way as a regular vectorizable node,
since need to reorder reused mask, not the scalars directly.
Differential Revision: https://reviews.llvm.org/D128360
This reverts commit cac60940b7.
Caused -Os -fsanitize=memory -march=haswell miscompile to pytorch/cpuinfo.
See my latest comment (may update) on D115462.
During the reordering transformation we should try to avoid reordering bundles
like fadd,fsub because this may block them being matched into a single vector
instruction in x86.
We do this by checking if a TreeEntry is such a pattern and adding it to the
list of TreeEntries with orders that need to be considered.
Differential Revision: https://reviews.llvm.org/D125712
This patch adds handling for the llvm.powi.* intrinsics in
BasicTTIImplBase::getIntrinsicInstrCost() and improves vectorization.
Closes#53887.
Differential Revision: https://reviews.llvm.org/D128172
If the OffsetBeg + InsertVecSz is greater than VecSz, need to estimate
the cost as shuffle of 2 vector, not as insert of subvector. Otherwise,
the inserted subvector is out of range and compiler may crash.
Differential Revision: https://reviews.llvm.org/D128071
If the root scalar is mapped to to the smallest bit width, the vector is
truncated and the types between original buildvector and extracted value
mismatched. For extract, we emit sext/zext instructions, for shuffles we
can reuse oringal vector instead of the truncated one.
Differential Revision: https://reviews.llvm.org/D127974
Currently scatter vectorize nodes can be emitted only for GEPs with
constant indices. But we can also emit such nodes for GEPs with the same
ptr and non-constant vectorizable/gathered indices, if profitable. Patch
adds support for such nodes and tries to improve handling of GEPs with
non-const indeces for such nodes.
Metric: SLP.NumVectorInstructions
Program SLP.NumVectorInstructions
results results0 diff
test-suite :: External/SPEC/CFP2017speed/638.imagick_s/638.imagick_s.test 5243.00 5240.00 -0.1%
test-suite :: External/SPEC/CFP2017rate/538.imagick_r/538.imagick_r.test 5243.00 5240.00 -0.1%
test-suite :: External/SPEC/CFP2017rate/526.blender_r/526.blender_r.test 27550.00 27507.00 -0.2%
test-suite :: External/SPEC/CFP2006/453.povray/453.povray.test 5395.00 5380.00 -0.3%
test-suite :: External/SPEC/CFP2017rate/511.povray_r/511.povray_r.test 5389.00 5374.00 -0.3%
test-suite :: External/SPEC/CINT2017rate/520.omnetpp_r/520.omnetpp_r.test 961.00 958.00 -0.3%
test-suite :: External/SPEC/CINT2017speed/620.omnetpp_s/620.omnetpp_s.test 961.00 958.00 -0.3%
test-suite :: External/SPEC/CFP2006/447.dealII/447.dealII.test 5664.00 5643.00 -0.4%
test-suite :: External/SPEC/CFP2017rate/510.parest_r/510.parest_r.test 13202.00 13127.00 -0.6%
test-suite :: External/SPEC/CINT2006/445.gobmk/445.gobmk.test 212.00 207.00 -2.4%
test-suite :: MultiSource/Benchmarks/7zip/7zip-benchmark.test 890.00 850.00 -4.5%
test-suite :: External/SPEC/CINT2006/464.h264ref/464.h264ref.test 1695.00 1581.00 -6.7%
test-suite :: MultiSource/Applications/JM/lencod/lencod.test 2338.00 2140.00 -8.5%
test-suite :: SingleSource/UnitTests/matrix-types-spec.test 63.00 55.00 -12.7%
test-suite :: SingleSource/Benchmarks/Adobe-C++/loop_unroll.test 468.00 356.00 -23.9%
Geomean difference -0.3%
All numbers show increased number of generated vector instructions.
Diff:
SingleSource/Benchmarks/Adobe-C++/loop_unroll - better without LTO, but
need an extra analysis with LTO (with LTO compiler generates
masked_gather, while before regular loads were emitted because of extra
data, availbale at LTO time).
SingleSource/UnitTests/matrix-types-spec - more vector code.
MultiSource/Applications/JM/lencod/lencod - same.
External/SPEC/CINT2006/464.h264ref/464.h264ref - same.
MultiSource/Benchmarks/7zip/7zip-benchmark - same.
External/SPEC/CINT2006/445.gobmk/445.gobmk - no changes.
External/SPEC/CFP2017rate/510.parest_r/510.parest_r - more vector code.
External/SPEC/CFP2006/447.dealII/447.dealII - same
External/SPEC/CINT2017speed/620.omnetpp_s/620.omnetpp_s - same
External/SPEC/CINT2017rate/520.omnetpp_r/520.omnetpp - same
External/SPEC/CFP2017rate/511.povray_r/511.povray - same
External/SPEC/CFP2006/453.povray/453.povray - same
External/SPEC/CFP2017rate/526.blender_r/526.blender_r - same
External/SPEC/CFP2017rate/538.imagick_r/538.imagick_r - same
External/SPEC/CFP2017speed/638.imagick_s/638.imagick_s - same
Differential Revision: https://reviews.llvm.org/D127219
We can skip the analysis of the constant nodes, their order should not
affect the ordering of the trees/subtrees.
Differential Revision: https://reviews.llvm.org/D127775
Improved/fixed cost modeling for shuffles by providing masks, improved
cost model for non-identity insertelements.
Differential Revision: https://reviews.llvm.org/D115462
Improved/fixed cost modeling for shuffles by providing masks, improved
cost model for non-identity insertelements.
Differential Revision: https://reviews.llvm.org/D115462
Improved/fixed cost modeling for shuffles by providing masks, improved
cost model for non-identity insertelements.
Differential Revision: https://reviews.llvm.org/D115462
Extractelement instructions may come from different basic blocks, need
to take it into account when looking for a last instruction in the
bundle to prevent compiler crash.
Differential Revision: https://reviews.llvm.org/D126777
Need to handle a corner case correctly, if all elements are Undefs/Poisons,
need to emit actual values, not just poisons.
Differential Revision: https://reviews.llvm.org/D126298
ScatterVectorize nodes should be handled same way as gathers in
reorderBottomToTop function, since we can simple reorder the loads in
this node. Because of that need to include such nodes to the list of
gathered nodes to fix compiler crash.
Differential Revision: https://reviews.llvm.org/D126378
SLP should build ScatterVectorize nodes only if they actually end up
with masked gather rather than with scalarization. In the second
scenario better to build a gather node.
Differential Revision: https://reviews.llvm.org/D126379
Need to use all ReductionOps when propagating flags for the reduction
ops, otherwise transformation is not correct. Plus, need to drop nuw/nsw
flags.
Differential Revision: https://reviews.llvm.org/D126371
The crash is caused by incorrect order set by reorderBottomToTop(), which
happens when it is reordering a TreeEntry which has a user that has already been
reordered earlier. Please see the detailed description in the lit test.
Differential Revision: https://reviews.llvm.org/D126099
SLP vectorizer emits extracts for externally used vectorized scalars and
estimates the cost for each such extract. But in many cases these
scalars are input for insertelement instructions, forming buildvector,
and instead of extractelement/insertelement pair we can emit/cost
estimate shuffle(s) cost and generate series of shuffles, which can be
further optimized.
Tested using test-suite (+SPEC2017), the tests passed, SLP was able to
generate/vectorize more instructions in many cases and it allowed to reduce
number of re-vectorization attempts (where we could try to vectorize
buildector insertelements again and again).
Differential Revision: https://reviews.llvm.org/D107966
This reverts commit fc9c59c355.
The patch triggers an assertion when building SPEC on X86. Reduced
reproducer shared at D107966.
Also reverts follow-up commit 11a09af76d.
SLP vectorizer emits extracts for externally used vectorized scalars and
estimates the cost for each such extract. But in many cases these
scalars are input for insertelement instructions, forming buildvector,
and instead of extractelement/insertelement pair we can emit/cost
estimate shuffle(s) cost and generate series of shuffles, which can be
further optimized.
Tested using test-suite (+SPEC2017), the tests passed, SLP was able to
generate/vectorize more instructions in many cases and it allowed to reduce
number of re-vectorization attempts (where we could try to vectorize
buildector insertelements again and again).
Differential Revision: https://reviews.llvm.org/D107966
When we generate a horizontal reduction of floating adds fed by a vectorized
tree rooted at floating multiplies, we should account for the cost of no
longer being able to generate scalar FMAs. Similarly, if we vectorize a
list of floating multiplies that each feeds a single floating add, we should
again account for this cost.
The first test was reduced from a case where the vectorizable tree looked
barely profitable (cost -1) with a horizontal reduction, but produced
substantially worse code than allowing the FMAs to be generated. The second
test was derived from the first: we again generate a horizontal reduction
here, but even if the horizontal reduction is forced to be unprofitable, we
try to vectorize the multiplies. I have follow-up patches to address these
issues.
Differential Revision: https://reviews.llvm.org/D124867
Alexey Bataev