At the point when we perform `emitTransformedIndex`, we have a broken IR (in
particular, we have Phis for which not every incoming value is properly set). On
such IR, it is illegal to create SCEV expressions, because their internal
simplification process may try to prove some predicates and break when it
stumbles across some broken IR.
The only purpose of using SCEV in this particular place is attempt to simplify
the generated code slightly. It seems that the result isn't worth it, because
some trivial cases (like addition of zero and multiplication by 1) can be
handled separately if needed, but more generally InstCombine is able to achieve
the goals we want to achieve by using SCEV.
This patch fixes a functional crash described in PR39160, and as side-effect it
also generates a bit smarter code in some simple cases. It also may cause some
optimality loss (i.e. we will now generate `mul` by power of `2` instead of
shift etc), but there is nothing what InstCombine could not handle later. In
case of dire need, we can support more trivial cases just in place.
Note that this patch only fixes one particular case of the general problem that
LV misuses SCEV, attempting to create SCEVs or prove predicates on invalid IR.
The general solution, however, seems complex enough.
Differential Revision: https://reviews.llvm.org/D52881
Reviewed By: fhahn, hsaito
llvm-svn: 343954
This patch fixes PR39099.
When strided loads are predicated, each of them will form an interleaved-group
(with gaps). However, subsequent stages of vectorization (planning and
transformation) assume that if a load is part of an Interleave-Group it is not
predicated, resulting in wrong code - unmasked wide loads are created.
The Interleaving Analysis does take care not to have conditional interleave
groups of size > 1, but until we extend the planning and transformation stages
to support masked-interleave-groups we should also avoid having them for
size == 1.
Reviewers: Ayal, hsaito, dcaballe, fhahn
Reviewed By: Ayal
Differential Revision: https://reviews.llvm.org/D52682
llvm-svn: 343931
Summary:
We are overly conservative in loop vectorizer with respect to stores to loop
invariant addresses.
More details in https://bugs.llvm.org/show_bug.cgi?id=38546
This is the first part of the fix where we start with vectorizing loop invariant
values to loop invariant addresses.
This also includes changes to ORE for stores to invariant address.
Reviewers: anemet, Ayal, mkuper, mssimpso
Subscribers: llvm-commits
Differential Revision: https://reviews.llvm.org/D50665
llvm-svn: 343028
There were two combines not covered by the check before now, neither of which
actually differed from normal in the benefit analysis.
The most recent seems to be because it was just added at the top of the
function (naturally). The older is from way back in 2008 (r46687) when we just
didn't put those checks in so routinely, and has been diligently maintained
since.
llvm-svn: 341831
Fix a latent bug in loop vectorizer which generates incorrect code for
memory accesses that are executed conditionally. As pointed in review,
this bug definitely affects uniform loads and may affect conditional
stores that should have turned into scatters as well).
The code gen for conditionally executed uniform loads on architectures
that support masked gather instructions is broken.
Without this patch, we were unconditionally executing the *conditional*
load in the vectorized version.
This patch does the following:
1. Uniform conditional loads on architectures with gather support will
have correct code generated. In particular, the cost model
(setCostBasedWideningDecision) is fixed.
2. For the recipes which are handled after the widening decision is set,
we use the isScalarWithPredication(I, VF) form which is added in the
patch.
3. Fix the vectorization cost model for scalarization
(getMemInstScalarizationCost): implement and use isPredicatedInst to
identify *all* predicated instructions, not just scalar+predicated. So,
now the cost for scalarization will be increased for maskedloads/stores
and gather/scatter operations. In short, we should be choosing the
gather/scatter in place of scalarization on archs where it is
profitable.
4. We needed to weaken the assert in useEmulatedMaskMemRefHack.
Reviewers: Ayal, hsaito, mkuper
Differential Revision: https://reviews.llvm.org/D51313
llvm-svn: 341673
This is fix for PR38786.
First order recurrence phis were incorrectly treated as uniform,
which caused them to be vectorized as uniform instructions.
Patch by Ayal Zaks and Orivej Desh!
Reviewed by: Anna
Differential Revision: https://reviews.llvm.org/D51639
llvm-svn: 341416
This reverts r319889.
Unfortunately, wrapping flags are not a part of SCEV's identity (they
do not participate in computing a hash value or in equality
comparisons) and in fact they could be assigned after the fact w/o
rebuilding a SCEV.
Grep for const_cast's to see quite a few of examples, apparently all
for AddRec's at the moment.
So, if 2 expressions get built in 2 slightly different ways: one with
flags set in the beginning, the other with the flags attached later
on, we may end up with 2 expressions which are exactly the same but
have their operands swapped in one of the commutative N-ary
expressions, and at least one of them will have "sorted by complexity"
invariant broken.
2 identical SCEV's won't compare equal by pointer comparison as they
are supposed to.
A real-world reproducer is added as a regression test: the issue
described causes 2 identical SCEV expressions to have different order
of operands and therefore compare not equal, which in its turn
prevents LoadStoreVectorizer from vectorizing a pair of consecutive
loads.
On a larger example (the source of the test attached, which is a
bugpoint) I have seen even weirder behavior: adding a constant to an
existing SCEV changes the order of the existing terms, for instance,
getAddExpr(1, ((A * B) + (C * D))) returns (1 + (C * D) + (A * B)).
Differential Revision: https://reviews.llvm.org/D40645
llvm-svn: 340777
This patch changes order of transform in InstCombineCompares to avoid
performing transforms based on ranges which produce complex bit arithmetics
before more simple things (like folding with constants) are done. See PR37636
for the motivating example.
Differential Revision: https://reviews.llvm.org/D48584
Reviewed By: spatel, lebedev.ri
llvm-svn: 336172
redundant-vf2-cost.ll is X86 specific. Moved from
test/Transforms/LoopVectorize/redundant-vf2-cost.ll to
test/Transforms/LoopVectorize/X86/redundant-vf2-cost.ll
llvm-svn: 334854
These weren't included in D19544 - probably just an oversight.
D40044 made it more likely that we'll have LLVM math intrinsics rather
than libcalls, so this bug was more easily exposed.
As the tests/code show, we already have the complete mappings for pow/exp/log.
I don't have any experience with SVML, so I don't know if anything else is
missing. It's also not clear to me that we should be doing this transform in
IR rather than DAG/isel, but that's a separate issue.
Differential Revision: https://reviews.llvm.org/D47610
llvm-svn: 334211
Summary:
Getelementptr returns a vector of pointers, instead of a single address,
when one or more of its arguments is a vector. In such case it is not
possible to simplify the expression by inserting a bitcast of operand(0)
into the destination type, as it will create a bitcast between different
sizes.
Reviewers: majnemer, mkuper, mssimpso, spatel
Reviewed By: spatel
Subscribers: lebedev.ri, llvm-commits
Differential Revision: https://reviews.llvm.org/D46379
llvm-svn: 333783
This patch aims to match the changes introduced in gcc by
https://gcc.gnu.org/ml/gcc-cvs/2018-04/msg00534.html. The
IBT feature definition is removed, with the IBT instructions
being freely available on all X86 targets. The shadow stack
instructions are also being made freely available, and the
use of all these CET instructions is controlled by the module
flags derived from the -fcf-protection clang option. The hasSHSTK
option remains since clang uses it to determine availability of
shadow stack instruction intrinsics, but it is no longer directly used.
Comes with a clang patch (D46881).
Patch by mike.dvoretsky
Differential Revision: https://reviews.llvm.org/D46882
llvm-svn: 332705
In order to set breakpoints on labels and list source code around
labels, we need collect debug information for labels, i.e., label
name, the function label belong, line number in the file, and the
address label located. In order to keep these information in LLVM
IR and to allow backend to generate debug information correctly.
We create a new kind of metadata for labels, DILabel. The format
of DILabel is
!DILabel(scope: !1, name: "foo", file: !2, line: 3)
We hope to keep debug information as much as possible even the
code is optimized. So, we create a new kind of intrinsic for label
metadata to avoid the metadata is eliminated with basic block.
The intrinsic will keep existing if we keep it from optimized out.
The format of the intrinsic is
llvm.dbg.label(metadata !1)
It has only one argument, that is the DILabel metadata. The
intrinsic will follow the label immediately. Backend could get the
label metadata through the intrinsic's parameter.
We also create DIBuilder API for labels to be used by Frontend.
Frontend could use createLabel() to allocate DILabel objects, and use
insertLabel() to insert llvm.dbg.label intrinsic in LLVM IR.
Differential Revision: https://reviews.llvm.org/D45024
Patch by Hsiangkai Wang.
llvm-svn: 331841
Summary:
This fixes a build break with r331269.
test/Transforms/LoopVectorize/pr23997.ll
should be in:
test/Transforms/LoopVectorize/X86/pr23997.ll
llvm-svn: 331281
Summary:
This is a fix for PR23997.
The loop vectorizer is not preserving the inbounds property of GEPs that it creates.
This is inhibiting some optimizations. This patch preserves the inbounds property in
the case where a load/store is being fed by an inbounds GEP.
Reviewers: mkuper, javed.absar, hsaito
Reviewed By: hsaito
Subscribers: dcaballe, hsaito, llvm-commits
Differential Revision: https://reviews.llvm.org/D46191
llvm-svn: 331269
Summary:
Revert r325687 workaround for PR36032 since
a fix was committed in r326154.
Reviewers: sbaranga
Differential Revision: http://reviews.llvm.org/D44768
From: Evgeny Stupachenko <evstupac@gmail.com>
<evgeny.v.stupachenko@intel.com>
llvm-svn: 328257
Summary:
It turned out to be error-prone to expect the callers to handle that - better to
leave the decision to this routine and make the required data to be explicitly
passed to the function.
This handles the case that was missed in the r322473 and fixes the assert
mentioned in PR36524.
Reviewers: dorit, mssimpso, Ayal, dcaballe
Reviewed By: dcaballe
Subscribers: Ka-Ka, hiraditya, dneilson, hsaito, llvm-commits
Differential Revision: https://reviews.llvm.org/D43812
llvm-svn: 327960
The range of SCEVUnknown Phi which merges values `X1, X2, ..., XN`
can be evaluated as `U(Range(X1), Range(X2), ..., Range(XN))`.
Reviewed By: sanjoy
Differential Revision: https://reviews.llvm.org/D43810
llvm-svn: 326418
There are too many perf regressions resulting from this, so we need to
investigate (and add tests for) targets like ARM and AArch64 before
trying to reinstate.
llvm-svn: 325658
This change was mentioned at least as far back as:
https://bugs.llvm.org/show_bug.cgi?id=26837#c26
...and I found a real program that is harmed by this:
Himeno running on AMD Jaguar gets 6% slower with SLP vectorization:
https://bugs.llvm.org/show_bug.cgi?id=36280
...but the change here appears to solve that bug only accidentally.
The div/rem costs for x86 look very wrong in some cases, but that's already true,
so we can fix those in follow-up patches. There's also evidence that more cost model
changes are needed to solve SLP problems as shown in D42981, but that's an independent
problem (though the solution may be adjusted after this change is made).
Differential Revision: https://reviews.llvm.org/D43079
llvm-svn: 325515
This will cause the vectorizers to do some limiting of the vector widths they create. This is not a strict limit. There are reasons I know of that the loop vectorizer will generate larger vectors for.
I've written this in such a way that the interface will only return a properly supported width(0/128/256/512) even if the attribute says something funny like 384 or 10.
This has been split from D41895 with the remainder in a follow up commit.
llvm-svn: 323015
VecValuesToIgnore holds values that will not appear in the vectorized loop.
We should therefore ignore their cost when VF > 1.
Differential Revision: https://reviews.llvm.org/D40883
llvm-svn: 320463
This patch is part of D38676.
The patch introduces two new Recipes to handle instructions whose vectorization
involves masking. These Recipes take VPlan-level masks in D38676, but still rely
on ILV's existing createEdgeMask(), createBlockInMask() in this patch.
VPBlendRecipe handles intra-loop phi nodes, which are vectorized as a sequence
of SELECTs. Its execute() code is refactored out of ILV::widenPHIInstruction(),
which now handles only loop-header phi nodes.
VPWidenMemoryInstructionRecipe handles load/store which are to be widened
(but are not part of an Interleave Group). In this patch it simply calls
ILV::vectorizeMemoryInstruction on execute().
Differential Revision: https://reviews.llvm.org/D39068
llvm-svn: 318149
This is no-functional-change-intended.
This is repackaging the functionality of D30333 (defer switch-to-lookup-tables) and
D35411 (defer folding unconditional branches) with pass parameters rather than a named
"latesimplifycfg" pass. Now that we have individual options to control the functionality,
we could decouple when these fire (but that's an independent patch if desired).
The next planned step would be to add another option bit to disable the sinking transform
mentioned in D38566. This should also make it clear that the new pass manager needs to
be updated to limit simplifycfg in the same way as the old pass manager.
Differential Revision: https://reviews.llvm.org/D38631
llvm-svn: 316835
These are changes to reduce redundant computations when calculating a
feasible vectorization factor:
1. early return when target has no vector registers
2. don't compute register usage for the default VF.
Suggested during review for D37702.
llvm-svn: 313176
Summary:
When the MaxVectorSize > ConstantTripCount, we should just clamp the
vectorization factor to be the ConstantTripCount.
This vectorizes loops where the TinyTripCountThreshold >= TripCount < MaxVF.
Earlier we were finding the maximum vector width, which could be greater than
the trip count itself. The Loop vectorizer does all the work for generating a
vectorizable loop, but in the end we would always choose the scalar loop (since
the VF > trip count). This allows us to choose the VF keeping in mind the trip
count if available.
This is a fix on top of rL312472.
Reviewers: Ayal, zvi, hfinkel, dneilson
Reviewed by: Ayal
Subscribers: llvm-commits
Differential Revision: https://reviews.llvm.org/D37702
llvm-svn: 313046
Summary:
Improve how MaxVF is computed while taking into account that MaxVF should not be larger than the loop's trip count.
Other than saving on compile-time by pruning the possible MaxVF candidates, this patch fixes pr34438 which exposed the following flow:
1. Short trip count identified -> Don't bail out, set OptForSize:=True to avoid tail-loop and runtime checks.
2. Compute MaxVF returned 16 on a target supporting AVX512.
3. OptForSize -> choose VF:=MaxVF.
4. Bail out because TripCount = 8, VF = 16, TripCount % VF !=0 means we need a tail loop.
With this patch step 2. will choose MaxVF=8 based on TripCount.
Reviewers: Ayal, dorit, mkuper, hfinkel
Reviewed By: hfinkel
Subscribers: hfinkel, llvm-commits
Differential Revision: https://reviews.llvm.org/D37425
llvm-svn: 312472
Store operation takes 2 UOps on X86 processors. The exact cost calculation affects several optimization passes including loop unroling.
This change compensates performance degradation caused by https://reviews.llvm.org/D34458 and shows improvements on some benchmarks.
Differential Revision: https://reviews.llvm.org/D35888
llvm-svn: 311285
Added a separate metadata to indicate when the loop
has already been vectorized instead of setting width and count to 1.
Patch written by Divya Shanmughan and Aditya Kumar
Differential Revision: https://reviews.llvm.org/D36220
llvm-svn: 311281
Summary:
The New Pass Manager infrastructure was forgetting to keep around the optimization remark yaml file that the compiler might have been producing. This meant setting the option to '-' for stdout worked, but setting it to a filename didn't give file output (presumably it was deleted because compilation didn't explicitly keep it). This change just ensures that the file is kept if compilation succeeds.
So far I have updated one of the optimization remark output tests to add a version with the new pass manager. It is my intention for this patch to also include changes to all tests that use `-opt-remark-output=` but I wanted to get the code patch ready for review while I was making all those changes.
Fixes https://bugs.llvm.org/show_bug.cgi?id=33951
Reviewers: anemet, chandlerc
Reviewed By: anemet, chandlerc
Subscribers: javed.absar, chandlerc, fhahn, llvm-commits
Differential Revision: https://reviews.llvm.org/D36906
llvm-svn: 311271
Summary:
When simplifying unconditional branches from empty blocks, we pre-test if the
BB belongs to a set of loop headers and keep the block to prevent passes from
destroying canonical loop structure. However, the current algorithm fails if
the destination of the branch is a loop header. Especially when such a loop's
latch block is folded into loop header it results in additional backedges and
LoopSimplify turns it into a nested loop which prevent later optimizations
from being applied (e.g., loop unrolling and loop interleaving).
This patch augments the existing algorithm by further checking if the
destination of the branch belongs to a set of loop headers and defer
eliminating it if yes to LateSimplifyCFG.
Fixes PR33605: https://bugs.llvm.org/show_bug.cgi?id=33605
Reviewers: efriedma, mcrosier, pacxx, hsung, davidxl
Reviewed By: efriedma
Subscribers: ashutosh.nema, gberry, javed.absar, llvm-commits
Differential Revision: https://reviews.llvm.org/D35411
llvm-svn: 308422
Generate a single test to decide if there are enough iterations to jump to the
vectorized loop, or else go to the scalar remainder loop. This test compares the
Scalar Trip Count: if STC < VF * UF go to the scalar loop. If
requiresScalarEpilogue() holds, at-least one iteration must remain scalar; the
rest can be used to form vector iterations. So in this case the test checks
instead if (STC - 1) < VF * UF by comparing STC <= VF * UF, and going to the
scalar loop if so. Otherwise the vector loop is entered for at-least one vector
iteration.
This test covers the case where incrementing the backedge-taken count will
overflow leading to an incorrect trip count of zero. In this (rare) case we will
also avoid the vector loop and jump to the scalar loop.
This patch simplifies the existing tests and effectively removes the basic-block
originally named "min.iters.checked", leaving the single test in block
"vector.ph".
Original observation and initial patch by Evgeny Stupachenko.
Differential Revision: https://reviews.llvm.org/D34150
llvm-svn: 308421
this patch updates the cost of addq\subq (add\subtract of vectors of 64bits)
based on the performance numbers of SLM arch.
Differential Revision: https://reviews.llvm.org/D33983
llvm-svn: 306974
Summary:
vectorizer-maximize-bandwidth is generally useful in terms of performance. I've tested the impact of changing this to default on speccpu benchmarks on sandybridge machines. The result shows non-negative impact:
spec/2006/fp/C++/444.namd 26.84 -0.31%
spec/2006/fp/C++/447.dealII 46.19 +0.89%
spec/2006/fp/C++/450.soplex 42.92 -0.44%
spec/2006/fp/C++/453.povray 38.57 -2.25%
spec/2006/fp/C/433.milc 24.54 -0.76%
spec/2006/fp/C/470.lbm 41.08 +0.26%
spec/2006/fp/C/482.sphinx3 47.58 -0.99%
spec/2006/int/C++/471.omnetpp 22.06 +1.87%
spec/2006/int/C++/473.astar 22.65 -0.12%
spec/2006/int/C++/483.xalancbmk 33.69 +4.97%
spec/2006/int/C/400.perlbench 33.43 +1.70%
spec/2006/int/C/401.bzip2 23.02 -0.19%
spec/2006/int/C/403.gcc 32.57 -0.43%
spec/2006/int/C/429.mcf 40.35 +0.27%
spec/2006/int/C/445.gobmk 26.96 +0.06%
spec/2006/int/C/456.hmmer 24.4 +0.19%
spec/2006/int/C/458.sjeng 27.91 -0.08%
spec/2006/int/C/462.libquantum 57.47 -0.20%
spec/2006/int/C/464.h264ref 46.52 +1.35%
geometric mean +0.29%
The regression on 453.povray seems real, but is due to secondary effects as all hot functions are bit-identical with and without the flag.
I started this patch to consult upstream opinions on this. It will be greatly appreciated if the community can help test the performance impact of this change on other architectures so that we can decided if this should be target-dependent.
Reviewers: hfinkel, mkuper, davidxl, chandlerc
Reviewed By: chandlerc
Subscribers: rengolin, sanjoy, javed.absar, bjope, dorit, magabari, RKSimon, llvm-commits, mzolotukhin
Differential Revision: https://reviews.llvm.org/D33341
llvm-svn: 306933
It may be detrimental to vectorize loops with very small trip count, as various
costs of the vectorized loop body as well as enclosing overheads including
runtime tests and scalar iterations may outweigh the gains of vectorizing. The
current cost model measures the cost of the vectorized loop body only, expecting
it will amortize other costs, and loops with known or expected very small trip
counts are not vectorized at all. This patch allows loops with very small trip
counts to be vectorized, but under OptForSize constraints, which ensure the cost
of the loop body is dominant, having no runtime guards nor scalar iterations.
Patch inspired by D32451.
Differential Revision: https://reviews.llvm.org/D34373
llvm-svn: 306803
Summary:
vectorizer-maximize-bandwidth is generally useful in terms of performance. I've tested the impact of changing this to default on speccpu benchmarks on sandybridge machines. The result shows non-negative impact:
spec/2006/fp/C++/444.namd 26.84 -0.31%
spec/2006/fp/C++/447.dealII 46.19 +0.89%
spec/2006/fp/C++/450.soplex 42.92 -0.44%
spec/2006/fp/C++/453.povray 38.57 -2.25%
spec/2006/fp/C/433.milc 24.54 -0.76%
spec/2006/fp/C/470.lbm 41.08 +0.26%
spec/2006/fp/C/482.sphinx3 47.58 -0.99%
spec/2006/int/C++/471.omnetpp 22.06 +1.87%
spec/2006/int/C++/473.astar 22.65 -0.12%
spec/2006/int/C++/483.xalancbmk 33.69 +4.97%
spec/2006/int/C/400.perlbench 33.43 +1.70%
spec/2006/int/C/401.bzip2 23.02 -0.19%
spec/2006/int/C/403.gcc 32.57 -0.43%
spec/2006/int/C/429.mcf 40.35 +0.27%
spec/2006/int/C/445.gobmk 26.96 +0.06%
spec/2006/int/C/456.hmmer 24.4 +0.19%
spec/2006/int/C/458.sjeng 27.91 -0.08%
spec/2006/int/C/462.libquantum 57.47 -0.20%
spec/2006/int/C/464.h264ref 46.52 +1.35%
geometric mean +0.29%
The regression on 453.povray seems real, but is due to secondary effects as all hot functions are bit-identical with and without the flag.
I started this patch to consult upstream opinions on this. It will be greatly appreciated if the community can help test the performance impact of this change on other architectures so that we can decided if this should be target-dependent.
Reviewers: hfinkel, mkuper, davidxl, chandlerc
Reviewed By: chandlerc
Subscribers: rengolin, sanjoy, javed.absar, bjope, dorit, magabari, RKSimon, llvm-commits, mzolotukhin
Differential Revision: https://reviews.llvm.org/D33341
llvm-svn: 306336
Summary:
vectorizer-maximize-bandwidth is generally useful in terms of performance. I've tested the impact of changing this to default on speccpu benchmarks on sandybridge machines. The result shows non-negative impact:
spec/2006/fp/C++/444.namd 26.84 -0.31%
spec/2006/fp/C++/447.dealII 46.19 +0.89%
spec/2006/fp/C++/450.soplex 42.92 -0.44%
spec/2006/fp/C++/453.povray 38.57 -2.25%
spec/2006/fp/C/433.milc 24.54 -0.76%
spec/2006/fp/C/470.lbm 41.08 +0.26%
spec/2006/fp/C/482.sphinx3 47.58 -0.99%
spec/2006/int/C++/471.omnetpp 22.06 +1.87%
spec/2006/int/C++/473.astar 22.65 -0.12%
spec/2006/int/C++/483.xalancbmk 33.69 +4.97%
spec/2006/int/C/400.perlbench 33.43 +1.70%
spec/2006/int/C/401.bzip2 23.02 -0.19%
spec/2006/int/C/403.gcc 32.57 -0.43%
spec/2006/int/C/429.mcf 40.35 +0.27%
spec/2006/int/C/445.gobmk 26.96 +0.06%
spec/2006/int/C/456.hmmer 24.4 +0.19%
spec/2006/int/C/458.sjeng 27.91 -0.08%
spec/2006/int/C/462.libquantum 57.47 -0.20%
spec/2006/int/C/464.h264ref 46.52 +1.35%
geometric mean +0.29%
The regression on 453.povray seems real, but is due to secondary effects as all hot functions are bit-identical with and without the flag.
I started this patch to consult upstream opinions on this. It will be greatly appreciated if the community can help test the performance impact of this change on other architectures so that we can decided if this should be target-dependent.
Reviewers: hfinkel, mkuper, davidxl, chandlerc
Reviewed By: chandlerc
Subscribers: rengolin, sanjoy, javed.absar, bjope, dorit, magabari, RKSimon, llvm-commits, mzolotukhin
Differential Revision: https://reviews.llvm.org/D33341
llvm-svn: 305960
Summary:
Existing heuristic uses the ratio between the function entry
frequency and the loop invocation frequency to find cold loops. However,
even if the loop executes frequently, if it has a small trip count per
each invocation, vectorization is not beneficial. On the other hand,
even if the loop invocation frequency is much smaller than the function
invocation frequency, if the trip count is high it is still beneficial
to vectorize the loop.
This patch uses estimated trip count computed from the profile metadata
as a primary metric to determine coldness of the loop. If the estimated
trip count cannot be computed, it falls back to the original heuristics.
Reviewers: Ayal, mssimpso, mkuper, danielcdh, wmi, tejohnson
Reviewed By: tejohnson
Subscribers: tejohnson, mzolotukhin, llvm-commits
Differential Revision: https://reviews.llvm.org/D32451
llvm-svn: 305729
The default behavior of -Rpass-analysis=loop-vectorizer is to report only the
first reason encountered for not vectorizing, if one is found, at which time the
vectorizer aborts its handling of the loop. This patch allows multiple reasons
for not vectorizing to be identified and reported, at the potential expense of
additional compile-time, under allowExtraAnalysis which can currently be turned
on by Clang's -fsave-optimization-record and opt's -pass-remarks-missed.
Removed from LoopVectorizationLegality::canVectorize() the redundant checking
and reporting if we CantComputeNumberOfIterations, as LAI::canAnalyzeLoop() also
does that. This redundancy is caught by a lit test once multiple reasons are
reported.
Patch initially developed by Dror Barak.
Differential Revision: https://reviews.llvm.org/D33396
llvm-svn: 303613
Fixes PR31789 - When loop-vectorize tries to use these intrinsics for a
non-default address space pointer we fail with a "Calling a function with a
bad singature!" assertion. This patch solves this by adding the 'vector of
pointers' argument as an overloaded type which will determine the address
space.
Differential revision: https://reviews.llvm.org/D31490
llvm-svn: 302018
This patch reapplies r298620. The original patch was reverted because of two
issues. First, the patch exposed a bug in InstCombine that caused the Chromium
builds to fail (PR32414). This issue was fixed in r299017. Second, the patch
introduced a bug in the vectorizer's scalars analysis that caused test suite
builds to fail on SystemZ. The scalars analysis was too aggressive and marked a
memory instruction scalar, even though it was going to be vectorized. This
issue has been fixed in the current patch and several new test cases for the
scalars analysis have been added.
llvm-svn: 299770
Reason: breaks linking Chromium with LLD + ThinLTO (a pass crashes)
LLVM bug: https://bugs.llvm.org//show_bug.cgi?id=32413
Original change description:
[LV] Vectorize GEPs
This patch adds support for vectorizing GEPs. Previously, we only generated
vector GEPs on-demand when creating gather or scatter operations. All GEPs from
the original loop were scalarized by default, and if a pointer was to be stored
to memory, we would have to build up the pointer vector with insertelement
instructions.
With this patch, we will vectorize all GEPs that haven't already been marked
for scalarization.
The patch refines collectLoopScalars to more exactly identify the scalar GEPs.
The function now more closely resembles collectLoopUniforms. And the patch
moves vector GEP creation out of vectorizeMemoryInstruction and into the main
vectorization loop. The vector GEPs needed for gather and scatter operations
will have already been generated before vectoring the memory accesses.
Original Differential Revision: https://reviews.llvm.org/D30710
llvm-svn: 298735
This patch adds support for vectorizing GEPs. Previously, we only generated
vector GEPs on-demand when creating gather or scatter operations. All GEPs from
the original loop were scalarized by default, and if a pointer was to be stored
to memory, we would have to build up the pointer vector with insertelement
instructions.
With this patch, we will vectorize all GEPs that haven't already been marked
for scalarization.
The patch refines collectLoopScalars to more exactly identify the scalar GEPs.
The function now more closely resembles collectLoopUniforms. And the patch
moves vector GEP creation out of vectorizeMemoryInstruction and into the main
vectorization loop. The vector GEPs needed for gather and scatter operations
will have already been generated before vectoring the memory accesses.
Differential Revision: https://reviews.llvm.org/D30710
llvm-svn: 298620
The practice in LV is that we emit analysis remarks and then finally report
either a missed or applied remark on the final decision whether vectorization
is taking place. On this code path, we were closing with an analysis remark.
llvm-svn: 296578
Making the cost model selecting between Interleave, GatherScatter or Scalar vectorization form of memory instruction.
The right decision should be done for non-consecutive memory access instrcuctions that may have more than one vectorization solution.
This patch includes the following changes:
- Cost Model calculates the cost of Load/Store vector form and choose the better option between Widening, Interleave, GatherScactter and Scalarization. Cost Model keeps the widening decision.
- Arrays of Uniform and Scalar values are moved from Legality to Cost Model.
- Cost Model collects Uniforms and Scalars per VF. The collection is based on CM decision map of Loadis/Stores vectorization form.
- Vectorization of memory instruction is performed according to the CM decision.
Differential Revision: https://reviews.llvm.org/D27919
llvm-svn: 294503
If a memory instruction will be vectorized, but it's pointer operand is
non-consecutive-like, the instruction is a gather or scatter operation. Its
pointer operand will be non-uniform. This should fix PR31671.
Reference: https://llvm.org/bugs/show_bug.cgi?id=31671
Differential Revision: https://reviews.llvm.org/D28819
llvm-svn: 292254
updated instructions:
pmulld, pmullw, pmulhw, mulsd, mulps, mulpd, divss, divps, divsd, divpd, addpd and subpd.
special optimization case which replaces pmulld with pmullw\pmulhw\pshuf seq.
In case if the real operands bitwidth <= 16.
Differential Revision: https://reviews.llvm.org/D28104
llvm-svn: 291657
This code seems to be target dependent which may not be the same for all targets.
Passed the decision whether the given stride is complex or not to the target by sending stride information via SCEV to getAddressComputationCost instead of 'IsComplex'.
Specifically at X86 targets we dont see any significant address computation cost in case of the strided access in general.
Differential Revision: https://reviews.llvm.org/D27518
llvm-svn: 291106
This patch attempts to scalarize the operand expressions of predicated
instructions if they were conditionally executed in the original loop. After
scalarization, the expressions will be sunk inside the blocks created for the
predicated instructions. The transformation essentially performs
un-if-conversion on the operands.
The cost model has been updated to determine if scalarization is profitable. It
compares the cost of a vectorized instruction, assuming it will be
if-converted, to the cost of the scalarized instruction, assuming that the
instructions corresponding to each vector lane will be sunk inside a predicated
block, possibly avoiding execution. If it's more profitable to scalarize the
entire expression tree feeding the predicated instruction, the expression will
be scalarized; otherwise, it will be vectorized. We only consider the cost of
the entire expression to accurately estimate the cost of the required
insertelement and extractelement instructions.
Differential Revision: https://reviews.llvm.org/D26083
llvm-svn: 288909
The register usage algorithm incorrectly treats instructions whose value is
not used within the loop (e.g. those that do not produce a value).
The algorithm first calculates the usages within the loop. It iterates over
the instructions in order, and records at which instruction index each use
ends (in fact, they're actually recorded against the next index, as this is
when we want to delete them from the open intervals).
The algorithm then iterates over the instructions again, adding each
instruction in turn to a list of open intervals. Instructions are then
removed from the list of open intervals when they occur in the list of uses
ended at the current index.
The problem is, instructions which are not used in the loop are skipped.
However, although they aren't used, the last use of a value may have been
recorded against that instruction index. In this case, the use is not deleted
from the open intervals, which may then bump up the estimated register usage.
This patch fixes the issue by simply moving the "is used" check after the loop
which erases the uses at the current index.
Differential Revision: https://reviews.llvm.org/D26554
llvm-svn: 286969
Add explicit v16i16/v32i8 ADD/SUB costs, matching the costs of v4i64/v8i32 - they were missing for some reason.
This has side effects on the LV max bandwidth tests (AVX1 now prefers 128-bit vectors vs AVX2 which still prefers 256-bit)
llvm-svn: 286832
This is PR28376.
Unfortunately given the current structure of optimization diagnostics we
lack the capability to tell whether the user has
passed -Rpass-analysis=loop-vectorize since this is local to the
front-end (BackendConsumer::OptimizationRemarkHandler).
So rather than printing this even if the user has already
passed -Rpass-analysis, this patch just punts and stops recommending
this option. I don't think that getting this right is worth the
complexity.
Differential Revision: https://reviews.llvm.org/D26563
llvm-svn: 286662
possible pointer-wrap-around concerns, in some cases.
Before this patch, collectConstStridedAccesses (part of interleaved-accesses
analysis) called getPtrStride with [Assume=false, ShouldCheckWrap=true] when
examining all candidate pointers. This is too conservative. Instead, this
patch makes collectConstStridedAccesses use an optimistic approach, calling
getPtrStride with [Assume=true, ShouldCheckWrap=false], and then, once the
candidate interleave groups have been formed, revisits the pointer-wrapping
analysis but only where it matters: namely, in groups that have gaps, and where
the gaps are not at the very end of the group (in which case the loop is
peeled). This second time getPtrStride is called with [Assume=false,
ShouldCheckWrap=true], but this could further be improved to using Assume=true,
once we also add the logic to track that we are not going to meet the scev
runtime checks threshold.
Differential Revision: https://reviews.llvm.org/D25276
llvm-svn: 285517
After r279649 when getting a vector value from VectorLoopValueMap, we create an
insertelement sequence on-demand if the value has been scalarized instead of
vectorized. We previously inserted this insertelement sequence before the
value's first vector user. However, this insert location is problematic if that
user is the phi node of a first-order recurrence. With this patch, we move the
insertelement sequence after the last scalar instruction we created when
scalarizing the value. Thus, the value's vector definition in the new loop will
immediately follow its scalar definitions. This should fix PR30183.
Reference: https://llvm.org/bugs/show_bug.cgi?id=30183
llvm-svn: 280001
This patch unifies the data structures we use for mapping instructions from the
original loop to their corresponding instructions in the new loop. Previously,
we maintained two distinct maps for this purpose: WidenMap and ScalarIVMap.
WidenMap maintained the vector values each instruction from the old loop was
represented with, and ScalarIVMap maintained the scalar values each scalarized
induction variable was represented with. With this patch, all values created
for the new loop are maintained in VectorLoopValueMap.
The change allows for several simplifications. Previously, when an instruction
was scalarized, we had to insert the scalar values into vectors in order to
maintain the mapping in WidenMap. Then, if a user of the scalarized value was
also scalar, we had to extract the scalar values from the temporary vector we
created. We now aovid these unnecessary scalar-to-vector-to-scalar conversions.
If a scalarized value is used by a scalar instruction, the scalar value is used
directly. However, if the scalarized value is needed by a vector instruction,
we generate the needed insertelement instructions on-demand.
A common idiom in several locations in the code (including the scalarization
code), is to first get the vector values an instruction from the original loop
maps to, and then extract a particular scalar value. This patch adds
getScalarValue for this purpose along side getVectorValue as an interface into
VectorLoopValueMap. These functions work together to return the requested
values if they're available or to produce them if they're not.
The mapping has also be made less permissive. Entries can be added to
VectorLoopValue map with the new initVector and initScalar functions.
getVectorValue has been modified to return a constant reference to the mapped
entries.
There's no real functional change with this patch; however, in some cases we
will generate slightly different code. For example, instead of an insertelement
sequence following the definition of an instruction, it will now precede the
first use of that instruction. This can be seen in the test case changes.
Differential Revision: https://reviews.llvm.org/D23169
llvm-svn: 279649
Shifts with a uniform but non-constant count were considered very expensive to
vectorize, because the splat of the uniform count and the shift would tend to
appear in different blocks. That made the splat invisible to ISel, and we'd
scalarize the shift at codegen time.
Since r201655, CodeGenPrepare sinks those splats to be next to their use, and we
are able to select the appropriate vector shifts. This updates the cost model to
to take this into account by making shifts by a uniform cheap again.
Differential Revision: https://reviews.llvm.org/D23049
llvm-svn: 277782
Update comment for isOutOfScope and add a testcase for uniform value being used
out of scope.
Differential Revision: https://reviews.llvm.org/D23073
llvm-svn: 277515
This patch enables the vectorizer to generate both scalar and vector versions
of an integer induction variable for a given loop. Previously, we only
generated a scalar induction variable if we knew all its users were going to be
scalar. Otherwise, we generated a vector induction variable. In the case of a
loop with both scalar and vector users of the induction variable, we would
generate the vector induction variable and extract scalar values from it for
the scalar users. With this patch, we now generate both versions of the
induction variable when there are both scalar and vector users and select which
version to use based on whether the user is scalar or vector.
Differential Revision: https://reviews.llvm.org/D22869
llvm-svn: 277474
Allowed loop vectorization with secondary FP IVs. Like this:
float *A;
float x = init;
for (int i=0; i < N; ++i) {
A[i] = x;
x -= fp_inc;
}
The auto-vectorization is possible when the induction binary operator is "fast" or the function has "unsafe" attribute.
Differential Revision: https://reviews.llvm.org/D21330
llvm-svn: 276554
This patch moves the update instruction for vectorized integer induction phi
nodes to the end of the latch block. This ensures consistent placement of all
induction updates across all the kinds of int inductions we create (scalar,
splat vector, or vector phi).
Differential Revision: https://reviews.llvm.org/D22416
llvm-svn: 276339
For instructions in uniform set, they will not have vector versions so
add them to VecValuesToIgnore.
For induction vars, those only used in uniform instructions or consecutive
ptrs instructions have already been added to VecValuesToIgnore above. For
those induction vars which are only used in uniform instructions or
non-consecutive/non-gather scatter ptr instructions, the related phi and
update will also be added into VecValuesToIgnore set.
The change will make the vector RegUsages estimation less conservative.
Differential Revision: https://reviews.llvm.org/D20474
The recommit fixed the testcase global_alias.ll.
llvm-svn: 275936
For instructions in uniform set, they will not have vector versions so
add them to VecValuesToIgnore.
For induction vars, those only used in uniform instructions or consecutive
ptrs instructions have already been added to VecValuesToIgnore above. For
those induction vars which are only used in uniform instructions or
non-consecutive/non-gather scatter ptr instructions, the related phi and
update will also be added into VecValuesToIgnore set.
The change will make the vector RegUsages estimation less conservative.
Differential Revision: https://reviews.llvm.org/D20474
llvm-svn: 275912
Max Kazantsev