This is a latent bug that's been hanging around for a while. For a loop-invariant
pointer, expandBounds would return the range {Ptr, Ptr}, but this was interpreted
as a half-open range, not a closed range. So we ended up planting incorrect
bounds checks. Even worse, they were tautological, so we ended up incorrectly
executing the optimized loop.
llvm-svn: 299526
This reverts r293386, r294027, r294029 and r296411.
Turns out the SLP tree isn't actually a "tree" and we don't handle
accessing the same packet of loads in several different orders well,
causing miscompiles.
Revert until we can fix this properly.
llvm-svn: 297493
for VectorizeTree() API.This API uses it for proper mask computation to be used in shufflevector IR.
The fix is to compute the mask for out of order memory accesses while building the vectorizable tree
instead of actual vectorization of vectorizable tree.It also needs to recompute the proper Lane for
external use of vectorizable scalars based on shuffle mask.
Reviewers: mkuper
Differential Revision: https://reviews.llvm.org/D30159
Change-Id: Ide8773ce0ad3562f3cf4d1a0ad0f487e2f60ce5d
llvm-svn: 296863
for VectorizeTree() API.This API uses it for proper mask computation to be used in shufflevector IR.
The fix is to compute the mask for out of order memory accesses while building the vectorizable tree
instead of actual vectorization of vectorizable tree.
Reviewers: mkuper
Differential Revision: https://reviews.llvm.org/D30159
Change-Id: Id1e287f073fa4959713ba545fa4254db5da8b40d
llvm-svn: 296575
proven larger than the loop-count
This fixes PR31098: Try to resolve statically data-dependences whose
compile-time-unknown distance can be proven larger than the loop-count,
instead of resorting to runtime dependence checking (which are not always
possible).
For vectorization it is sufficient to prove that the dependence distance
is >= VF; But in some cases we can prune unknown dependence distances early,
and even before selecting the VF, and without a runtime test, by comparing
the distance against the loop iteration count. Since the vectorized code
will be executed only if LoopCount >= VF, proving distance >= LoopCount
also guarantees that distance >= VF. This check is also equivalent to the
Strong SIV Test.
Reviewers: mkuper, anemet, sanjoy
Differential Revision: https://reviews.llvm.org/D28044
llvm-svn: 294892
This generalizes memory access sorting to use differences between SCEVs,
instead of relying on constant offsets. That allows us to properly do
SLP vectorization of non-sequentially ordered loads within loops bodies.
Differential Revision: https://reviews.llvm.org/D29425
llvm-svn: 294027
The jumbled scalar loads will be sorted while building the tree and these accesses will be marked to generate shufflevector after the vectorized load with proper mask.
Reviewers: hfinkel, mssimpso, mkuper
Differential Revision: https://reviews.llvm.org/D26905
Change-Id: I9c0c8e6f91a00076a7ee1465440a3f6ae092f7ad
llvm-svn: 293386
the latter to the Transforms library.
While the loop PM uses an analysis to form the IR units, the current
plan is to have the PM itself establish and enforce both loop simplified
form and LCSSA. This would be a layering violation in the analysis
library.
Fundamentally, the idea behind the loop PM is to *transform* loops in
addition to running passes over them, so it really seemed like the most
natural place to sink this was into the transforms library.
We can't just move *everything* because we also have loop analyses that
rely on a subset of the invariants. So this patch splits the the loop
infrastructure into the analysis management that has to be part of the
analysis library, and the transform-aware pass manager.
This also required splitting the loop analyses' printer passes out to
the transforms library, which makes sense to me as running these will
transform the code into LCSSA in theory.
I haven't split the unittest though because testing one component
without the other seems nearly intractable.
Differential Revision: https://reviews.llvm.org/D28452
llvm-svn: 291662
arguments much like the CGSCC pass manager.
This is a major redesign following the pattern establish for the CGSCC layer to
support updates to the set of loops during the traversal of the loop nest and
to support invalidation of analyses.
An additional significant burden in the loop PM is that so many passes require
access to a large number of function analyses. Manually ensuring these are
cached, available, and preserved has been a long-standing burden in LLVM even
with the help of the automatic scheduling in the old pass manager. And it made
the new pass manager extremely unweildy. With this design, we can package the
common analyses up while in a function pass and make them immediately available
to all the loop passes. While in some cases this is unnecessary, I think the
simplicity afforded is worth it.
This does not (yet) address loop simplified form or LCSSA form, but those are
the next things on my radar and I have a clear plan for them.
While the patch is very large, most of it is either mechanically updating loop
passes to the new API or the new testing for the loop PM. The code for it is
reasonably compact.
I have not yet updated all of the loop passes to correctly leverage the update
mechanisms demonstrated in the unittests. I'll do that in follow-up patches
along with improved FileCheck tests for those passes that ensure things work in
more realistic scenarios. In many cases, there isn't much we can do with these
until the loop simplified form and LCSSA form are in place.
Differential Revision: https://reviews.llvm.org/D28292
llvm-svn: 291651
Summary:
If LAA expands a bound that is loop invariant, but not hoisted out
of the loop body, it used to use that value anyway, causing a
non-domination error, because the memcheck block is of course not
dominated by the scalar loop body. Detect this situation and expand
the SCEV expression instead.
Fixes PR31251
Reviewers: anemet
Subscribers: mzolotukhin, llvm-commits
Differential Revision: https://reviews.llvm.org/D27397
llvm-svn: 288705
analyses to have a common type which is enforced rather than using
a char object and a `void *` type when used as an identifier.
This has a number of advantages. First, it at least helps some of the
confusion raised in Justin Lebar's code review of why `void *` was being
used everywhere by having a stronger type that connects to documentation
about this.
However, perhaps more importantly, it addresses a serious issue where
the alignment of these pointer-like identifiers was unknown. This made
it hard to use them in pointer-like data structures. We were already
dodging this in dangerous ways to create the "all analyses" entry. In
a subsequent patch I attempted to use these with TinyPtrVector and
things fell apart in a very bad way.
And it isn't just a compile time or type system issue. Worse than that,
the actual alignment of these pointer-like opaque identifiers wasn't
guaranteed to be a useful alignment as they were just characters.
This change introduces a type to use as the "key" object whose address
forms the opaque identifier. This both forces the objects to have proper
alignment, and provides type checking that we get it right everywhere.
It also makes the types somewhat less mysterious than `void *`.
We could go one step further and introduce a truly opaque pointer-like
type to return from the `ID()` static function rather than returning
`AnalysisKey *`, but that didn't seem to be a clear win so this is just
the initial change to get to a reliably typed and aligned object serving
is a key for all the analyses.
Thanks to Richard Smith and Justin Lebar for helping pick plausible
names and avoid making this refactoring many times. =] And thanks to
Sean for the super fast review!
While here, I've tried to move away from the "PassID" nomenclature
entirely as it wasn't really helping and is overloaded with old pass
manager constructs. Now we have IDs for analyses, and key objects whose
address can be used as IDs. Where possible and clear I've shortened this
to just "ID". In a few places I kept "AnalysisID" to make it clear what
was being identified.
Differential Revision: https://reviews.llvm.org/D27031
llvm-svn: 287783
(Recommit after making sure IsVerbose gets properly initialized in
DiagnosticInfoOptimizationBase. See previous commit that takes care of
this.)
OptimizationRemarkAnalysis directly takes the role of the report that is
generated by LAA.
Then we need the magic to be able to turn an LAA remark into an LV
remark. This is done via a new OptimizationRemark ctor.
llvm-svn: 282813
OptimizationRemarkAnalysis directly takes the role of the report that is
generated by LAA.
Then we need the magic to be able to turn an LAA remark into an LV
remark. This is done via a new OptimizationRemark ctor.
llvm-svn: 282758
Ever since LAA was split out into an analysis on its own, this function
stopped emitting the report directly. Instead it stores it to be
retrieved by the client which can then emit it as its own report
(e.g. -Rpass-analysis=loop-vectorize).
llvm-svn: 282561
Fixed a bug in run-time checks for possible memory conflicts inside loop.
The bug is in Low <-> High boundaries calculation. The High boundary should be calculated as "last memory access pointer + element size".
Differential revision: https://reviews.llvm.org/D23176
llvm-svn: 279930
One exception here is LoopInfo which must forward-declare it (because
the typedef is in LoopPassManager.h which depends on LoopInfo).
Also, some includes for LoopPassManager.h were needed since that file
provides the typedef.
Besides a general consistently benefit, the extra layer of indirection
allows the mechanical part of https://reviews.llvm.org/D23256 that
requires touching every transformation and analysis to be factored out
cleanly.
Thanks to David for the suggestion.
llvm-svn: 278079
Besides a general consistently benefit, the extra layer of indirection
allows the mechanical part of https://reviews.llvm.org/D23256 that
requires touching every transformation and analysis to be factored out
cleanly.
Thanks to David for the suggestion.
llvm-svn: 278077
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
The earlier change added hotness attribute to missed-optimization
remarks. This follows up with the analysis remarks (the ones explaining
the reason for the missed optimization).
llvm-svn: 276192
It did not handle correctly cases without GEP.
The following loop wasn't vectorized:
for (int i=0; i<len; i++)
*to++ = *from++;
I use getPtrStride() to find Stride for memory access and return 0 is the Stride is not 1 or -1.
Re-commit rL273257 - revision: http://reviews.llvm.org/D20789
llvm-svn: 273864
It did not handle correctly cases without GEP.
The following loop wasn't vectorized:
for (int i=0; i<len; i++)
*to++ = *from++;
I use getPtrStride() to find Stride for memory access and return 0 is the Stride is not 1 or -1.
Differential revision: http://reviews.llvm.org/D20789
llvm-svn: 273257
James Molloy