If the landingpad of the invoke is using a personality function that
catches asynch exceptions, then it can catch a trap.
Also add some landingpads to invalid LLVM IR test cases that lack them.
Over-the-shoulder reviewed by David Majnemer.
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When creating a scev for sext({X,+,Y}), scev checks if the expression
is equivalent to {sext X,+,zext Y}. If it can prove that, it also
tags the original {X,+,Y} as <nsw>, which is not correct.
In the test case I run `-scalar-evolution` twice because the bug
manifests only once SCEV has run through and seen the `sext`
expressions (and then does a in-place mutation on {X,+,Y}).
Differential Revision: http://reviews.llvm.org/D7495
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For the attached test case different types are used in the ICmpInst
and SelectInst that represent the min/max expressions. However, if the
ICmpInst type is smaller a comparison with the sign/zero extended
operands would have yielded the same result. This situation might
arise after the instruction combination pass was applied.
Differential Revision: http://reviews.llvm.org/D7338
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add recurrences don't overflow.
This change makes the optimization more restrictive. It still assumes
that an overflowing `add nsw` is undefined behavior; and this change
will need revisiting once we have a consistent semantics for poison
values.
Differential Revision: http://reviews.llvm.org/D7331
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Summary:
The alias.scope metadata represents sets of things an instruction might
alias with. When generically combining the metadata from two
instructions the result must be the union of the original sets, because
the new instruction might alias with anything any of the original
instructions aliased with.
Reviewers: hfinkel
Subscribers: llvm-commits
Differential Revision: http://reviews.llvm.org/D7490
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Turns out there is a simpler way of checking that all bytes in a word are equal
than binary decomposition.
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different fields.
We can show that two GEPs off of the same (possibly multidimensional)
array of structs, into different fields, can't alias. Quoting:
For two GEPOperators GEP1 and GEP2, if we find that:
- both GEPs begin indexing from the exact same pointer;
- the last indices in both GEPs are constants, indexing into a struct;
- said indices are different, hence,the pointed-to fields are different;
- and both GEPs only index through arrays prior to that;
this lets us determine that the struct that GEP1 indexes into and the
struct that GEP2 indexes into must either precisely overlap or be
completely disjoint. Because they cannot partially overlap, indexing
into different non-overlapping fields of the struct will never alias.
The other BasicAA::aliasGEP rules worked in some cases, but not all
(for example, the i32x3 struct in the testcase).
We can add this simple ad-hoc rule to complement them.
rdar://19717375
Differential Revision: http://reviews.llvm.org/D7453
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Composing DenseMaps and SmallVectors is still somewhat suboptimal,
but this at least halves the size of the vector elements. NFC.
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It is a variation of SimplifyBinOp, but it takes into account
FastMathFlags.
It is needed in inliner and loop-unroller to accurately predict the
transformation's outcome (previously we dropped the flags and were too
conservative in some cases).
Example:
float foo(float *a, float b) {
float r;
if (a[1] * b)
r = /* a lot of expensive computations */;
else
r = 1;
return r;
}
float boo(float *a) {
return foo(a, 0.0);
}
Without this patch, we don't inline 'foo' into 'boo'.
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This will allow it to be shared with the new Loop Distribution pass.
getFirstInst is currently duplicated across LoopVectorize.cpp and
LoopAccessAnalysis.cpp. This is a short-term work-around until we figure out
a better solution.
NFC. (The code moved is adjusted a bit for the name of the Loop member and
that PtrRtCheck is now a reference rather than a pointer.)
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Since testing the function indirectly is tricky, introduce a direct
print-memderefs pass, in the same spirit as print-memdeps, which prints
dereferenceability information matched by FileCheck.
Differential Revision: http://reviews.llvm.org/D7075
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Summary: When evaluating floating point instructions in the inliner, ask the TTI whether it is an expensive operation. By default, it's not an expensive operation. This keeps the default behavior the same as before. The ARM TTI has been updated to return back TCC_Expensive for targets which don't have hardware floating point.
Reviewers: chandlerc, echristo
Reviewed By: echristo
Subscribers: t.p.northover, aemerson, llvm-commits
Differential Revision: http://reviews.llvm.org/D6936
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Other than moving code and adding the boilerplate for the new files, the code
being moved is unchanged.
There are a few global functions that are shared with the rest of the
LoopVectorizer. I moved these to the new module as well (emitLoopAnalysis,
stripIntegerCast, replaceSymbolicStrideSCEV) along with the Report class used
by emitLoopAnalysis. There is probably room for further improvement in this
area.
I kept DEBUG_TYPE "loop-vectorize" because it's used as the PassName with
emitOptimizationRemarkAnalysis. This will obviously have to change.
NFC. This is part of the patchset that splits out the memory dependence logic
from LoopVectorizationLegality into a new class LoopAccessAnalysis.
LoopAccessAnalysis will be used by the new Loop Distribution pass.
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terms of the new pass manager's TargetIRAnalysis.
Yep, this is one of the nicer bits of the new pass manager's design.
Passes can in many cases operate in a vacuum and so we can just nest
things when convenient. This is particularly convenient here as I can
now consolidate all of the TargetMachine logic on this analysis.
The most important change here is that this pushes the function we need
TTI for all the way into the TargetMachine, and re-creates the TTI
object for each function rather than re-using it for each function.
We're now prepared to teach the targets to produce function-specific TTI
objects with specific subtargets cached, etc.
One piece of feedback I'd love here is whether its worth renaming any of
this stuff. None of the names really seem that awesome to me at this
point, but TargetTransformInfoWrapperPass is particularly ... odd.
TargetIRAnalysisWrapper might make more sense. I would want to do that
rename separately anyways, but let me know what you think.
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getTTI method used to get an actual TTI object.
No functionality changed. This just threads the argument and ensures
code like the inliner can correctly look up the callee's TTI rather than
using a fixed one.
The next change will use this to implement per-function subtarget usage
by TTI. The changes after that should eliminate the need for FTTI as that
will have become the default.
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produce it.
This adds a function to the TargetMachine that produces this analysis
via a callback for each function. This in turn faves the way to produce
a *different* TTI per-function with the correct subtarget cached.
I've also done the necessary wiring in the opt tool to thread the target
machine down and make it available to the pass registry so that we can
construct this analysis from a target machine when available.
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base which it adds a single analysis pass to, to instead return the type
erased TargetTransformInfo object constructed for that TargetMachine.
This removes all of the pass variants for TTI. There is now a single TTI
*pass* in the Analysis layer. All of the Analysis <-> Target
communication is through the TTI's type erased interface itself. While
the diff is large here, it is nothing more that code motion to make
types available in a header file for use in a different source file
within each target.
I've tried to keep all the doxygen comments and file boilerplate in line
with this move, but let me know if I missed anything.
With this in place, the next step to making TTI work with the new pass
manager is to introduce a really simple new-style analysis that produces
a TTI object via a callback into this routine on the target machine.
Once we have that, we'll have the building blocks necessary to accept
a function argument as well.
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type erased interface and a single analysis pass rather than an
extremely complex analysis group.
The end result is that the TTI analysis can contain a type erased
implementation that supports the polymorphic TTI interface. We can build
one from a target-specific implementation or from a dummy one in the IR.
I've also factored all of the code into "mix-in"-able base classes,
including CRTP base classes to facilitate calling back up to the most
specialized form when delegating horizontally across the surface. These
aren't as clean as I would like and I'm planning to work on cleaning
some of this up, but I wanted to start by putting into the right form.
There are a number of reasons for this change, and this particular
design. The first and foremost reason is that an analysis group is
complete overkill, and the chaining delegation strategy was so opaque,
confusing, and high overhead that TTI was suffering greatly for it.
Several of the TTI functions had failed to be implemented in all places
because of the chaining-based delegation making there be no checking of
this. A few other functions were implemented with incorrect delegation.
The message to me was very clear working on this -- the delegation and
analysis group structure was too confusing to be useful here.
The other reason of course is that this is *much* more natural fit for
the new pass manager. This will lay the ground work for a type-erased
per-function info object that can look up the correct subtarget and even
cache it.
Yet another benefit is that this will significantly simplify the
interaction of the pass managers and the TargetMachine. See the future
work below.
The downside of this change is that it is very, very verbose. I'm going
to work to improve that, but it is somewhat an implementation necessity
in C++ to do type erasure. =/ I discussed this design really extensively
with Eric and Hal prior to going down this path, and afterward showed
them the result. No one was really thrilled with it, but there doesn't
seem to be a substantially better alternative. Using a base class and
virtual method dispatch would make the code much shorter, but as
discussed in the update to the programmer's manual and elsewhere,
a polymorphic interface feels like the more principled approach even if
this is perhaps the least compelling example of it. ;]
Ultimately, there is still a lot more to be done here, but this was the
huge chunk that I couldn't really split things out of because this was
the interface change to TTI. I've tried to minimize all the other parts
of this. The follow up work should include at least:
1) Improving the TargetMachine interface by having it directly return
a TTI object. Because we have a non-pass object with value semantics
and an internal type erasure mechanism, we can narrow the interface
of the TargetMachine to *just* do what we need: build and return
a TTI object that we can then insert into the pass pipeline.
2) Make the TTI object be fully specialized for a particular function.
This will include splitting off a minimal form of it which is
sufficient for the inliner and the old pass manager.
3) Add a new pass manager analysis which produces TTI objects from the
target machine for each function. This may actually be done as part
of #2 in order to use the new analysis to implement #2.
4) Work on narrowing the API between TTI and the targets so that it is
easier to understand and less verbose to type erase.
5) Work on narrowing the API between TTI and its clients so that it is
easier to understand and less verbose to forward.
6) Try to improve the CRTP-based delegation. I feel like this code is
just a bit messy and exacerbating the complexity of implementing
the TTI in each target.
Many thanks to Eric and Hal for their help here. I ended up blocked on
this somewhat more abruptly than I expected, and so I appreciate getting
it sorted out very quickly.
Differential Revision: http://reviews.llvm.org/D7293
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This patch folds fcmp in some cases of interest in Julia. The patch adds a function CannotBeOrderedLessThanZero that returns true if a value is provably not less than zero. I.e. the function returns true if the value is provably -0, +0, positive, or a NaN. The patch extends InstructionSimplify.cpp to fold instances of fcmp where:
- the predicate is olt or uge
- the first operand is provably not less than zero
- the second operand is zero
The motivation for handling these cases optimizing away domain checks for sqrt in Julia for common idioms such as sqrt(x*x+y*y)..
http://reviews.llvm.org/D6972
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According to my reading of the LangRef, volatiles are only ordered with respect to other volatiles. It is entirely legal and profitable to forward unrelated loads over the volatile load. This patch implements this for GVN by refining the transition rules MemoryDependenceAnalysis uses when encountering a volatile.
The added test cases show where the extra flexibility is profitable for local dependence optimizations. I have a related change (227110) which will extend this to non-local dependence (i.e. PRE), but that's essentially orthogonal to the semantic change in this patch. I have tested the two together and can confirm that PRE works over a volatile load with both changes. I will be submitting a PRE w/volatiles test case seperately in the near future.
Differential Revision: http://reviews.llvm.org/D6901
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This change is mostly motivated by exposing information about the original query instruction to the actual scanning work in getPointerDependencyFrom when used by GVN PRE. In a follow up change, I will use this to be more precise with regards to the semantics of volatile instructions encountered in the scan of a basic block.
Worth noting, is that this change (despite appearing quite simple) is not semantically preserving. By providing more information to the helper routine, we allow some optimizations to kick in that weren't previously able to (when called from this code path.) In particular, we see that treatment of !invariant.load becomes more precise. In theory, we might see a difference with an ordered/atomic instruction as well, but I'm having a hard time actually finding a test case which shows that.
Test wise, I've included new tests for !invariant.load which illustrate this difference. I've also included some updated TBAA tests which highlight that this change isn't needed for that optimization to kick in - it's handled inside alias analysis itself.
Eventually, it would be nice to factor the !invariant.load handling inside alias analysis as well.
Differential Revision: http://reviews.llvm.org/D6895
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manager to support the actual uses of it. =]
When I ported instcombine to the new pass manager I discover that it
didn't work because TLI wasn't available in the right places. This is
a somewhat surprising and/or subtle aspect of the new pass manager
design that came up before but I think is useful to be reminded of:
While the new pass manager *allows* a function pass to query a module
analysis, it requires that the module analysis is already run and cached
prior to the function pass manager starting up, possibly with
a 'require<foo>' style utility in the pass pipeline. This is an
intentional hurdle because using a module analysis from a function pass
*requires* that the module analysis is run prior to entering the
function pass manager. Otherwise the other functions in the module could
be in who-knows-what state, etc.
A somewhat surprising consequence of this design decision (at least to
me) is that you have to design a function pass that leverages
a module analysis to do so as an optional feature. Even if that means
your function pass does no work in the absence of the module analysis,
you have to handle that possibility and remain conservatively correct.
This is a natural consequence of things being able to invalidate the
module analysis and us being unable to re-run it. And it's a generally
good thing because it lets us reorder passes arbitrarily without
breaking correctness, etc.
This ends up causing problems in one case. What if we have a module
analysis that is *definitionally* impossible to invalidate. In the
places this might come up, the analysis is usually also definitionally
trivial to run even while other transformation passes run on the module,
regardless of the state of anything. And so, it follows that it is
natural to have a hard requirement on such analyses from a function
pass.
It turns out, that TargetLibraryInfo is just such an analysis, and
InstCombine has a hard requirement on it.
The approach I've taken here is to produce an analysis that models this
flexibility by making it both a module and a function analysis. This
exposes the fact that it is in fact safe to compute at any point. We can
even make it a valid CGSCC analysis at some point if that is useful.
However, we don't want to have a copy of the actual target library info
state for each function! This state is specific to the triple. The
somewhat direct and blunt approach here is to turn TLI into a pimpl,
with the state and mutators in the implementation class and the query
routines primarily in the wrapper. Then the analysis can lazily
construct and cache the implementations, keyed on the triple, and
on-demand produce wrappers of them for each function.
One minor annoyance is that we will end up with a wrapper for each
function in the module. While this is a bit wasteful (one pointer per
function) it seems tolerable. And it has the advantage of ensuring that
we pay the absolute minimum synchronization cost to access this
information should we end up with a nice parallel function pass manager
in the future. We could look into trying to mark when analysis results
are especially cheap to recompute and more eagerly GC-ing the cached
results, or we could look at supporting a variant of analyses whose
results are specifically *not* cached and expected to just be used and
discarded by the consumer. Either way, these seem like incremental
enhancements that should happen when we start profiling the memory and
CPU usage of the new pass manager and not before.
The other minor annoyance is that if we end up using the TLI in both
a module pass and a function pass, those will be produced by two
separate analyses, and thus will point to separate copies of the
implementation state. While a minor issue, I dislike this and would like
to find a way to cleanly allow a single analysis instance to be used
across multiple IR unit managers. But I don't have a good solution to
this today, and I don't want to hold up all of the work waiting to come
up with one. This too seems like a reasonable thing to incrementally
improve later.
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I had already factored this analysis specifically to enable doing this,
but hadn't actually committed the necessary wiring to get at this from
the new pass manager. This also nicely shows how the separate cache
object can be directly managed by the new pass manager.
This analysis didn't have any direct tests and so I've added a printer
pass and a boring test case. I chose to print the i1 value which is
being assumed rather than the call to llvm.assume as that seems much
more useful for testing... but suggestions on an even better printing
strategy welcome. My main goal was to make sure things actually work. =]
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Specifically, gc.result benefits from this greatly. Instead of:
gc.result.int.*
gc.result.float.*
gc.result.ptr.*
...
We now have a gc.result.* that can specialize to literally any type.
Differential Revision: http://reviews.llvm.org/D7020
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ScalarEvolution currently lowers a subtraction recurrence to an add
recurrence with the same no-wrap flags as the subtraction. This is
incorrect because `sub nsw X, Y` is not the same as `add nsw X, -Y`
and `sub nuw X, Y` is not the same as `add nuw X, -Y`. This patch
fixes the issue, and adds two test cases demonstrating the bug.
Differential Revision: http://reviews.llvm.org/D7081
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pass and a LoopPrinterPass with the expected associated wiring.
I've added a RUN line to the only test case (!!!) we have that actually
prints loops. Everything seems to be working.
This is somewhat exciting as this is the first analysis using another
analysis to go in for the new pass manager. =D I also believe it is the
last analysis necessary for porting instcombine, but of course I may yet
discover more.
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cleaner to derive from the generic base.
Thise removes a ton of boiler plate code and somewhat strange and
pointless indirections. It also remove a bunch of the previously needed
friend declarations. To fully remove these, I also lifted the verify
logic into the generic LoopInfoBase, which seems good anyways -- it is
generic and useful logic even for the machine side.
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unused variables in a no-asserts build.
I've fixed this by putting the entire loop behind an #ifndef as it
contains nothing other than asserts.
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a LoopInfoWrapperPass to wire the object up to the legacy pass manager.
This switches all the clients of LoopInfo over and paves the way to port
LoopInfo to the new pass manager. No functionality change is intended
with this iteration.
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TargetLibraryAnalysis pass.
There are actually no direct tests of this already in the tree. I've
added the most basic test that the pass manager bits themselves work,
and the TLI object produced will be tested by an upcoming patches as
they port passes which rely on TLI.
This is starting to point out the awkwardness of the invalidate API --
it seems poorly fitting on the *result* object. I suspect I will change
it to live on the analysis instead, but that's not for this change, and
I'd rather have a few more passes ported in order to have more
experience with how this plays out.
I believe there is only one more analysis required in order to start
porting instcombine. =]
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The pass is really just a means of accessing a cached instance of the
TargetLibraryInfo object, and this way we can re-use that object for the
new pass manager as its result.
Lots of delta, but nothing interesting happening here. This is the
common pattern that is developing to allow analyses to live in both the
old and new pass manager -- a wrapper pass in the old pass manager
emulates the separation intrinsic to the new pass manager between the
result and pass for analyses.
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While the term "Target" is in the name, it doesn't really have to do
with the LLVM Target library -- this isn't an abstraction which LLVM
targets generally need to implement or extend. It has much more to do
with modeling the various runtime libraries on different OSes and with
different runtime environments. The "target" in this sense is the more
general sense of a target of cross compilation.
This is in preparation for porting this analysis to the new pass
manager.
No functionality changed, and updates inbound for Clang and Polly.
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it's defined in the current module. Clang generates this situation for the
C++14 sized deallocation functions, because it generates a weak definition in
case one isn't provided by the C++ runtime library.
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utils/sort_includes.py.
I clearly haven't done this in a while, so more changed than usual. This
even uncovered a missing include from the InstrProf library that I've
added. No functionality changed here, just mechanical cleanup of the
include order.
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a print method.
This was formulated on a bad idea, but sadly I didn't uncover how bad
this was until I got further down the path. I had hoped that we could
provide a low boilerplate way of printing analyses, but it just doesn't
seem like this really fits the needs of the analyses. Not all analyses
really want to do printing, and those that do don't all use the same
interface. Instead, with the new pass manager let's just take advantage
of the fact that creating an explicit printer pass like the LCG has is
pretty low boilerplate already and rely on that for testing.
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