This caused PR23008, compiles failing with: "Use still stuck around after Def is
destroyed: %.sroa.speculated"
Also reverting follow-up r233064.
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It is possible to have code that converts from integer to float, performs operations then converts back, and the result is provably the same as if integers were used.
This can come from different sources, but the most obvious is a helper function that uses floats but the arguments given at an inlined callsites are integers.
This pass considers all integers requiring a bitwidth less than or equal to the bitwidth of the mantissa of a floating point type (23 for floats, 52 for doubles) as exactly representable in floating point.
To reduce the risk of harming efficient code, the pass only attempts to perform complete removal of inttofp/fptoint operations, not just move them around.
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Remove `DebugInfoVerifierLegacyPass` and the `-verify-di` pass.
Instead, call into the `DebugInfoVerifier` from inside
`VerifierLegacyPass::finalizeModule()`. This better matches the logic
in `verifyModule()` (used by the new PassManager), avoids requiring two
separate passes to verify the IR, and makes the API for "add a pass to
verify the IR" simple.
Note: the `-verify-debug-info` flag still works (for now, at least;
eventually it might make sense to just remove it).
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`StripDebug` was only used by tools/opt/opt.cpp in
`AddStandardLinkPasses()`, but opt.cpp adds the same pass based on its
command-line flag before it calls `AddStandardLinkPasses()`. Stripping
debug info twice isn't very useful.
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It's firstly committed at r231630, and reverted at r231635.
Function pass InstructionSimplifier is inserted as barrier to
make sure loop unroll pass won't affect on LICM pass.
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Runtime unrollng will introduce a runtime check in loop prologue.
If the unrolled loop is a inner loop, then the proglogue will be inside
the outer loop. LICM pass can help to promote the runtime check out if
the checked value is loop invariant.
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This pass interchanges loops to provide a more cache-friendly memory access.
For e.g. given a loop like -
for(int i=0;i<N;i++)
for(int j=0;j<N;j++)
A[j][i] = A[j][i]+B[j][i];
is interchanged to -
for(int j=0;j<N;j++)
for(int i=0;i<N;i++)
A[j][i] = A[j][i]+B[j][i];
This pass is currently disabled by default.
To give a brief introduction it consists of 3 stages-
LoopInterchangeLegality : Checks the legality of loop interchange based on Dependency matrix.
LoopInterchangeProfitability: A very basic heuristic has been added to check for profitibility. This will evolve over time.
LoopInterchangeTransform : Which does the actual transform.
LNT Performance tests shows improvement in Polybench/linear-algebra/kernels/mvt and Polybench/linear-algebra/kernels/gemver becnmarks.
TODO:
1) Add support for reductions and lcssa phi.
2) Improve profitability model.
3) Improve loop selection algorithm to select best loop for interchange. Currently the innermost loop is selected for interchange.
4) Improve compile time regression found in llvm lnt due to this pass.
5) Fix issues in Dependency Analysis module.
A special thanks to Hal for reviewing this code.
Review: http://reviews.llvm.org/D7499
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This patch introduces a new mechanism that allows IR modules to co-operatively
build pointer sets corresponding to addresses within a given set of
globals. One particular use case for this is to allow a C++ program to
efficiently verify (at each call site) that a vtable pointer is in the set
of valid vtable pointers for the class or its derived classes. One way of
doing this is for a toolchain component to build, for each class, a bit set
that maps to the memory region allocated for the vtables, such that each 1
bit in the bit set maps to a valid vtable for that class, and lay out the
vtables next to each other, to minimize the total size of the bit sets.
The patch introduces a metadata format for representing pointer sets, an
'@llvm.bitset.test' intrinsic and an LTO lowering pass that lays out the globals
and builds the bitsets, and documents the new feature.
Differential Revision: http://reviews.llvm.org/D7288
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BDCE is a bit-tracking dead code elimination pass. It is based on ADCE (the
"aggressive DCE" pass), with the added capability to track dead bits of integer
valued instructions and remove those instructions when all of the bits are
dead.
Currently, it does not actually do this all-bits-dead removal, but rather
replaces the instruction's uses with a constant zero, and lets instcombine (and
the later run of ADCE) do the rest. Because we essentially get a run of ADCE
"for free" while tracking the dead bits, we also do what ADCE does and removes
actually-dead instructions as well (this includes instructions newly trivially
dead because all bits were dead, but not all such instructions can be removed).
The motivation for this is a case like:
int __attribute__((const)) foo(int i);
int bar(int x) {
x |= (4 & foo(5));
x |= (8 & foo(3));
x |= (16 & foo(2));
x |= (32 & foo(1));
x |= (64 & foo(0));
x |= (128& foo(4));
return x >> 4;
}
As it turns out, if you order the bit-field insertions so that all of the dead
ones come last, then instcombine will remove them. However, if you pick some
other order (such as the one above), the fact that some of the calls to foo()
are useless is not locally obvious, and we don't remove them (without this
pass).
I did a quick compile-time overhead check using sqlite from the test suite
(Release+Asserts). BDCE took ~0.4% of the compilation time (making it about
twice as expensive as ADCE).
I've not looked at why yet, but we eliminate instructions due to having
all-dead bits in:
External/SPEC/CFP2006/447.dealII/447.dealII
External/SPEC/CINT2006/400.perlbench/400.perlbench
External/SPEC/CINT2006/403.gcc/403.gcc
MultiSource/Applications/ClamAV/clamscan
MultiSource/Benchmarks/7zip/7zip-benchmark
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LLVM's include tree and the use of using declarations to hide the
'legacy' namespace for the old pass manager.
This undoes the primary modules-hostile change I made to keep
out-of-tree targets building. I sent an email inquiring about whether
this would be reasonable to do at this phase and people seemed fine with
it, so making it a reality. This should allow us to start bootstrapping
with modules to a certain extent along with making it easier to mix and
match headers in general.
The updates to any code for users of LLVM are very mechanical. Switch
from including "llvm/PassManager.h" to "llvm/IR/LegacyPassManager.h".
Qualify the types which now produce compile errors with "legacy::". The
most common ones are "PassManager", "PassManagerBase", and
"FunctionPassManager".
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analyses back into the LTO code generator.
The pass manager builder (and the transforms library in general)
shouldn't be referencing the target machine at all.
This makes the LTO population work like the others -- the data layout
and target transform info need to be pre-populated.
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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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We used to always vectorize (slp and loop vectorize) in the LTO pass pipeline.
r220345 changed it so that we used the PassManager's fields 'LoopVectorize' and
'SLPVectorize' out of the desire to be able to disable vectorization using the
cl::opt flags 'vectorize-loops'/'slp-vectorize' which the before mentioned
fields default to.
Unfortunately, this turns off vectorization because those fields
default to false.
This commit adds flags to the LTO library to disable lto vectorization which
reconciles the desire to optionally disable vectorization during LTO and
the desired behavior of defaulting to enabled vectorization.
We really want tools to set PassManager flags directly to enable/disable
vectorization and not go the route via cl::opt flags *in*
PassManagerBuilder.cpp.
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Summary: Patches 202051 and 208013 added calls to LTO's PassManager which unconditionally add LoopVectorizePass and SLPVectorizerPass instead of following the logic in PassManagerBuilder::populateModulePassManager and honoring the -vectorize-loops -run-slp-after-loop-vectorization flags.
Reviewers: nadav, aschwaighofer, yijiang
Subscribers: llvm-commits
Differential Revision: http://reviews.llvm.org/D5884
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the IR going into it and to clean up the IR produced by the vectorizers.
Note that these are *off by default* right now while folks collect data
on whether the performance tradeoff is reasonable.
In a build of the 'opt' binary, I see about 2% compile time regression
due to this change on average. This is in my mind essentially the worst
expected case: very little of the opt binary is going to *benefit* from
these extra passes.
I've seen several benchmarks improve in performance my small amounts due
to running these passes, and there are certain (rare) cases where these
passes make a huge difference by either enabling the vectorizer at all
or by hoisting runtime checks out of the outer loop. My primary
motivation is to prevent people from seeing runtime check overhead in
benchmarks where the existing passes and optimizers would be able to
eliminate that.
I've chosen the sequence of passes based on the kinds of things that
seem likely to be relevant for the code at each stage: rotaing loops for
the vectorizer, finding correlated values, loop invariants, and
unswitching opportunities from any runtime checks, and cleaning up
commonalities exposed by the SLP vectorizer.
I'll be pinging existing threads where some of these issues have come up
and will start new threads to get folks to benchmark and collect data on
whether this is the right tradeoff or we should do something else.
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With this a DataLayoutPass can be reused for multiple modules.
Once we have doInitialization/doFinalization, it doesn't seem necessary to pass
a Module to the constructor.
Overall this change seems in line with the idea of making DataLayout a required
part of Module. With it the only way of having a DataLayout used is to add it
to the Module.
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This adds a ScalarEvolution-powered transformation that updates load, store and
memory intrinsic pointer alignments based on invariant((a+q) & b == 0)
expressions. Many of the simple cases we can get with ValueTracking, but we
still need something like this for the more complicated cases (such as those
with an offset) that require some algebra. Note that gcc's
__builtin_assume_aligned's optional third argument provides exactly for this
kind of 'misalignment' offset for which this kind of logic is necessary.
The primary motivation is to fixup alignments for vector loads/stores after
vectorization (and unrolling). This pass is added to the optimization pipeline
just after the SLP vectorizer runs (which, admittedly, does not preserve SE,
although I imagine it could). Regardless, I actually don't think that the
preservation matters too much in this case: SE computes lazily, and this pass
won't issue any SE queries unless there are any assume intrinsics, so there
should be no real additional cost in the common case (SLP does preserve DT and
LoopInfo).
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Add -use-cfl-aa (and -use-cfl-aa-in-codegen) to add CFL AA in the default pass
managers (for easy testing).
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This swaps the order of the loop vectorizer and the SLP/BB vectorizers. It is disabled by default so we can do performance testing - ideally we want to change to having the loop vectorizer running first, and the SLP vectorizer using its leftovers instead of the other way around.
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This is mostly a cleanup, but it changes a fairly old behavior.
Every "real" LTO user was already disabling the silly internalize pass
and creating the internalize pass itself. The difference with this
patch is for "opt -std-link-opts" and the C api.
Now to get a usable behavior out of opt one doesn't need the funny
looking command line:
opt -internalize -disable-internalize -internalize-public-api-list=foo,bar -std-link-opts
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This commit adds scoped noalias metadata. The primary motivations for this
feature are:
1. To preserve noalias function attribute information when inlining
2. To provide the ability to model block-scope C99 restrict pointers
Neither of these two abilities are added here, only the necessary
infrastructure. In fact, there should be no change to existing functionality,
only the addition of new features. The logic that converts noalias function
parameters into this metadata during inlining will come in a follow-up commit.
What is added here is the ability to generally specify noalias memory-access
sets. Regarding the metadata, alias-analysis scopes are defined similar to TBAA
nodes:
!scope0 = metadata !{ metadata !"scope of foo()" }
!scope1 = metadata !{ metadata !"scope 1", metadata !scope0 }
!scope2 = metadata !{ metadata !"scope 2", metadata !scope0 }
!scope3 = metadata !{ metadata !"scope 2.1", metadata !scope2 }
!scope4 = metadata !{ metadata !"scope 2.2", metadata !scope2 }
Loads and stores can be tagged with an alias-analysis scope, and also, with a
noalias tag for a specific scope:
... = load %ptr1, !alias.scope !{ !scope1 }
... = load %ptr2, !alias.scope !{ !scope1, !scope2 }, !noalias !{ !scope1 }
When evaluating an aliasing query, if one of the instructions is associated
with an alias.scope id that is identical to the noalias scope associated with
the other instruction, or is a descendant (in the scope hierarchy) of the
noalias scope associated with the other instruction, then the two memory
accesses are assumed not to alias.
Note that is the first element of the scope metadata is a string, then it can
be combined accross functions and translation units. The string can be replaced
by a self-reference to create globally unqiue scope identifiers.
[Note: This overview is slightly stylized, since the metadata nodes really need
to just be numbers (!0 instead of !scope0), and the scope lists are also global
unnamed metadata.]
Existing noalias metadata in a callee is "cloned" for use by the inlined code.
This is necessary because the aliasing scopes are unique to each call site
(because of possible control dependencies on the aliasing properties). For
example, consider a function: foo(noalias a, noalias b) { *a = *b; } that gets
inlined into bar() { ... if (...) foo(a1, b1); ... if (...) foo(a2, b2); } --
now just because we know that a1 does not alias with b1 at the first call site,
and a2 does not alias with b2 at the second call site, we cannot let inlining
these functons have the metadata imply that a1 does not alias with b2.
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Merges equivalent loads on both sides of a hammock/diamond
and hoists into into the header.
Merges equivalent stores on both sides of a hammock/diamond
and sinks it to the footer.
Can enable if conversion and tolerate better load misses
and store operand latencies.
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Exposes more constant globals that can be removed by
the global optimizer. A specific example is the removal
of the static global block address array in
clang/test/CodeGen/indirect-goto.c. This change impacts only
lower optimization levels. With LTO interprocedural
const prop runs already before global opt.
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This extension point allows adding passes that perform peephole optimizations
similar to the instruction combiner. These passes will be inserted after
each instance of the instruction combiner pass.
Differential Revision: http://reviews.llvm.org/D3905
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Similar to r202051, add missing loop simplification passes to the LTO
optimization pipeline.
Patch by Rafael Espindola.
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The generic (concatenation) loop unroller is currently placed early in the
standard optimization pipeline. This is a good place to perform full unrolling,
but not the right place to perform partial/runtime unrolling. However, most
targets don't enable partial/runtime unrolling, so this never mattered.
However, even some x86 cores benefit from partial/runtime unrolling of very
small loops, and follow-up commits will enable this. First, we need to move
partial/runtime unrolling late in the optimization pipeline (importantly, this
is after SLP and loop vectorization, as vectorization can drastically change
the size of a loop), while keeping the full unrolling where it is now. This
change does just that.
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