instead of getAggregateElement. This has the advantage of being
more consistent and allowing higher-level constant folding to
procede even if an inner extract element cannot be folded.
Make ConstantFoldInstruction call ConstantFoldConstantExpression
on the instruction's operands, making it more consistent with
ConstantFoldConstantExpression itself. This makes sure that
ConstantExprs get TargetData-aware folding before being handed
off as operands for further folding.
This causes more expressions to be folded, but due to a known
shortcoming in constant folding, this currently has the side effect
of stripping a few more nuw and inbounds flags in the non-targetdata
side of constant-fold-gep.ll. This is mostly harmless.
This fixes rdar://11324230.
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intructions are processed. So there's no need to look at them if they're used as
operands of other instructions.
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through the use of 'fpmath' metadata. Currently this only provides a 'fpaccuracy'
value, which may be a number in ULPs or the keyword 'fast', however the intent is
that this will be extended with additional information about NaN's, infinities
etc later. No optimizations have been hooked up to this so far.
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thinking of generalizing it to be able to specify other freedoms beyond accuracy
(such as that NaN's don't have to be respected). I'd like the 3.1 release (the
first one with this metadata) to have the more generic name already rather than
having to auto-upgrade it in 3.2.
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directly instead of a user Instruction. This allows them to test
whether a def dominates a particular operand if the user instruction
is a PHI.
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FoldingSet is implemented as a chained hash table. When there is a hash
collision during insertion, which is common as we fill the table until a
load factor of 2.0 is hit, we walk the chained elements, comparing every
operand with the new element's operands. This can be very expensive if the
MDNode has many operands.
We sacrifice a word of space in MDNode to cache the full hash value, reducing
compares on collision to a minimum. MDNode grows from 28 to 32 bytes + operands
on x86. On x86_64 the new bits fit nicely into existing padding, not growing
the struct at all.
The actual speedup depends a lot on the test case and is typically between
1% and 2% for C++ code with clang -c -O0 -g.
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StringMap. This was redundant and unnecessarily bloated the MDString class.
Because the MDString class is a "Value" and will never have a "name", and
because the Name field in the Value class is a pointer to a StringMap entry, we
repurpose the Name field for an MDString. It stores the StringMap entry in the
Name field, and uses the normal methods to get the string (name) back.
PR12474
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An MDNode has a list of MDNodeOperands allocated directly after it as part of
its allocation. Therefore, the Parent of the MDNodeOperands can be found by
walking back through the operands to the beginning of that list. Mark the first
operand's value pointer as being the 'first' operand so that we know where the
beginning of said list is.
This saves a *lot* of space during LTO with -O0 -g flags.
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the PassManager annoying and should be reimplemented as a decorator
on top of existing passes (as should the timing data).
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correlated pairs of pointer arguments at the callsite. This is designed
to recognize the common C++ idiom of begin/end pointer pairs when the
end pointer is a constant offset from the begin pointer. With the
C-based idiom of a pointer and size, the inline cost saw the constant
size calculation, and this provides the same level of information for
begin/end pairs.
In order to propagate this information we have to search for candidate
operations on a pair of pointer function arguments (or derived from
them) which would be simplified if the pointers had a known constant
offset. Then the callsite analysis looks for such pointer pairs in the
argument list, and applies the appropriate bonus.
This helps LLVM detect that half of bounds-checked STL algorithms
(such as hash_combine_range, and some hybrid sort implementations)
disappear when inlined with a constant size input. However, it's not
a complete fix due the inaccuracy of our cost metric for constants in
general. I'm looking into that next.
Benchmarks showed no significant code size change, and very minor
performance changes. However, specific code such as hashing is showing
significantly cleaner inlining decisions.
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Renamed methods caseBegin, caseEnd and caseDefault with case_begin, case_end, and case_default.
Added some notes relative to case iterators.
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a common collection of methods on Value, and share their implementation.
We had two variations in two different places already, and I need the
third variation for inline cost estimation.
Reviewed by Duncan Sands on IRC, but further comments here welcome.
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http://lists.cs.uiuc.edu/pipermail/llvm-commits/Week-of-Mon-20120130/136146.html
Implemented CaseIterator and it solves almost all described issues: we don't need to mix operand/case/successor indexing anymore. Base iterator class is implemented as a template since it may be initialized either from "const SwitchInst*" or from "SwitchInst*".
ConstCaseIt is just a read-only iterator.
CaseIt is read-write iterator; it allows to change case successor and case value.
Usage of iterator allows totally remove resolveXXXX methods. All indexing convertions done automatically inside the iterator's getters.
Main way of iterator usage looks like this:
SwitchInst *SI = ... // intialize it somehow
for (SwitchInst::CaseIt i = SI->caseBegin(), e = SI->caseEnd(); i != e; ++i) {
BasicBlock *BB = i.getCaseSuccessor();
ConstantInt *V = i.getCaseValue();
// Do something.
}
If you want to convert case number to TerminatorInst successor index, just use getSuccessorIndex iterator's method.
If you want initialize iterator from TerminatorInst successor index, use CaseIt::fromSuccessorIndex(...) method.
There are also related changes in llvm-clients: klee and clang.
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to hash_combine. One of the interfaces could already do this, and the
other can just use a small buffer. This is a much more efficient way to
use the hash_combine interface, although I don't have any particular
benchmark where this code was hot, so I can't measure much of an impact.
It at least doesn't slow anything down.
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"is sized". This prevents every query to isSized() from recursing over
every sub-type of a struct type. This could get *very* slow for
extremely deep nesting of structs, as in 177.mesa.
This change is a 45% speedup for 'opt -O2' of 177.mesa.linked.bc, and
likely a significant speedup for other cases as well. It even impacts
-O0 cases because so many part of the code try to check whether a type
is sized.
Thanks for the review from Nick Lewycky and Benjamin Kramer on IRC.
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new hash_value infrastructure, and replace their implementations using
hash_combine. This removes a complete copy of Jenkin's lookup3 hash
function (which is both significantly slower and lower quality than the
one implemented in hash_combine) along with a somewhat scary xor-only
hash function.
Now that APInt and APFloat can be passed directly to hash_combine,
simplify the rest of the LLVMContextImpl hashing to use the new
infrastructure.
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of the proposed standard hashing interfaces (N3333), and to use
a modified and tuned version of the CityHash algorithm.
Some of the highlights of this change:
-- Significantly higher quality hashing algorithm with very well
distributed results, and extremely few collisions. Should be close to
a checksum for up to 64-bit keys. Very little clustering or clumping of
hash codes, to better distribute load on probed hash tables.
-- Built-in support for reserved values.
-- Simplified API that composes cleanly with other C++ idioms and APIs.
-- Better scaling performance as keys grow. This is the fastest
algorithm I've found and measured for moderately sized keys (such as
show up in some of the uniquing and folding use cases)
-- Support for enabling per-execution seeds to prevent table ordering
or other artifacts of hashing algorithms to impact the output of
LLVM. The seeding would make each run different and highlight these
problems during bootstrap.
This implementation was tested extensively using the SMHasher test
suite, and pased with flying colors, doing better than the original
CityHash algorithm even.
I've included a unittest, although it is somewhat minimal at the moment.
I've also added (or refactored into the proper location) type traits
necessary to implement this, and converted users of GeneralHash over.
My only immediate concerns with this implementation is the performance
of hashing small keys. I've already started working to improve this, and
will continue to do so. Currently, the only algorithms faster produce
lower quality results, but it is likely there is a better compromise
than the current one.
Many thanks to Jeffrey Yasskin who did most of the work on the N3333
paper, pair-programmed some of this code, and reviewed much of it. Many
thanks also go to Geoff Pike Pike and Jyrki Alakuijala, the original
authors of CityHash on which this is heavily based, and Austin Appleby
who created MurmurHash and the SMHasher test suite.
Also thanks to Nadav, Tobias, Howard, Jay, Nick, Ahmed, and Duncan for
all of the review comments! If there are further comments or concerns,
please let me know and I'll jump on 'em.
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verifier does. This correctly handles invoke.
Thanks to Duncan, Andrew and Chris for the comments.
Thanks to Joerg for the early testing.
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