implementation of the SROA algorithm. We were using the term 'partition'
in many places that no longer ever represented an actual partition, but
rather just an arbitrary slice of an alloca.
No functionality change intended here. Mostly just renaming of types,
functions, variables, and rewording of comments. Several comments were
rewritten to make a lot more sense in the new structure of things.
The stats are still weird and not reflective of how this really works.
I'll fix those up in a separate patch as it is a touch more semantic of
a change...
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SROA.
The crux of the issue is that now we track uses of a partition of the
alloca in two places: the iterators over the partitioning uses and the
previously collected split uses vector. We weren't accounting for the
fact that the split uses might invalidate integer widening in ways other
than due to their width (in this case due to being volatile).
Further reduced testcase added to the tests.
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end of a vector. This was found with ASan. I've had one other report of
a crasher, but thus far been unable to reproduce the crash. It may well
be fixed with this version, and if not I'd like to get more information
from the build bots about what is happening.
See r186316 for the full commit log for the new implementation of the
SROA algorithm.
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a bot.
This reverts the commit which introduced a new implementation of the
fancy SROA pass designed to reduce its overhead. I'll skip the huge
commit log here, refer to r186316 if you're looking for how this all
works and why it works that way.
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different core implementation strategy.
Previously, SROA would build a relatively elaborate partitioning of an
alloca, associate uses with each partition, and then rewrite the uses of
each partition in an attempt to break apart the alloca into chunks that
could be promoted. This was very wasteful in terms of memory and compile
time because regardless of how complex the alloca or how much we're able
to do in breaking it up, all of the datastructure work to analyze the
partitioning was done up front.
The new implementation attempts to form partitions of the alloca lazily
and on the fly, rewriting the uses that make up that partition as it
goes. This has a few significant effects:
1) Much simpler data structures are used throughout.
2) No more double walk of the recursive use graph of the alloca, only
walk it once.
3) No more complex algorithms for associating a particular use with
a particular partition.
4) PHI and Select speculation is simplified and happens lazily.
5) More precise information is available about a specific use of the
alloca, removing the need for some side datastructures.
Ultimately, I think this is a much better implementation. It removes
about 300 lines of code, but arguably removes more like 500 considering
that some code grew in the process of being factored apart and cleaned
up for this all to work.
I've re-used as much of the old implementation as possible, which
includes the lion's share of code in the form of the rewriting logic.
The interesting new logic centers around how the uses of a partition are
sorted, and split into actual partitions.
Each instruction using a pointer derived from the alloca gets
a 'Partition' entry. This name is totally wrong, but I'll do a rename in
a follow-up commit as there is already enough churn here. The entry
describes the offset range accessed and the nature of the access. Once
we have all of these entries we sort them in a very specific way:
increasing order of begin offset, followed by whether they are
splittable uses (memcpy, etc), followed by the end offset or whatever.
Sorting by splittability is important as it simplifies the collection of
uses into a partition.
Once we have these uses sorted, we walk from the beginning to the end
building up a range of uses that form a partition of the alloca.
Overlapping unsplittable uses are merged into a single partition while
splittable uses are broken apart and carried from one partition to the
next. A partition is also introduced to bridge splittable uses between
the unsplittable regions when necessary.
I've looked at the performance PRs fairly closely. PR15471 no longer
will even load (the module is invalid). Not sure what is up there.
PR15412 improves by between 5% and 10%, however it is nearly impossible
to know what is holding it up as SROA (the entire pass) takes less time
than reading the IR for that test case. The analysis takes the same time
as running mem2reg on the final allocas. I suspect (without much
evidence) that the new implementation will scale much better however,
and it is just the small nature of the test cases that makes the changes
small and noisy. Either way, it is still simpler and cleaner I think.
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against a constant."
This reverts commit r186107. It didn't handle wrapping arithmetic in the
loop correctly and thus caused the following C program to count from
0 to UINT64_MAX instead of from 0 to 255 as intended:
#include <stdio.h>
int main() {
unsigned char first = 0, last = 255;
do { printf("%d\n", first); } while (first++ != last);
}
Full test case and instructions to reproduce with just the -indvars pass
sent to the original review thread rather than to r186107's commit.
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Patch by Michele Scandale!
Adds a special handling of the case where, during the loop exit
condition rewriting, the exit value is a constant of bitwidth lower
than the type of the induction variable: instead of introducing a
trunc operation in order to match correctly the operand types, it
allows to convert the constant value to an equivalent constant,
depending on the initial value of the induction variable and the trip
count, in order have an equivalent comparison between the induction
variable and the new constant.
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Without the changes introduced into this patch, if TRE saw any allocas at all,
TRE would not perform TRE *or* mark callsites with the tail marker.
Because TRE runs after mem2reg, this inadequacy is not a death sentence. But
given a callsite A without escaping alloca argument, A may not be able to have
the tail marker placed on it due to a separate callsite B having a write-back
parameter passed in via an argument with the nocapture attribute.
Assume that B is the only other callsite besides A and B only has nocapture
escaping alloca arguments (*NOTE* B may have other arguments that are not passed
allocas). In this case not marking A with the tail marker is unnecessarily
conservative since:
1. By assumption A has no escaping alloca arguments itself so it can not
access the caller's stack via its arguments.
2. Since all of B's escaping alloca arguments are passed as parameters with
the nocapture attribute, we know that B does not stash said escaping
allocas in a manner that outlives B itself and thus could be accessed
indirectly by A.
With the changes introduced by this patch:
1. If we see any escaping allocas passed as a capturing argument, we do
nothing and bail early.
2. If we do not see any escaping allocas passed as captured arguments but we
do see escaping allocas passed as nocapture arguments:
i. We do not perform TRE to avoid PR962 since the code generator produces
significantly worse code for the dynamic allocas that would be created
by the TRE algorithm.
ii. If we do not return twice, mark call sites without escaping allocas
with the tail marker. *NOTE* This excludes functions with escaping
nocapture allocas.
3. If we do not see any escaping allocas at all (whether captured or not):
i. If we do not have usage of setjmp, mark all callsites with the tail
marker.
ii. If there are no dynamic/variable sized allocas in the function,
attempt to perform TRE on all callsites in the function.
Based off of a patch by Nick Lewycky.
rdar://14324281.
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debug statements to add a missing newline. Also canonicalize to '\n' instead of
"\n"; the latter calls a function with a loop the former does not.
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When a 1-element vector alloca is promoted, a store instruction can often be
rewritten without converting the value to a scalar and using an insertelement
instruction to stuff it into the new alloca. This patch just adds a check
to skip that conversion when it is unnecessary. This turns out to be really
important for some ARM Neon operations where <1 x i64> is used to get around
the fact that i64 is not a legal type.
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This commit completely removes what is left of the simplify-libcalls
pass. All of the functionality has now been migrated to the instcombine
and functionattrs passes. The following C API functions are now NOPs:
1. LLVMAddSimplifyLibCallsPass
2. LLVMPassManagerBuilderSetDisableSimplifyLibCalls
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Prior to this change, the considered addressing modes may be invalid since the
maximum and minimum offsets were not taking into account.
This was causing an assertion failure.
The added test case exercices that behavior.
<rdar://problem/14199725> Assertion failed: (CurScaleCost >= 0 && "Legal
addressing mode has an illegal cost!")
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r183584 tries to derive some info from the code *AFTER* a call and apply
these derived info to the code *BEFORE* the call, which is not always safe
as the call in question may never return, and in this case, the derived
info is invalid.
Thank Duncan for pointing out this potential bug.
rdar://14073661
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The MemCpyOpt pass is capable of optimizing:
callee(&S); copy N bytes from S to D.
into:
callee(&D);
subject to some legality constraints.
Assertion is triggered when the compiler tries to evalute "sizeof(typeof(D))",
while D is an opaque-typed, 'sret' formal argument of function being compiled.
i.e. the signature of the func being compiled is something like this:
T caller(...,%opaque* noalias nocapture sret %D, ...)
The fix is that when come across such situation, instead of calling some
utility functions to get the size of D's type (which will crash), we simply
assume D has at least N bytes as implified by the copy-instruction.
rdar://14073661
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IndVarSimplify is willing to move divide instructions outside of their
loop bodies if they are invariant of the loop. However, it may not be
safe to expand them if we do not know if they can trap.
Instead, check to see if it is not safe to expand the instruction and
skip the expansion.
This fixes PR16041.
Testcase by Rafael Ávila de Espíndola.
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Account for the cost of scaling factor in Loop Strength Reduce when rating the
formulae. This uses a target hook.
The default implementation of the hook is: if the addressing mode is legal, the
scaling factor is free.
<rdar://problem/13806271>
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Namely, check if the target allows to fold more that one register in the
addressing mode and if yes, adjust the cost accordingly.
Prior to this commit, reg1 + scale * reg2 accesses were artificially preferred
to reg1 + reg2 accesses. Indeed, the cost model wrongly assumed that reg1 + reg2
needs a temporary register for the computation, whereas it was correctly
estimated for reg1 + scale * reg2.
<rdar://problem/13973908>
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iteration.
This on step toward non-iterative GVN. My local hack suggests that getting rid
of iteration will speedup GVN by 30%+ on a medium sized input (2k LOC, C++).
I cannot explain why not 2x or more at this moment.
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Test case by Michele Scandale!
Fixes PR10293: Load not hoisted out of loop with multiple exits.
There are few regressions with this patch, now tracked by
rdar:13817079, and a roughly equal number of improvements. The
regressions are almost certainly back luck because LoopRotate has very
little idea of whether rotation is profitable. Doing better requires a
more comprehensive solution.
This checkin is a quick fix that lacks generality (PR10293 has
a counter-example). But it trivially fixes the case in PR10293 without
interfering with other cases, and it does satify the criteria that
LoopRotate is a loop canonicalization pass that should avoid
heuristics and special cases.
I can think of two approaches that would probably be better in
the long run. Ultimately they may both make sense.
(1) LoopRotate should check that the current header would make a good
loop guard, and that the loop does not already has a sufficient
guard. The artifical SimplifiedLoopLatch check would be unnecessary,
and the design would be more general and canonical. Two difficulties:
- We need a strong guarantee that we won't endlessly rotate, so the
analysis would need to be precise in order to avoid the
SimplifiedLoopLatch precondition.
- Analysis like this are usually based on SCEV, which we don't want to
rely on.
(2) Rotate on-demand in late loop passes. This could even be done by
shoving the loop back on the queue after the optimization that needs
it. This could work well when we find LICM opportunities in
multi-branch loops. This requires some work, and it doesn't really
solve the problem of SCEV wanting a loop guard before the analysis.
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This function consists of following steps:
1. Collect dependent memory accesses.
2. Analyze availability.
3. Perform fully redundancy elimination, or
4. Perform PRE, depending on the availability
Step 2, 3 and 4 are now moved to three helper routines.
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Actually it took me couple of hours trying to make sense of them and
only to find they are dead code. I guess the original author used
"allSingleSucc" to indicate if there are any critial edge emanating
from some blocks, and tried to perform code motion (actually speculation)
in the presence of these critical edges; but later on he/she changed mind
and decided to perform edge-splitting first.
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the things, and renames it to CBindingWrapping.h. I also moved
CBindingWrapping.h into Support/.
This new file just contains the macros for defining different wrap/unwrap
methods.
The calls to those macros, as well as any custom wrap/unwrap definitions
(like for array of Values for example), are put into corresponding C++
headers.
Doing this required some #include surgery, since some .cpp files relied
on the fact that including Wrap.h implicitly caused the inclusion of a
bunch of other things.
This also now means that the C++ headers will include their corresponding
C API headers; for example Value.h must include llvm-c/Core.h. I think
this is harmless, since the C API headers contain just external function
declarations and some C types, so I don't believe there should be any
nasty dependency issues here.
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Shuffles are more difficult to lower and we usually don't touch them, while we do optimize selects more often.
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When Reassociator optimize "(x | C1)" ^ "(X & C2)", it may swap the two
subexpressions, however, it forgot to swap cached constants (of C1 and C2)
accordingly.
rdar://13739160
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Also add a check for llvm.used in the verifier and simplify clients now that
they can assume they have a ConstantArray.
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This is an edge case that can happen if we modify a chain of multiple selects.
Update all operands in that case and remove the assert. PR15805.
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I brazenly think this change is slightly simpler than r178793 because:
- no "state" in functor
- "OpndPtrs[i]" looks simpler than "&Opnds[OpndIndices[i]]"
While I can reproduce the probelm in Valgrind, it is rather difficult to come up
a standalone testing case. The reason is that when an iterator is invalidated,
the stale invalidated elements are not yet clobbered by nonsense data, so the
optimizer can still proceed successfully.
Thank Benjamin for fixing this bug and generously providing the test case.
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The fix for PR14972 in r177055 introduced a real think-o in the *store*
side, likely because I was much more focused on the load side. While we
can arbitrarily widen (or narrow) a loaded value, we can't arbitrarily
widen a value to be stored, as that changes the width of memory access!
Lock down the code path in the store rewriting which would do this to
only handle the intended circumstance.
All of the existing tests continue to pass, and I've added a test from
the PR.
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This optimization is unstable at this moment; it
1) block us on a very important application
2) PR15200
3) test6 and test7 in test/Transforms/ScalarRepl/dynamic-vector-gep.ll
(the CHECK command compare the output against wrong result)
I personally believe this optimization should not have any impact on the
autovectorized code, as auto-vectorizer is supposed to put gather/scatter
in a "right" way. Although in theory downstream optimizaters might reveal
some gather/scatter optimization opportunities, the chance is quite slim.
For the hand-crafted vectorizing code, in term of redundancy elimination,
load-CSE, copy-propagation and DSE can collectively achieve the same result,
but in much simpler way. On the other hand, these optimizers are able to
improve the code in a incremental way; in contrast, SROA is sort of all-or-none
approach. However, SROA might slighly win in stack size, as it tries to figure
out a stretch of memory tightenly cover the area accessed by the dynamic index.
rdar://13174884
PR15200
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