introduce no-return or unreachable heuristics.
The return heuristics from the Ball and Larus paper don't work well in
practice as they pessimize early return paths. The only good hitrate
return heuristics are those for:
- NULL return
- Constant return
- negative integer return
Only the last of these three can possibly require significant code for
the returning block, and even the last is fairly rare and usually also
a constant. As a consequence, even for the cold return paths, there is
little code on that return path, and so little code density to be gained
by sinking it. The places where sinking these blocks is valuable (inner
loops) will already be weighted appropriately as the edge is a loop-exit
branch.
All of this aside, early returns are nearly as common as all three of
these return categories, and should actually be predicted as taken!
Rather than muddy the waters of the static predictions, just remain
silent on returns and let the CFG itself dictate any layout or other
issues.
However, the return heuristic was flagging one very important case:
unreachable. Unfortunately it still gave a 1/4 chance of the
branch-to-unreachable occuring. It also didn't do a rigorous job of
finding those blocks which post-dominate an unreachable block.
This patch builds a more powerful analysis that should flag all branches
to blocks known to then reach unreachable. It also has better worst-case
runtime complexity by not looping through successors for each block. The
previous code would perform an N^2 walk in the event of a single entry
block branching to N successors with a switch where each successor falls
through to the next and they finally fall through to a return.
Test case added for noreturn heuristics. Also doxygen comments improved
along the way.
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state. Furthermore, they might not have two operands. This fixes the underlying
issue behind the crashes introduced in r142781.
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Assertion `i_nocapture < OperandTraits<PHINode>::operands(this) && "getOperand() out of range!"' failed.
coming out of indvars.
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a single class. Previously it was split between two classes, one
internal and one external. The concern seemed to center around exposing
the weights used, but those can remain confined to the implementation
file.
Having a single class to maintain the state and analyses in use will
also simplify several of the enhancements I want to make to our static
heuristics.
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extraneous whitespace. Trying to clean-up this pass as much as I can
before I start making functional changes.
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to bring it under direct test instead of merely indirectly testing it in
the BlockFrequencyInfo pass.
The next step is to start adding tests for the various heuristics
employed, and to start fixing those heuristics once they're under test.
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able to constant fold load instructions where the argument is a constant.
Second, we should be able to watch multiple PHI nodes through the loop; this
patch only supports PHIs in loop headers, more can be done here.
With this patch, we now constant evaluate:
static const int arr[] = {1, 2, 3, 4, 5};
int test() {
int sum = 0;
for (int i = 0; i < 5; ++i) sum += arr[i];
return sum;
}
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and switches, with arbitrary numbers of successors. Still optimized for
the common case of 2 successors for a conditional branch.
Add a test case for switch metadata showing up in the BlockFrequencyInfo pass.
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encoding of probabilities. In the absense of metadata, it continues to
fall back on static heuristics.
This allows __builtin_expect, after lowering through llvm.expect
a branch instruction's metadata, to actually enter the branch
probability model. This is one component of resolving PR2577.
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layer already had support for printing the results of this analysis, but
the wiring was missing.
Now that printing the analysis works, actually bring some of this
analysis, and the BranchProbabilityInfo analysis that it wraps, under
test! I'm planning on fixing some bugs and doing other work here, so
having a nice place to add regression tests and a way to observe the
results is really useful.
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Some code want to check that *any* call within a function has the 'returns
twice' attribute, not just that the current function has one.
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Just because we're dealing with a GEP doesn't mean we can assert the
SCEV has a pointer type. The fix is simply to ignore the SCEV pointer
type, which we really didn't need.
Fixes PR11138 webkit crash.
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could be arguments, for example.
No testcase because this is a bug-fix broken out of a larger optimization patch.
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Speculatively reapply to see if this test case still crashes on
linux. I may have fixed it in my last checkin.
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This avoids unnecessary expansion of expressions and allows the SCEV
expander to work on expression DAGs, not just trees.
Fixes PR11090.
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file. Since it should only be used when necessary propagate it through
the backend code generation and tweak testcases accordingly.
This helps with code like in clang's test/CodeGen/debug-info-line.c where
we have multiple #line directives within a single lexical block and want
to generate only a single block that contains each file change.
Part of rdar://10246360
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IVs.
Indvars previously chose randomly between congruent IVs. Now it will
bias the decision toward IVs that SCEVExpander likes to create. This
was not done to fix any problem, it's just a welcome side effect of
factoring code.
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I noticed during self-review that my previous checkin disabled some
analysis. Even with the reenabled analysis the test case runs in about
5ms. Without the fix, it will take several minutes at least.
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Note to compiler writers: never recurse on multiple instruction
operands without memoization.
Fixes rdar://10187945. Was taking 45s, now taking 5ms.
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We want heuristics to be based on accurate data, but more importantly
we don't want llvm to behave randomly. A benign trunc inserted by an
upstream pass should not cause a wild swings in optimization
level. See PR11034. It's a general problem with threshold-based
heuristics, but we can make it less bad.
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