Natural Loop Information
Loop Pass Manager
Canonicalize natural loops
Scalar Evolution Analysis
Loop Pass Manager
Induction Variable Users
Canonicalize natural loops
Induction Variable Users
Loop Strength Reduction
into this:
Scalar Evolution Analysis
Loop Pass Manager
Canonicalize natural loops
Induction Variable Users
Loop Strength Reduction
This fixes <rdar://problem/8869639>. I also filed PR9184 on doing this sort of
thing automatically, but it seems easier to just change the ordering of the
passes if this is the only case.
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the active loop. This is generally desirable, and it avoids trouble
in situations such as the testcase in PR9123, though the failure
mode depends on use-list order, so it is infeasible to test.
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must be called in the pass's constructor. This function uses static dependency declarations to recursively initialize
the pass's dependencies.
Clients that only create passes through the createFooPass() APIs will require no changes. Clients that want to use the
CommandLine options for passes will need to manually call the appropriate initialization functions in PassInitialization.h
before parsing commandline arguments.
I have tested this with all standard configurations of clang and llvm-gcc on Darwin. It is possible that there are problems
with the static dependencies that will only be visible with non-standard options. If you encounter any crash in pass
registration/creation, please send the testcase to me directly.
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perform initialization without static constructors AND without explicit initialization
by the client. For the moment, passes are required to initialize both their
(potential) dependencies and any passes they preserve. I hope to be able to relax
the latter requirement in the future.
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formulae which become illegal as a result of the offset updating don't
escape.
This is for rdar://8529692. No testcase yet, because the given cases
hit use-list ordering differences.
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This doesn't usually matter, because the other heuristics usually
succeed regardless, but it's good to keep the register use
bookkeeping consistent.
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other filtering techniques, as those may allow it to filter
out more obviously unprofitable candidates.
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LSRInstance data structures up to date. This fixes some
pessimizations caused by stale data which will be exposed
in an upcoming change.
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uninteresting, just put all the operands on one list and make
GenerateReassociations make the decision about what's interesting.
This is simpler, and it avoids an extra ScalarEvolution::getAddExpr call.
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ScalarEvolution::getAddExpr, which can be pretty expensive, when nothing
has changed, which is pretty common.
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different widths. In a use with a narrower fixup, formulae
may be wider than the fixup, in which case the high bits
aren't necessarily meaningful, so it isn't safe to reuse
them for uses with wider fixups.
This fixes PR7618, though the testcase is too large for a
reasonable regression test, since it heavily dependes on
hitting LSR's heuristics in a certain way.
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a zero. This situation arrises in Fortran code with induction variables
that start at 1 instead of 0. This fixes PR7651.
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SCEVUnknown values which are loop-variant, as LSR can't do anything
interesting with these values in any case. This fixes very slow compile
times on loops which have large numbers of such values.
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enough special case, and it theoretically allows more folding because
it works even when x is unanalyzable.
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