Mark Lacey 1859b476d4 Further integration of inlining, devirtualization, and specialization. ...

This updates the performance inliner to iterate on inlining in cases
where devirtualization or specialization after the first pass of
inlining expose new opportunities for inlining. Similarly, in some cases
inlining exposes new opportunities for devirtualization, e.g. when we
inline an initializer and can now see an alloc_ref that allows us to
devirtualize some class_methods.

The implementation currently has some inefficiencies which increase the
swift compilation time for the stdlib by around 3% (this is swift-time
only, no LLVM time, so overall time does not grow by this much).

Unfortunately the (unchanged) current implementation of the core
inlining trades off improved estimates of code growth for increased
compile time, and that plays a part in why compile time increases as
much as it does. Despite this, I have some ideas on how to win some of
that time back in future patches.

Performance differences are mixed, and this will likely require some
further inliner tuning to reduce or remove some of the losses seen here
at -O. I will open radars for the losses.

Wins:
DeltaBlue                        10.2%
EditDistance                     13.8%
SwiftStructuresInsertionSort     32.6%
SwiftStructuresStack             34.9%

Losses:
PopFrontArrayGeneric            -12.7%
PrimeNum                        -19.0%
RC4                             -30.7%
Sim2DArray                      -14.6%

There were a handful of wins and losses at Onone and Ounchecked as
well. I'll review the perf testing output and open radars accordingly.

The new test case shows an example of the power of the closer
integration here. We are able to completely devirtualize and inline a
series of class_method applies (10 deep in this case, but in theory
substantially deeper) in a single pass of the inliner, whereas before we
could only do a single level per pass of inlining & devirtualization.

Swift SVN r27561

2015-04-22 04:48:13 +00:00

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