introduce a common superclass, SILNode.
This is in preparation for allowing instructions to have multiple
results. It is also a somewhat more elegant representation for
instructions that have zero results. Instructions that are known
to have exactly one result inherit from a class, SingleValueInstruction,
that subclasses both ValueBase and SILInstruction. Some care must be
taken when working with SILNode pointers and testing for equality;
please see the comment on SILNode for more information.
A number of SIL passes needed to be updated in order to handle this
new distinction between SIL values and SIL instructions.
Note that the SIL parser is now stricter about not trying to assign
a result value from an instruction (like 'return' or 'strong_retain')
that does not produce any.
In particular, support the following optimizations:
- owned-to-guaranteed
- dead argument elimination
Argument explosion is disabled for generics at the moment as it usually leads to a slower code.
Separate formal lowered types from SIL types.
The SIL type of an argument will depend on the SIL module's conventions.
The module conventions are determined by the SIL stage and LangOpts.
Almost NFC, but specialized manglings are broken incidentally as a result of
fixes to the way passes handle book-keeping of aruments. The mangler is fixed in
the subsequent commit.
Otherwise, NFC is intended, but quite possible do to rewriting the logic in many
places.
We don't want the machine calling conventions for closure invocation functions to necessarily be tied to the convention for normal thin functions or methods. NFC yet; for now, 'closure' follows the same behavior as the 'method' convention, but as part of partial_apply simplification it will be a requirement that partial_apply takes a @convention(closure) function and a box and produces a @convention(thick) function from them.
Several functionalities have been added to FSO over time and the logic has become
muddled.
We were always looking at a static image of the SIL and try to reason about what kind of
function signature related optimizations we can do.
This can easily lead to muddled logic. e.g. we need to consider 2 different function
signature optimizations together instead of independently.
Split 1 single function to do all sorts of different analyses in FSO into several
small transformations, each of which does a specific job. After every analysis, we produce
a new function and eventually we collapse all intermediate thunks to in a single thunk.
With this change, it will be easier to implement function signature optimization as now
we can do them independently now.
Small modifications to the test cases.
Several functionalities have been added to FSO over time and the logic has become
muddled.
We were always looking at a static image of the SIL and try to reason about what kind of
function signature related optimizations we can do.
This can easily lead to muddled logic. e.g. we need to consider 2 different function
signature optimizations together instead of independently.
Split 1 single function to do all sorts of different analyses in FSO into several
small transformations, each of which does a specific job. After every analysis, we produce
a new function and eventually we collapse all intermediate thunks to in a single thunk.
With this change, it will be easier to implement function signature optimization as now
we can do them independently now.
Minimal modifications to the test cases.
If we can not find the epilogue releases for all the fields with
reference sematics, but we found for some fields. Explode the argument.
I do not see a performance improvement with this change
rdar://25451364
Change the optimizer to only make specializations [fragile] if both the
original callee is [fragile] *and* the caller is [fragile].
Otherwise, the specialized callee might be [fragile] even if it is never
called from a [fragile] function, which inhibits the optimizer from
devirtualizing calls inside the specialization.
This opens up some missed optimization opportunities in the performance
inliner and devirtualization, which currently reject fragile->non-fragile
references:
TEST | OLD_MIN | NEW_MIN | DELTA (%) | SPEEDUP
--- | --- | --- | --- | ---
DictionaryRemoveOfObjects | 38391 | 35859 | -6.6% | **1.07x**
Hanoi | 5853 | 5288 | -9.7% | **1.11x**
Phonebook | 18287 | 14988 | -18.0% | **1.22x**
SetExclusiveOr_OfObjects | 20001 | 15906 | -20.5% | **1.26x**
SetUnion_OfObjects | 16490 | 12370 | -25.0% | **1.33x**
Right now, passes other than performance inlining and devirtualization
of class methods are not checking invariants on [fragile] functions
at all, which was incorrect; as part of the work on building the
standard library with -enable-resilience, I added these checks, which
regressed performance with resilience disabled. This patch makes up for
these regressions.
Furthermore, once SIL type lowering is aware of resilience, this will
allow the stack promotion pass to make further optimizations after
specializing [fragile] callees.
This split the function signature module pass into 2 functin passes.
By doing so, this allows us to rewrite to using the FSO-optimized
function prior to attempting inlining, but allow us to do a substantial
amount of optimization on the current function before attempting to do
FSO on that function.
And also helps us to move to a model which module pass is NOT used unless
necesary.
I do not see regression nor improvement for on the performance test suite.
functionsignopts.sil and functionsignopt_sroa.sil are modified because the
mangler now takes into account of information in the projection tree.
