This removes the ambiguity when casting from a SingleValueInstruction to SILNode, which makes the code simpler. E.g. the "isRepresentativeSILNode" logic is not needed anymore.
Also, it reduces the size of the most used instruction class - SingleValueInstruction - by one pointer.
Conceptually, SILInstruction is still a SILNode. But implementation-wise SILNode is not a base class of SILInstruction anymore.
Only the two sub-classes of SILInstruction - SingleValueInstruction and NonSingleValueInstruction - inherit from SILNode. SingleValueInstruction's SILNode is embedded into a ValueBase and its relative offset in the class is the same as in NonSingleValueInstruction (see SILNodeOffsetChecker).
This makes it possible to cast from a SILInstruction to a SILNode without knowing which SILInstruction sub-class it is.
Casting to SILNode cannot be done implicitly, but only with an LLVM `cast` or with SILInstruction::asSILNode(). But this is a rare case anyway.
This removes the ambiguity when casting from a SingleValueInstruction to SILNode, which makes the code simpler. E.g. the "isRepresentativeSILNode" logic is not needed anymore.
Also, it reduces the size of the most used instruction class - SingleValueInstruction - by one pointer.
Conceptually, SILInstruction is still a SILNode. But implementation-wise SILNode is not a base class of SILInstruction anymore.
Only the two sub-classes of SILInstruction - SingleValueInstruction and NonSingleValueInstruction - inherit from SILNode. SingleValueInstruction's SILNode is embedded into a ValueBase and its relative offset in the class is the same as in NonSingleValueInstruction (see SILNodeOffsetChecker).
This makes it possible to cast from a SILInstruction to a SILNode without knowing which SILInstruction sub-class it is.
Casting to SILNode cannot be done implicitly, but only with an LLVM `cast` or with SILInstruction::asSILNode(). But this is a rare case anyway.
With the advent of dynamic_function_ref the actual callee of such a ref
my vary. Optimizations should not assume to know the content of a
function referenced by dynamic_function_ref. Introduce
getReferencedFunctionOrNull which will return null for such function
refs. And getInitialReferencedFunction to return the referenced
function.
Use as appropriate.
rdar://50959798
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.
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.
For a long time, we have:
1. Created methods on SILArgument that only work on either function arguments or
block arguments.
2. Created code paths in the compiler that only allow for "function"
SILArguments or "block" SILArguments.
This commit refactors SILArgument into two subclasses, SILPHIArgument and
SILFunctionArgument, separates the function and block APIs onto the subclasses
(leaving the common APIs on SILArgument). It also goes through and changes all
places in the compiler that conditionalize on one of the forms of SILArgument to
just use the relevant subclass. This is made easier by the relevant APIs not
being on SILArgument anymore. If you take a quick look through you will see that
the API now expresses a lot more of its intention.
The reason why I am performing this refactoring now is that SILFunctionArguments
have a ValueOwnershipKind defined by the given function's signature. On the
other hand, SILBlockArguments have a stored ValueOwnershipKind. Rather than
store ValueOwnershipKind in both instances and in the function case have a dead
variable, I decided to just bite the bullet and fix this.
rdar://29671437
We were giving special handling to ApplyInst when we were attempting to use
getMemoryBehavior(). This commit changes the special handling to work on all
full apply sites instead of just AI. Additionally, we look through partial
applies and thin to thick functions.
I also added a dumper called BasicInstructionPropertyDumper that just dumps the
results of SILInstruction::get{Memory,Releasing}Behavior() for all instructions
in order to verify this behavior.
Similarly to how we've always handled parameter types, we
now recursively expand tuples in result types and separately
determine a result convention for each result.
The most important code-generation change here is that
indirect results are now returned separately from each
other and from any direct results. It is generally far
better, when receiving an indirect result, to receive it
as an independent result; the caller is much more likely
to be able to directly receive the result in the address
they want to initialize, rather than having to receive it
in temporary memory and then copy parts of it into the
target.
The most important conceptual change here that clients and
producers of SIL must be aware of is the new distinction
between a SILFunctionType's *parameters* and its *argument
list*. The former is just the formal parameters, derived
purely from the parameter types of the original function;
indirect results are no longer in this list. The latter
includes the indirect result arguments; as always, all
the indirect results strictly precede the parameters.
Apply instructions and entry block arguments follow the
argument list, not the parameter list.
A relatively minor change is that there can now be multiple
direct results, each with its own result convention.
This is a minor change because I've chosen to leave
return instructions as taking a single operand and
apply instructions as producing a single result; when
the type describes multiple results, they are implicitly
bound up in a tuple. It might make sense to split these
up and allow e.g. return instructions to take a list
of operands; however, it's not clear what to do on the
caller side, and this would be a major change that can
be separated out from this already over-large patch.
Unsurprisingly, the most invasive changes here are in
SILGen; this requires substantial reworking of both call
emission and reabstraction. It also proved important
to switch several SILGen operations over to work with
RValue instead of ManagedValue, since otherwise they
would be forced to spuriously "implode" buffers.
Tested via static assert.
There is no reason for these data structures to not have these properties.
Adding these properties will improve the compile time efficiency of ARC by
allowing for cheaper copying and 0 cost destruction.
This speeds and reduces memory consumption of test cases with large
CFGs. The specific test case that spawned this fix was a large function
with many dictionary assignments:
public func func_0(dictIn : [String : MyClass]) -> [String : MyClass] {
var dictOut : [String : MyClass] = [:]
dictOut["key5000"] = dictIn["key500"]
dictOut["key5010"] = dictIn["key501"]
dictOut["key5020"] = dictIn["key502"]
dictOut["key5030"] = dictIn["key503"]
dictOut["key5040"] = dictIn["key504"]
...
}
This continued for 10k - 20k values.
This commit reduces the compile time by 2.5x and reduces the amount of
memory allocated by ARC by 2.6x (the memory allocation number includes
memory that is subsequently freed).
rdar://24350646
(libraries now)
It has been generally agreed that we need to do this reorg, and now
seems like the perfect time. Some major pass reorganization is in the
works.
This does not have to be the final word on the matter. The consensus
among those working on the code is that it's much better than what we
had and a better starting point for future bike shedding.
Note that the previous organization was designed to allow separate
analysis and optimization libraries. It turns out this is an
artificial distinction and not an important goal.
