Although I don't plan to bring over new assertions wholesale
into the current qualification branch, it's entirely possible
that various minor changes in main will use the new assertions;
having this basic support in the release branch will simplify that.
(This is why I'm adding the includes as a separate pass from
rewriting the individual assertions)
And replace them with explicit `metatype` instruction in the entry block.
This allows such metatype instructions to be deleted if they are dead.
This was already done for performance-annotated functions. But now do this for all functions.
It is essential that performance-annotated functions are specialized in the same way as other functions.
Because otherwise it can happen that the same specialization has different performance characteristics in different modules.
And it's up to the linker to select one of those ODR functions when linking.
Also, dropping metatype arguments is good for performance and code size in general.
This change also contains a few bug fixes for dropping metatype arguments.
rdar://110509780
This invalidation kind is used when a compute-effects pass changes function effects.
Also, let optimization passes which don't change effects only invalidate the `FunctionBody` and not `Everything`.
The main point of this change is to make sure that a shared function always has a body: both, in the optimizer pipeline and in the swiftmodule file.
This is important because the compiler always needs to emit code for a shared function. Shared functions cannot be referenced from outside the module.
In several corner cases we missed to maintain this invariant which resulted in unresolved-symbol linker errors.
As side-effect of this change we can drop the shared_external SIL linkage and the IsSerializable flag, which simplifies the serialization and linkage concept.
If the specialized function has a re-abstracted (= converted from indirect to direct) resilient argument or return types, use an alternative mangling: "TB" instead of "Tg".
Resilient parameters/returns can be converted from indirect to direct if the specialization is created within the type's resilience domain, i.e. in its module (where the type is loadable).
In this case we need to generate a different mangled name for the specialized function to distinguish it from specializations in other modules, which cannot re-abstract this resilient type.
This fixes a miscompile resulting from ODR-linking specializations from different modules, which in fact have different function signatures.
https://bugs.swift.org/browse/SR-13900
rdar://71914016
The XXOptUtils.h convention is already established and parallels
the SIL/XXUtils convention.
New:
- InstOptUtils.h
- CFGOptUtils.h
- BasicBlockOptUtils.h
- ValueLifetime.h
Removed:
- Local.h
- Two conflicting CFG.h files
This reorganization is helpful before I introduce more
utilities for block cloning similar to SinkAddressProjections.
Move the control flow utilies out of Local.h, which was an
unreadable, unprincipled mess. Rename it to InstOptUtils.h, and
confine it to small APIs for working with individual instructions.
These are the optimizer's additions to /SIL/InstUtils.h.
Rename CFG.h to CFGOptUtils.h and remove the one in /Analysis. Now
there is only SIL/CFG.h, resolving the naming conflict within the
swift project (this has always been a problem for source tools). Limit
this header to low-level APIs for working with branches and CFG edges.
Add BasicBlockOptUtils.h for block level transforms (it makes me sad
that I can't use BBOptUtils.h, but SIL already has
BasicBlockUtils.h). These are larger APIs for cloning or removing
whole blocks.
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.
At some point, pass definitions were heavily macro-ized. Pass
descriptive names were added in two places. This is not only redundant
but a source of confusion. You could waste a lot of time grepping for
the wrong string. I removed all the getName() overrides which, at
around 90 passes, was a fairly significant amount of code bloat.
Any pass that we want to be able to invoke by name from a tool
(sil-opt) or pipeline plan *should* have unique type name, enum value,
commend-line string, and name string. I removed a comment about the
various inliner passes that contradicted that.
Side note: We should be consistent with the policy that a pass is
identified by its type. We have a couple passes, LICM and CSE, which
currently violate that convention.
Also, add a third [serializable] state for functions whose bodies we
*can* serialize, but only do so if they're referenced from another
serialized function.
This will be used for bodies synthesized for imported definitions,
such as init(rawValue:), etc, and various thunks, but for now this
change is NFC.
Previously it was part of swiftBasic.
The demangler library does not depend on llvm (except some header-only utilities like StringRef). Putting it into its own library makes sure that no llvm stuff will be linked into clients which use the demangler library.
This change also contains other refactoring, like moving demangler code into different files. This makes it easier to remove the old demangler from the runtime library when we switch to the new symbol mangling.
Also in this commit: remove some unused API functions from the demangler Context.
fixes rdar://problem/30503344
SubstitutionList is going to be a more compact representation of
a SubstitutionMap, suitable for inline allocation inside another
object.
For now, it's just a typedef for ArrayRef<Substitution>.
Changes:
* Terminate all namespaces with the correct closing comment.
* Make sure argument names in comments match the corresponding parameter name.
* Remove redundant get() calls on smart pointers.
* Prefer using "override" or "final" instead of "virtual". Remove "virtual" where appropriate.
The purpose of this change is to test if the new mangling is equivalent to the old mangling.
Both mangling strings are created, de-mangled and checked if the de-mangle trees are equivalent.
If we find a specialization within the current module, it's okay if it
has a body. This can come up if we compile something with optimizations
and then compile the resulting SIL (or SIB) without optimizations.
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 was mistakenly reverted in an attempt to fix buildbots.
Unfortunately it's now smashed into one commit.
---
Introduce @_specialize(<type list>) internal attribute.
This attribute can be attached to generic functions. The attribute's
arguments must be a list of concrete types to be substituted in the
function's generic signature. Any number of specializations may be
associated with a generic function.
This attribute provides a hint to the compiler. At -O, the compiler
will generate the specified specializations and emit calls to the
specialized code in the original generic function guarded by type
checks.
The current attribute is designed to be an internal tool for
performance experimentation. It does not affect the language or
API. This work may be extended in the future to add user-visible
attributes that do provide API guarantees and/or direct dispatch to
specialized code.
This attribute works on any generic function: a freestanding function
with generic type parameters, a nongeneric method declared in a
generic class, a generic method in a nongeneric class or a generic
method in a generic class. A function's generic signature is a
concatenation of the generic context and the function's own generic
type parameters.
e.g.
struct S<T> {
var x: T
@_specialize(Int, Float)
mutating func exchangeSecond<U>(u: U, _ t: T) -> (U, T) {
x = t
return (u, x)
}
}
// Substitutes: <T, U> with <Int, Float> producing:
// S<Int>::exchangeSecond<Float>(u: Float, t: Int) -> (Float, Int)
---
[SILOptimizer] Introduce an eager-specializer pass.
This pass finds generic functions with @_specialized attributes and
generates specialized code for the attribute's concrete types. It
inserts type checks and guarded dispatch at the beginning of the
generic function for each specialization. Since we don't currently
expose this attribute as API and don't specialize vtables and witness
tables yet, the only way to reach the specialized code is by calling
the generic function which performs the guarded dispatch.
In the future, we can build on this work in several ways:
- cross module dispatch directly to specialized code
- dynamic dispatch directly to specialized code
- automated specialization based on less specific hints
- partial specialization
- and so on...
I reorganized and refactored the optimizer's generic utilities to
support direct function specialization as opposed to apply
specialization.
Temporarily reverting @_specialize because stdlib unit tests are
failing on an internal branch during deserialization.
This reverts commit e2c43cfe14, reversing
changes made to 9078011f93.
This pass finds generic functions with @_specialized attributes and
generates specialized code for the attribute's concrete types. It
inserts type checks and guarded dispatch at the beginning of the
generic function for each specialization. Since we don't currently
expose this attribute as API and don't specialize vtables and witness
tables yet, the only way to reach the specialized code is by calling
the generic function which performs the guarded dispatch.
In the future, we can build on this work in several ways:
- cross module dispatch directly to specialized code
- dynamic dispatch directly to specialized code
- automated specialization based on less specific hints
- partial specialization
- and so on...
I reorganized and refactored the optimizer's generic utilities to
support direct function specialization as opposed to apply
specialization.
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.
With this re-abstraction a specialized function has the same calling convention as if it would have been written with the specialized types in the first place.
In general this results in less alloc_stacks and load/stores.
It also can eliminate some re-abstraction thunks, e.g. if a generic closure is used in a non-generic context.
It some (hopefully rare) cases it may require to add re-abstraction thunks.
In case a function has multiple indirect results, only the first is converted to a direct result. This is an open TODO.
This commit changes the Swift mangler from a utility that writes tokens into a
stream into a name-builder that has two phases: "building a name", and "ready".
This clear separation is needed for the implementation of the compression layer.
Users of the mangler can continue to build the name using the mangleXXX methods,
but to access the results the users of the mangler need to call the finalize()
method. This method can write the result into a stream, like before, or return
an std::string.
