docs/HighLevelSILOptimizations.rst - third_party/swift - Git at Google

 :orphan:

 .. _HighLevelSILOptimizations:

 High-Level Optimizations in SIL
 ===============================

 .. contents::

 Abstract
 --------

 This document describes the high-level abstraction of built-in Swift
 data structures in SIL that is used by the optimizer. You need to read
 this document if you wish to understand the early stages of the Swift
 optimizer or if you are working on one of the containers in the
 standard library.


 Why do we need high-level optimizations?
 -----------------------------------------

 Swift containers are implemented in the Swift standard library in Swift code.
 Traditional compiler optimizations can remove some of the redundancy that is
 found in high-level code, but not all of it. Without knowledge of the Swift
 language the optimizer can't perform high-level optimizations on the built-in
 containers. For example::

   Dict["a"] = 1
   Dict["a"] = 2

 Any Swift developer could identify the redundancy in the code sample above.
 Storing two values into the same key in the dictionary is inefficient.
 However, optimizing compilers are unaware of the special semantics that the
 Swift dictionary has and can't perform this optimization. Traditional
 compilers would start optimizing this code by inlining the subscript
 function call and try to analyze the sequence of load/store instructions.
 This approach is not very effective because the compiler has to be very
 conservative when optimizing general code with pointers.

 On the other hand, compilers for high-level languages usually have special
 bytecode instructions that allow them to perform high-level optimizations.
 However, unlike high-level languages such as JavaScript or Python, Swift
 containers are implemented in Swift itself. Moreover, it is beneficial to
 be able to inline code from the container into the user program and optimize
 them together, especially for code that uses Generics.

 In order to perform both high-level optimizations, that are common in
 high-level languages, and low-level optimizations we annotate parts of the
 standard library and describe the semantics of a domain-specific high-level
 operations on data types in the Swift standard library.

 Annotation of code in the standard library
 ------------------------------------------

 We use the ``@_semantics`` attribute to annotate code in the standard library.
 These annotations can be used by the high-level SIL optimizer to perform
 domain-specific optimizations. The same function may have multiple ``@_semantics``
 attributes.

 This is an example of the ``@_semantics`` attribute::

   @public @_semantics("array.count")
   func getCount() -> Int {
     return _buffer.count
    }

 In this example we annotate a member of the Swift array struct with the tag
 ``array.count``. This tag informs the optimizer that this method reads the
 size of the array.


 The ``@_semantics`` attribute allows us to define "builtin" SIL-level
 operations implemented in Swift code. In SIL code they are encoded as
 apply instructions, but the optimizer can operate on them as atomic
 instructions. The semantic annotations don't necessarily need to be on
 public APIs. For example, the Array subscript operator may invoke two
 operations in the semantic model. One for checking the bounds and
 another one for accessing the elements. With this abstraction the
 optimizer can remove the ``checkSubscript`` instruction and keep the
 getElement instruction::

   @public subscript(index: Int) -> Element {
      get {
       checkSubscript(index)
       return getElement(index)
      }

   @_semantics("array.check_subscript") func checkSubscript(_ index: Int) {
     ...
   }

   @_semantics("array.get_element") func getElement(_ index: Int) -> Element {
     return _buffer[index]
   }


 Swift optimizations
 -------------------
 The Swift optimizer can access the information that is provided by the
 ``@_semantics`` attribute to perform high-level optimizations. In the early
 stages of the optimization pipeline the optimizer does not inline functions
 with special semantics in order to allow the early high-level optimization
 passes to operate on them. In the later stages of the optimization pipeline
 the optimizer inlines functions with special semantics to allow low-level
 optimizations.


 Annotated data structures in the standard library
 -------------------------------------------------

 This section describes the semantic tags that are assigned to data-structures
 in the standard library and the axioms that the optimizer uses.


 Cloning code from the standard library
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

 The Swift compiler can copy code from the standard library into the
 application for functions marked @inlinable. This allows the optimizer to
 inline calls from the stdlib and improve the performance of code that uses
 common operators such as '+=' or basic containers such as Array. However,
 importing code from the standard library can increase the binary size.

 To prevent copying of functions from the standard library into the user
 program, make sure the function in question is not marked @inlinable.

 Array
 ~~~~~

 The following semantic tags describe Array operations. The operations
 are first described in terms of the Array "state". Relations between the
 operations are formally defined below. 'Array' refers to the standard library
 Array<Element>, ContiguousArray<Element>, and ArraySlice<Element>
 data-structures.

 We consider the array state to consist of a set of disjoint elements
 and a storage descriptor that encapsulates non-element data such as the
 element count and capacity. Operations that semantically write state
 are always *control dependent*. A control dependent operation is one
 that may only be executed on the control flow paths in which the
 operation originally appeared, ignoring potential program
 exits. Generally, operations that only read state are not control
 dependent. One exception is ``check_subscript`` which is readonly but
 control dependent because it may trap. Some operations are *guarded*
 by others. A guarded operation can never be executed before its
 guard.

 array.init

   Initialize an array with new storage. This currently applies to any
   initializer that does not get its storage from an argument. This
   semantically writes to every array element and the array's storage
   descriptor. ``init`` also implies the guarding semantics of
   ``make_mutable``. It is not itself guarded by ``make_mutable`` and
   may act as a guard to other potentially mutating operations, such as
   ``get_element_address``.

 array.uninitialized(count: Builtin.Word) -> (Array<Element>, Builtin.RawPointer)

   Creates an array with the specified number of elements. It initializes
   the storage descriptor but not the array elements. The returned tuple
   contains the new array and a raw pointer to the element storage.
   The caller is responsible for writing the elements to the element storage.

 array.props.isCocoa/needsElementTypeCheck -> Bool

   Reads storage descriptors properties (isCocoa, needsElementTypeCheck).
   This is not control dependent or guarded. The optimizer has
   semantic knowledge of the state transfer those properties cannot make:
   An array that is not ``isCocoa`` cannot transfer to ``isCocoa``.
   An array that is not ``needsElementTypeCheck`` cannot transfer to
   ``needsElementTypeCheck``.

 array.get_element(index: Int) -> Element

    Read an element from the array at the specified index. No other
    elements are read. The storage descriptor is not read. No state is
    written. This operation is not control dependent, but may be
    guarded by ``check_subscript``. Any ``check_subscript`` may act as a
    guard, regardless of the index being checked [#f1]_.

 array.get_element_address(index: Int) -> UnsafeMutablePointer<Element>

    Get the address of an element of the array. No state is written. The storage
    descriptor is not read. The resulting pointer may be used to access elements
    in the array. This operation is not control dependent, but may be guarded by
    ``check_subscript``. Any ``check_subscript``, ``make_mutable`` or
    ``mutate_unknown`` may act as a guard.

 array.check_subscript(index: Int)

   Read the array count from the storage descriptor. Execute a ``trap``
   if ``index < array.startIndex || index >= array.endIndex``. No elements are
   read. No state is written. Despite being read only, this operation is control
   dependent.

 array.get_count() -> Int

   Read the array count (``array.endIndex - array.startIndex``) from the storage
   descriptor. No elements are read. No state is written. This is neither guarded
   nor control dependent.

 array.get_capacity() -> Int

   Read the array capacity from the storage descriptor. The semantics
   are identical to ``get_count`` except for the meaning of the return value.

 array.append_element(newElement: Element)

   Appends a single element to the array. No elements are read.
   The operation is itself guarded by ``make_mutable``.
   In contrast to other semantics operations, this operation is allowed to be
   inlined in the early stages of the compiler.

 array.append_contentsOf(contentsOf newElements: S)

   Appends all elements from S, which is a Sequence. No elements are read.
   The operation is itself guarded by ``make_mutable``.

 array.make_mutable()

   This operation guards mutating operations that don't already imply
   ``make_mutable`` semantics. (Currently, the only guarded operation
   is ``get_element_address``.) ``make_mutable`` may create a copy of the array
   storage; however, semantically it neither reads nor writes the array
   state. It does not write state simply because the copy's state is
   identical to the original. It does not read state because no other
   Array operations can undo mutability--only code that retains a
   reference to the Array can do that. ``make_mutable`` does
   effectively need to be guarded by any SIL operation that may retain
   the array. Because ``make_mutable`` semantically does not read the
   array state, is idempotent, and has no control dependence, it can be
   executed safely on any array at any point. i.e. the optimizer can
   freely insert calls to make_mutable.

 array.mutate_unknown

   This operation may mutate the array in any way, so it semantically
   writes to the entire array state and is naturally control
   dependent. ``mutate_unknown`` also implies the guarding semantics of
   ``make_mutable``. It is not itself guarded by ``make_mutable`` and
   may act as a guard to other mutating operations, such as
   ``get_element_address``. Combining semantics allows the flexibility in how
   the array copy is implemented in conjunction with implementing
   mutating functionality. This may be more efficient than cleanly
   isolating the copy and mutation code.

 To complete the semantics understood by the optimizer, we define these relations:

 interferes-with

   Given idempotent ``OpA``, the sequence "``OpA, OpB, OpA``" is
   semantically equivalent to the sequence "``OpA, OpB``" *iff* ``OpB``
   does not interfere with ``OpA``.

   All array operations marked with semantics are idempotent as long as
   they call the same function with the same argument values, with the
   exception of ``mutate_unknown``.

 guards

   If ``OpA`` guards ``OpB``, then the sequence of operations
   ``OpA, OpB`` must be preserved on any control flow path on which the
   sequence originally appears.

 An operation can only interfere-with or guard another if they may operate on the same Array.
 ``get_element_address`` is abbreviated with ``get_elt_addr`` in the table below.

 ================ =============== ==========================================
 semantic op      relation        semantic ops
 ================ =============== ==========================================
 make_mutable     guards          get_element_address
 check_subscript  guards          get_element, get_element_address
 make_mutable     interferes-with props.isCocoa/needsElementTypeCheck
 get_elt_addr     interferes-with get_element, get_element_address,
                                  props.isCocoa/needsElementTypeCheck
 mutate_unknown   interferes-with get_element, check_subscript, get_count,
                                  get_capacity, get_element_address,
                                  props.isCocoa/needsElementTypeCheck
 ================ =============== ==========================================

 .. [#f1] Any check_subscript(N) may act as a guard for
          ``get_element(i)/get_element_address(i)`` as long as it can be
          shown that ``N >= i``.

 In addition to preserving these semantics, the optimizer must
 conservatively handle any unknown access to the array object. For
 example, if a SIL operation takes the address to any member of the
 Array, any subsequent operations that may have visibility of that
 address are considered to interfere with any array operations with
 explicit semantics.

 String
 ~~~~~~

 string.concat(lhs: String, rhs: String) -> String

   Performs concatenation of two strings. Operands are not mutated.
   This operation can be optimized away in case of both operands
   being string literals. In this case, it can be replaced by
   a string literal representing a concatenation of both operands.

 string.makeUTF8(start: RawPointer, utf8CodeUnitCount: Word, isASCII: Int1) -> String

   Converts a built-in UTF8-encoded string literal into a string.

 string.makeUTF16(start: RawPointer, utf16CodeUnitCount: Word) -> String

   Converts a built-in UTF16-encoded string literal into a string.

 Dictionary
 ~~~~~~~~~~
 TBD.

 @_effects attribute
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~

 The @_effects attribute describes how a function affects "the state of the world".
 More practically how the optimizer can modify the program based on information
 that is provided by the attribute.

 Usage:

   @_effects(readonly) func foo() { .. }


 The @_effects attribute supports the following tags:

 readnone

   function has no side effects and no dependencies on the state of
   the program. It always returns an identical result given
   identical inputs. Calls to readnone functions can be eliminated,
   reordered, and folded arbitrarily.

 readonly

   function has no side effects, but is dependent on the global
   state of the program. Calls to readonly functions can be
   eliminated, but cannot be reordered or folded in a way that would
   move calls to the readnone function across side effects.

 releasenone

   function has side effects, it can read or write global state, or state
   reachable from its arguments. It can however be assumed that no externally
   visible release has happened (i.e it is allowed for a ``releasenone``
   function to allocate and destruct an object in its implementation as long as
   this is does not cause an release of an object visible outside of the
   implementation). Here are some examples::

     class SomeObject {
       final var x: Int = 3
     }

     var global = SomeObject()

     class SomeOtherObject {
       var x: Int = 2
       deinit {
         global = SomeObject()
       }
     }

     @_effects(releasenone)
     func validReleaseNoneFunction(x: Int) -> Int {
       global.x = 5
       return x + 2
     }

     @_effects(releasenone)
     func validReleaseNoneFunction(x: Int) -> Int {
       var notExternallyVisibleObject = SomeObject()
       return x +  notExternallyVisibleObject.x
     }

     func notAReleaseNoneFunction(x: Int, y: SomeObject) -> Int {
       return x + y.x
     }

     func notAReleaseNoneFunction(x: Int) -> Int {
       var releaseExternallyVisible = SomeOtherObject()
       return x + releaseExternallyVisible.x
     }

 readwrite

   function has side effects and the optimizer can't assume anything.

 Optimize semantics attribute
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

 The optimize attribute adds function-specific directives to the optimizer.

 The optimize attribute supports the following tags:

 sil.specialize.generic.never

    The sil optimizer should never create generic specializations of this function.

 optimize.sil.specialize.generic.partial.never

    The sil optimizer should never create generic partial specializations of this function.

 Availability checks
 ~~~~~~~~~~~~~~~~~~~

 The availability attribute is used for functions which implement the ``if #available``
 guards.

 The availability attribute supports the following tags:

 availability.osversion(major: Builtin.Word, minor: Builtin.Word, patch: Builtin.Word) -> Builtin.Int1

   Returns true if the OS version matches the parameters.
	:orphan:

	.. _HighLevelSILOptimizations:

	High-Level Optimizations in SIL
	===============================

	.. contents::

	Abstract
	--------

	This document describes the high-level abstraction of built-in Swift
	data structures in SIL that is used by the optimizer. You need to read
	this document if you wish to understand the early stages of the Swift
	optimizer or if you are working on one of the containers in the
	standard library.


	Why do we need high-level optimizations?
	-----------------------------------------

	Swift containers are implemented in the Swift standard library in Swift code.
	Traditional compiler optimizations can remove some of the redundancy that is
	found in high-level code, but not all of it. Without knowledge of the Swift
	language the optimizer can't perform high-level optimizations on the built-in
	containers. For example::

	Dict["a"] = 1
	Dict["a"] = 2

	Any Swift developer could identify the redundancy in the code sample above.
	Storing two values into the same key in the dictionary is inefficient.
	However, optimizing compilers are unaware of the special semantics that the
	Swift dictionary has and can't perform this optimization. Traditional
	compilers would start optimizing this code by inlining the subscript
	function call and try to analyze the sequence of load/store instructions.
	This approach is not very effective because the compiler has to be very
	conservative when optimizing general code with pointers.

	On the other hand, compilers for high-level languages usually have special
	bytecode instructions that allow them to perform high-level optimizations.
	However, unlike high-level languages such as JavaScript or Python, Swift
	containers are implemented in Swift itself. Moreover, it is beneficial to
	be able to inline code from the container into the user program and optimize
	them together, especially for code that uses Generics.

	In order to perform both high-level optimizations, that are common in
	high-level languages, and low-level optimizations we annotate parts of the
	standard library and describe the semantics of a domain-specific high-level
	operations on data types in the Swift standard library.

	Annotation of code in the standard library
	------------------------------------------

	We use the ``@_semantics`` attribute to annotate code in the standard library.
	These annotations can be used by the high-level SIL optimizer to perform
	domain-specific optimizations. The same function may have multiple ``@_semantics``
	attributes.

	This is an example of the ``@_semantics`` attribute::

	@public @_semantics("array.count")
	func getCount() -> Int {
	return _buffer.count
	}

	In this example we annotate a member of the Swift array struct with the tag
	``array.count``. This tag informs the optimizer that this method reads the
	size of the array.


	The ``@_semantics`` attribute allows us to define "builtin" SIL-level
	operations implemented in Swift code. In SIL code they are encoded as
	apply instructions, but the optimizer can operate on them as atomic
	instructions. The semantic annotations don't necessarily need to be on
	public APIs. For example, the Array subscript operator may invoke two
	operations in the semantic model. One for checking the bounds and
	another one for accessing the elements. With this abstraction the
	optimizer can remove the ``checkSubscript`` instruction and keep the
	getElement instruction::

	@public subscript(index: Int) -> Element {
	get {
	checkSubscript(index)
	return getElement(index)
	}

	@_semantics("array.check_subscript") func checkSubscript(_ index: Int) {
	...
	}

	@_semantics("array.get_element") func getElement(_ index: Int) -> Element {
	return _buffer[index]
	}


	Swift optimizations
	-------------------
	The Swift optimizer can access the information that is provided by the
	``@_semantics`` attribute to perform high-level optimizations. In the early
	stages of the optimization pipeline the optimizer does not inline functions
	with special semantics in order to allow the early high-level optimization
	passes to operate on them. In the later stages of the optimization pipeline
	the optimizer inlines functions with special semantics to allow low-level
	optimizations.


	Annotated data structures in the standard library
	-------------------------------------------------

	This section describes the semantic tags that are assigned to data-structures
	in the standard library and the axioms that the optimizer uses.


	Cloning code from the standard library
	~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

	The Swift compiler can copy code from the standard library into the
	application for functions marked @inlinable. This allows the optimizer to
	inline calls from the stdlib and improve the performance of code that uses
	common operators such as '+=' or basic containers such as Array. However,
	importing code from the standard library can increase the binary size.

	To prevent copying of functions from the standard library into the user
	program, make sure the function in question is not marked @inlinable.

	Array
	~~~~~

	The following semantic tags describe Array operations. The operations
	are first described in terms of the Array "state". Relations between the
	operations are formally defined below. 'Array' refers to the standard library
	Array<Element>, ContiguousArray<Element>, and ArraySlice<Element>
	data-structures.

	We consider the array state to consist of a set of disjoint elements
	and a storage descriptor that encapsulates non-element data such as the
	element count and capacity. Operations that semantically write state
	are always control dependent. A control dependent operation is one
	that may only be executed on the control flow paths in which the
	operation originally appeared, ignoring potential program
	exits. Generally, operations that only read state are not control
	dependent. One exception is ``check_subscript`` which is readonly but
	control dependent because it may trap. Some operations are guarded
	by others. A guarded operation can never be executed before its
	guard.

	array.init

	Initialize an array with new storage. This currently applies to any
	initializer that does not get its storage from an argument. This
	semantically writes to every array element and the array's storage
	descriptor. ``init`` also implies the guarding semantics of
	``make_mutable``. It is not itself guarded by ``make_mutable`` and
	may act as a guard to other potentially mutating operations, such as
	``get_element_address``.

	array.uninitialized(count: Builtin.Word) -> (Array<Element>, Builtin.RawPointer)

	Creates an array with the specified number of elements. It initializes
	the storage descriptor but not the array elements. The returned tuple
	contains the new array and a raw pointer to the element storage.
	The caller is responsible for writing the elements to the element storage.

	array.props.isCocoa/needsElementTypeCheck -> Bool

	Reads storage descriptors properties (isCocoa, needsElementTypeCheck).
	This is not control dependent or guarded. The optimizer has
	semantic knowledge of the state transfer those properties cannot make:
	An array that is not ``isCocoa`` cannot transfer to ``isCocoa``.
	An array that is not ``needsElementTypeCheck`` cannot transfer to
	``needsElementTypeCheck``.

	array.get_element(index: Int) -> Element

	Read an element from the array at the specified index. No other
	elements are read. The storage descriptor is not read. No state is
	written. This operation is not control dependent, but may be
	guarded by ``check_subscript``. Any ``check_subscript`` may act as a
	guard, regardless of the index being checked [#f1]_.

	array.get_element_address(index: Int) -> UnsafeMutablePointer<Element>

	Get the address of an element of the array. No state is written. The storage
	descriptor is not read. The resulting pointer may be used to access elements
	in the array. This operation is not control dependent, but may be guarded by
	``check_subscript``. Any ``check_subscript``, ``make_mutable`` or
	``mutate_unknown`` may act as a guard.

	array.check_subscript(index: Int)

	Read the array count from the storage descriptor. Execute a ``trap``
	if ``index < array.startIndex \|\| index >= array.endIndex``. No elements are
	read. No state is written. Despite being read only, this operation is control
	dependent.

	array.get_count() -> Int

	Read the array count (``array.endIndex - array.startIndex``) from the storage
	descriptor. No elements are read. No state is written. This is neither guarded
	nor control dependent.

	array.get_capacity() -> Int

	Read the array capacity from the storage descriptor. The semantics
	are identical to ``get_count`` except for the meaning of the return value.

	array.append_element(newElement: Element)

	Appends a single element to the array. No elements are read.
	The operation is itself guarded by ``make_mutable``.
	In contrast to other semantics operations, this operation is allowed to be
	inlined in the early stages of the compiler.

	array.append_contentsOf(contentsOf newElements: S)

	Appends all elements from S, which is a Sequence. No elements are read.
	The operation is itself guarded by ``make_mutable``.

	array.make_mutable()

	This operation guards mutating operations that don't already imply
	``make_mutable`` semantics. (Currently, the only guarded operation
	is ``get_element_address``.) ``make_mutable`` may create a copy of the array
	storage; however, semantically it neither reads nor writes the array
	state. It does not write state simply because the copy's state is
	identical to the original. It does not read state because no other
	Array operations can undo mutability--only code that retains a
	reference to the Array can do that. ``make_mutable`` does
	effectively need to be guarded by any SIL operation that may retain
	the array. Because ``make_mutable`` semantically does not read the
	array state, is idempotent, and has no control dependence, it can be
	executed safely on any array at any point. i.e. the optimizer can
	freely insert calls to make_mutable.

	array.mutate_unknown

	This operation may mutate the array in any way, so it semantically
	writes to the entire array state and is naturally control
	dependent. ``mutate_unknown`` also implies the guarding semantics of
	``make_mutable``. It is not itself guarded by ``make_mutable`` and
	may act as a guard to other mutating operations, such as
	``get_element_address``. Combining semantics allows the flexibility in how
	the array copy is implemented in conjunction with implementing
	mutating functionality. This may be more efficient than cleanly
	isolating the copy and mutation code.

	To complete the semantics understood by the optimizer, we define these relations:

	interferes-with

	Given idempotent ``OpA``, the sequence "``OpA, OpB, OpA``" is
	semantically equivalent to the sequence "``OpA, OpB``" iff ``OpB``
	does not interfere with ``OpA``.

	All array operations marked with semantics are idempotent as long as
	they call the same function with the same argument values, with the
	exception of ``mutate_unknown``.

	guards

	If ``OpA`` guards ``OpB``, then the sequence of operations
	``OpA, OpB`` must be preserved on any control flow path on which the
	sequence originally appears.

	An operation can only interfere-with or guard another if they may operate on the same Array.
	``get_element_address`` is abbreviated with ``get_elt_addr`` in the table below.

	================ =============== ==========================================
	semantic op relation semantic ops
	================ =============== ==========================================
	make_mutable guards get_element_address
	check_subscript guards get_element, get_element_address
	make_mutable interferes-with props.isCocoa/needsElementTypeCheck
	get_elt_addr interferes-with get_element, get_element_address,
	props.isCocoa/needsElementTypeCheck
	mutate_unknown interferes-with get_element, check_subscript, get_count,
	get_capacity, get_element_address,
	props.isCocoa/needsElementTypeCheck
	================ =============== ==========================================

	.. [#f1] Any check_subscript(N) may act as a guard for
	``get_element(i)/get_element_address(i)`` as long as it can be
	shown that ``N >= i``.

	In addition to preserving these semantics, the optimizer must
	conservatively handle any unknown access to the array object. For
	example, if a SIL operation takes the address to any member of the
	Array, any subsequent operations that may have visibility of that
	address are considered to interfere with any array operations with
	explicit semantics.

	String
	~~~~~~

	string.concat(lhs: String, rhs: String) -> String

	Performs concatenation of two strings. Operands are not mutated.
	This operation can be optimized away in case of both operands
	being string literals. In this case, it can be replaced by
	a string literal representing a concatenation of both operands.

	string.makeUTF8(start: RawPointer, utf8CodeUnitCount: Word, isASCII: Int1) -> String

	Converts a built-in UTF8-encoded string literal into a string.

	string.makeUTF16(start: RawPointer, utf16CodeUnitCount: Word) -> String

	Converts a built-in UTF16-encoded string literal into a string.

	Dictionary
	~~~~~~~~~~
	TBD.

	@_effects attribute
	~~~~~~~~~~~~~~~~~~~~~~~~~~~

	The @_effects attribute describes how a function affects "the state of the world".
	More practically how the optimizer can modify the program based on information
	that is provided by the attribute.

	Usage:

	@_effects(readonly) func foo() { .. }


	The @_effects attribute supports the following tags:

	readnone

	function has no side effects and no dependencies on the state of
	the program. It always returns an identical result given
	identical inputs. Calls to readnone functions can be eliminated,
	reordered, and folded arbitrarily.

	readonly

	function has no side effects, but is dependent on the global
	state of the program. Calls to readonly functions can be
	eliminated, but cannot be reordered or folded in a way that would
	move calls to the readnone function across side effects.

	releasenone

	function has side effects, it can read or write global state, or state
	reachable from its arguments. It can however be assumed that no externally
	visible release has happened (i.e it is allowed for a ``releasenone``
	function to allocate and destruct an object in its implementation as long as
	this is does not cause an release of an object visible outside of the
	implementation). Here are some examples::

	class SomeObject {
	final var x: Int = 3
	}

	var global = SomeObject()

	class SomeOtherObject {
	var x: Int = 2
	deinit {
	global = SomeObject()
	}
	}

	@_effects(releasenone)
	func validReleaseNoneFunction(x: Int) -> Int {
	global.x = 5
	return x + 2
	}

	@_effects(releasenone)
	func validReleaseNoneFunction(x: Int) -> Int {
	var notExternallyVisibleObject = SomeObject()
	return x + notExternallyVisibleObject.x
	}

	func notAReleaseNoneFunction(x: Int, y: SomeObject) -> Int {
	return x + y.x
	}

	func notAReleaseNoneFunction(x: Int) -> Int {
	var releaseExternallyVisible = SomeOtherObject()
	return x + releaseExternallyVisible.x
	}

	readwrite

	function has side effects and the optimizer can't assume anything.

	Optimize semantics attribute
	~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

	The optimize attribute adds function-specific directives to the optimizer.

	The optimize attribute supports the following tags:

	sil.specialize.generic.never

	The sil optimizer should never create generic specializations of this function.

	optimize.sil.specialize.generic.partial.never

	The sil optimizer should never create generic partial specializations of this function.

	Availability checks
	~~~~~~~~~~~~~~~~~~~

	The availability attribute is used for functions which implement the ``if #available``
	guards.

	The availability attribute supports the following tags:

	availability.osversion(major: Builtin.Word, minor: Builtin.Word, patch: Builtin.Word) -> Builtin.Int1

	Returns true if the OS version matches the parameters.