docs/BranchWeightMetadata.rst - llvm-project/llvm - Git at Google

 ===========================
 LLVM Branch Weight Metadata
 ===========================

 .. contents::
    :local:

 Introduction
 ============

 Branch Weight Metadata represents branch weights as its likeliness to be taken
 (see :doc:`BlockFrequencyTerminology`). Metadata is assigned to an
 ``Instruction`` that is a terminator as a ``MDNode`` of the ``MD_prof`` kind.
 The first operator is always a ``MDString`` node with the string
 "branch_weights".  Number of operators depends on the terminator type.

 Branch weights might be fetch from the profiling file, or generated based on
 `__builtin_expect`_ and `__builtin_expect_with_probability`_ instruction.

 All weights are represented as an unsigned 32-bit values, where higher value
 indicates greater chance to be taken.

 Supported Instructions
 ======================

 ``BranchInst``
 ^^^^^^^^^^^^^^

 Metadata is only assigned to the conditional branches. There are two extra
 operands for the true and the false branch.

 .. code-block:: none

   !0 = metadata !{
     metadata !"branch_weights",
     i32 <TRUE_BRANCH_WEIGHT>,
     i32 <FALSE_BRANCH_WEIGHT>
   }

 ``SwitchInst``
 ^^^^^^^^^^^^^^

 Branch weights are assigned to every case (including the ``default`` case which
 is always case #0).

 .. code-block:: none

   !0 = metadata !{
     metadata !"branch_weights",
     i32 <DEFAULT_BRANCH_WEIGHT>
     [ , i32 <CASE_BRANCH_WEIGHT> ... ]
   }

 ``IndirectBrInst``
 ^^^^^^^^^^^^^^^^^^

 Branch weights are assigned to every destination.

 .. code-block:: none

   !0 = metadata !{
     metadata !"branch_weights",
     i32 <LABEL_BRANCH_WEIGHT>
     [ , i32 <LABEL_BRANCH_WEIGHT> ... ]
   }

 ``CallInst``
 ^^^^^^^^^^^^^^^^^^

 Calls may have branch weight metadata, containing the execution count of
 the call. It is currently used in SamplePGO mode only, to augment the
 block and entry counts which may not be accurate with sampling.

 .. code-block:: none

   !0 = metadata !{
     metadata !"branch_weights",
     i32 <CALL_BRANCH_WEIGHT>
   }

 ``InvokeInst``
 ^^^^^^^^^^^^^^^^^^

 Invoke instruction may have branch weight metadata with one or two weights.
 The second weight is optional and corresponds to the unwind branch.
 If only one weight is set then it contains the execution count of the call
 and used in SamplePGO mode only as described for the call instruction. If both
 weights are specified then the second weight contains count of unwind branch
 taken and the first weights contains the execution count of the call minus
 the count of unwind branch taken. Both weights specified are used to calculate
 BranchProbability as for BranchInst and for SamplePGO the sum of both weights
 is used.

 .. code-block:: none

   !0 = metadata !{
     metadata !"branch_weights",
     i32 <INVOKE_NORMAL_WEIGHT>
     [ , i32 <INVOKE_UNWIND_WEIGHT> ]
   }

 Other
 ^^^^^

 Other terminator instructions are not allowed to contain Branch Weight Metadata.

 .. _\__builtin_expect:

 Built-in ``expect`` Instructions
 ================================

 ``__builtin_expect(long exp, long c)`` instruction provides branch prediction
 information. The return value is the value of ``exp``.

 It is especially useful in conditional statements. Currently Clang supports two
 conditional statements:

 ``if`` statement
 ^^^^^^^^^^^^^^^^

 The ``exp`` parameter is the condition. The ``c`` parameter is the expected
 comparison value. If it is equal to 1 (true), the condition is likely to be
 true, in other case condition is likely to be false. For example:

 .. code-block:: c++

   if (__builtin_expect(x > 0, 1)) {
     // This block is likely to be taken.
   }

 ``switch`` statement
 ^^^^^^^^^^^^^^^^^^^^

 The ``exp`` parameter is the value. The ``c`` parameter is the expected
 value. If the expected value doesn't show on the cases list, the ``default``
 case is assumed to be likely taken.

 .. code-block:: c++

   switch (__builtin_expect(x, 5)) {
   default: break;
   case 0:  // ...
   case 3:  // ...
   case 5:  // This case is likely to be taken.
   }

 .. _\__builtin_expect_with_probability:

 Built-in ``expect.with.probability`` Instruction
 ================================================

 ``__builtin_expect_with_probability(long exp, long c, double probability)`` has
 the same semantics as ``__builtin_expect``, but the caller provides the
 probability that ``exp == c``. The last argument ``probability`` must be
 constant floating-point expression and be in the range [0.0, 1.0] inclusive.
 The usage is also similar as ``__builtin_expect``, for example:

 ``if`` statement
 ^^^^^^^^^^^^^^^^

 If the expect comparison value ``c`` is equal to 1(true), and probability
 value ``probability`` is set to 0.8, that means the probability of condition
 to be true is 80% while that of false is 20%.

 .. code-block:: c++

   if (__builtin_expect_with_probability(x > 0, 1, 0.8)) {
     // This block is likely to be taken with probability 80%.
   }

 ``switch`` statement
 ^^^^^^^^^^^^^^^^^^^^

 This is basically the same as ``switch`` statement in ``__builtin_expect``.
 The probability that ``exp`` is equal to the expect value is given in
 the third argument ``probability``, while the probability of other value is
 the average of remaining probability(``1.0 - probability``). For example:

 .. code-block:: c++

   switch (__builtin_expect_with_probability(x, 5, 0.7)) {
   default: break;  // Take this case with probability 10%
   case 0:  break;  // Take this case with probability 10%
   case 3:  break;  // Take this case with probability 10%
   case 5:  break;  // This case is likely to be taken with probability 70%
   }

 CFG Modifications
 =================

 Branch Weight Metatada is not proof against CFG changes. If terminator operands'
 are changed some action should be taken. In other case some misoptimizations may
 occur due to incorrect branch prediction information.

 Function Entry Counts
 =====================

 To allow comparing different functions during inter-procedural analysis and
 optimization, ``MD_prof`` nodes can also be assigned to a function definition.
 The first operand is a string indicating the name of the associated counter.

 Currently, one counter is supported: "function_entry_count". The second operand
 is a 64-bit counter that indicates the number of times that this function was
 invoked (in the case of instrumentation-based profiles). In the case of
 sampling-based profiles, this operand is an approximation of how many times
 the function was invoked.

 For example, in the code below, the instrumentation for function foo()
 indicates that it was called 2,590 times at runtime.

 .. code-block:: llvm

   define i32 @foo() !prof !1 {
     ret i32 0
   }
   !1 = !{!"function_entry_count", i64 2590}

 If "function_entry_count" has more than 2 operands, the later operands are
 the GUID of the functions that needs to be imported by ThinLTO. This is only
 set by sampling based profile. It is needed because the sampling based profile
 was collected on a binary that had already imported and inlined these functions,
 and we need to ensure the IR matches in the ThinLTO backends for profile
 annotation. The reason why we cannot annotate this on the callsite is that it
 can only goes down 1 level in the call chain. For the cases where
 foo_in_a_cc()->bar_in_b_cc()->baz_in_c_cc(), we will need to go down 2 levels
 in the call chain to import both bar_in_b_cc and baz_in_c_cc.
	===========================
	LLVM Branch Weight Metadata
	===========================

	.. contents::
	:local:

	Introduction
	============

	Branch Weight Metadata represents branch weights as its likeliness to be taken
	(see :doc:`BlockFrequencyTerminology`). Metadata is assigned to an
	``Instruction`` that is a terminator as a ``MDNode`` of the ``MD_prof`` kind.
	The first operator is always a ``MDString`` node with the string
	"branch_weights". Number of operators depends on the terminator type.

	Branch weights might be fetch from the profiling file, or generated based on
	`__builtin_expect`_ and `__builtin_expect_with_probability`_ instruction.

	All weights are represented as an unsigned 32-bit values, where higher value
	indicates greater chance to be taken.

	Supported Instructions
	======================

	``BranchInst``
	^^^^^^^^^^^^^^

	Metadata is only assigned to the conditional branches. There are two extra
	operands for the true and the false branch.

	.. code-block:: none

	!0 = metadata !{
	metadata !"branch_weights",
	i32 <TRUE_BRANCH_WEIGHT>,
	i32 <FALSE_BRANCH_WEIGHT>
	}

	``SwitchInst``
	^^^^^^^^^^^^^^

	Branch weights are assigned to every case (including the ``default`` case which
	is always case #0).

	.. code-block:: none

	!0 = metadata !{
	metadata !"branch_weights",
	i32 <DEFAULT_BRANCH_WEIGHT>
	[ , i32 <CASE_BRANCH_WEIGHT> ... ]
	}

	``IndirectBrInst``
	^^^^^^^^^^^^^^^^^^

	Branch weights are assigned to every destination.

	.. code-block:: none

	!0 = metadata !{
	metadata !"branch_weights",
	i32 <LABEL_BRANCH_WEIGHT>
	[ , i32 <LABEL_BRANCH_WEIGHT> ... ]
	}

	``CallInst``
	^^^^^^^^^^^^^^^^^^

	Calls may have branch weight metadata, containing the execution count of
	the call. It is currently used in SamplePGO mode only, to augment the
	block and entry counts which may not be accurate with sampling.

	.. code-block:: none

	!0 = metadata !{
	metadata !"branch_weights",
	i32 <CALL_BRANCH_WEIGHT>
	}

	``InvokeInst``
	^^^^^^^^^^^^^^^^^^

	Invoke instruction may have branch weight metadata with one or two weights.
	The second weight is optional and corresponds to the unwind branch.
	If only one weight is set then it contains the execution count of the call
	and used in SamplePGO mode only as described for the call instruction. If both
	weights are specified then the second weight contains count of unwind branch
	taken and the first weights contains the execution count of the call minus
	the count of unwind branch taken. Both weights specified are used to calculate
	BranchProbability as for BranchInst and for SamplePGO the sum of both weights
	is used.

	.. code-block:: none

	!0 = metadata !{
	metadata !"branch_weights",
	i32 <INVOKE_NORMAL_WEIGHT>
	[ , i32 <INVOKE_UNWIND_WEIGHT> ]
	}

	Other
	^^^^^

	Other terminator instructions are not allowed to contain Branch Weight Metadata.

	.. _\__builtin_expect:

	Built-in ``expect`` Instructions
	================================

	``__builtin_expect(long exp, long c)`` instruction provides branch prediction
	information. The return value is the value of ``exp``.

	It is especially useful in conditional statements. Currently Clang supports two
	conditional statements:

	``if`` statement
	^^^^^^^^^^^^^^^^

	The ``exp`` parameter is the condition. The ``c`` parameter is the expected
	comparison value. If it is equal to 1 (true), the condition is likely to be
	true, in other case condition is likely to be false. For example:

	.. code-block:: c++

	if (__builtin_expect(x > 0, 1)) {
	// This block is likely to be taken.
	}

	``switch`` statement
	^^^^^^^^^^^^^^^^^^^^

	The ``exp`` parameter is the value. The ``c`` parameter is the expected
	value. If the expected value doesn't show on the cases list, the ``default``
	case is assumed to be likely taken.

	.. code-block:: c++

	switch (__builtin_expect(x, 5)) {
	default: break;
	case 0: // ...
	case 3: // ...
	case 5: // This case is likely to be taken.
	}

	.. _\__builtin_expect_with_probability:

	Built-in ``expect.with.probability`` Instruction
	================================================

	``__builtin_expect_with_probability(long exp, long c, double probability)`` has
	the same semantics as ``__builtin_expect``, but the caller provides the
	probability that ``exp == c``. The last argument ``probability`` must be
	constant floating-point expression and be in the range [0.0, 1.0] inclusive.
	The usage is also similar as ``__builtin_expect``, for example:

	``if`` statement
	^^^^^^^^^^^^^^^^

	If the expect comparison value ``c`` is equal to 1(true), and probability
	value ``probability`` is set to 0.8, that means the probability of condition
	to be true is 80% while that of false is 20%.

	.. code-block:: c++

	if (__builtin_expect_with_probability(x > 0, 1, 0.8)) {
	// This block is likely to be taken with probability 80%.
	}

	``switch`` statement
	^^^^^^^^^^^^^^^^^^^^

	This is basically the same as ``switch`` statement in ``__builtin_expect``.
	The probability that ``exp`` is equal to the expect value is given in
	the third argument ``probability``, while the probability of other value is
	the average of remaining probability(``1.0 - probability``). For example:

	.. code-block:: c++

	switch (__builtin_expect_with_probability(x, 5, 0.7)) {
	default: break; // Take this case with probability 10%
	case 0: break; // Take this case with probability 10%
	case 3: break; // Take this case with probability 10%
	case 5: break; // This case is likely to be taken with probability 70%
	}

	CFG Modifications
	=================

	Branch Weight Metatada is not proof against CFG changes. If terminator operands'
	are changed some action should be taken. In other case some misoptimizations may
	occur due to incorrect branch prediction information.

	Function Entry Counts
	=====================

	To allow comparing different functions during inter-procedural analysis and
	optimization, ``MD_prof`` nodes can also be assigned to a function definition.
	The first operand is a string indicating the name of the associated counter.

	Currently, one counter is supported: "function_entry_count". The second operand
	is a 64-bit counter that indicates the number of times that this function was
	invoked (in the case of instrumentation-based profiles). In the case of
	sampling-based profiles, this operand is an approximation of how many times
	the function was invoked.

	For example, in the code below, the instrumentation for function foo()
	indicates that it was called 2,590 times at runtime.

	.. code-block:: llvm

	define i32 @foo() !prof !1 {
	ret i32 0
	}
	!1 = !{!"function_entry_count", i64 2590}

	If "function_entry_count" has more than 2 operands, the later operands are
	the GUID of the functions that needs to be imported by ThinLTO. This is only
	set by sampling based profile. It is needed because the sampling based profile
	was collected on a binary that had already imported and inlined these functions,
	and we need to ensure the IR matches in the ThinLTO backends for profile
	annotation. The reason why we cannot annotate this on the callsite is that it
	can only goes down 1 level in the call chain. For the cases where
	foo_in_a_cc()->bar_in_b_cc()->baz_in_c_cc(), we will need to go down 2 levels
	in the call chain to import both bar_in_b_cc and baz_in_c_cc.