1 @c Copyright (c) 2004, 2005 Free Software Foundation, Inc.
2 @c Free Software Foundation, Inc.
3 @c This is part of the GCC manual.
4 @c For copying conditions, see the file gcc.texi.
6 @c ---------------------------------------------------------------------
8 @c ---------------------------------------------------------------------
11 @chapter Analysis and Optimization of GIMPLE Trees
13 @cindex Optimization infrastructure for GIMPLE
15 GCC uses three main intermediate languages to represent the program
16 during compilation: GENERIC, GIMPLE and RTL@. GENERIC is a
17 language-independent representation generated by each front end. It
18 is used to serve as an interface between the parser and optimizer.
19 GENERIC is a common representation that is able to represent programs
20 written in all the languages supported by GCC@.
22 GIMPLE and RTL are used to optimize the program. GIMPLE is used for
23 target and language independent optimizations (e.g., inlining,
24 constant propagation, tail call elimination, redundancy elimination,
25 etc). Much like GENERIC, GIMPLE is a language independent, tree based
26 representation. However, it differs from GENERIC in that the GIMPLE
27 grammar is more restrictive: expressions contain no more than 3
28 operands (except function calls), it has no control flow structures
29 and expressions with side-effects are only allowed on the right hand
30 side of assignments. See the chapter describing GENERIC and GIMPLE
33 This chapter describes the data structures and functions used in the
34 GIMPLE optimizers (also known as ``tree optimizers'' or ``middle
35 end''). In particular, it focuses on all the macros, data structures,
36 functions and programming constructs needed to implement optimization
40 * GENERIC:: A high-level language-independent representation.
41 * GIMPLE:: A lower-level factored tree representation.
42 * Annotations:: Attributes for statements and variables.
43 * Statement Operands:: Variables referenced by GIMPLE statements.
44 * SSA:: Static Single Assignment representation.
45 * Alias analysis:: Representing aliased loads and stores.
52 The purpose of GENERIC is simply to provide a language-independent way of
53 representing an entire function in trees. To this end, it was necessary to
54 add a few new tree codes to the back end, but most everything was already
55 there. If you can express it with the codes in @code{gcc/tree.def}, it's
58 Early on, there was a great deal of debate about how to think about
59 statements in a tree IL@. In GENERIC, a statement is defined as any
60 expression whose value, if any, is ignored. A statement will always
61 have @code{TREE_SIDE_EFFECTS} set (or it will be discarded), but a
62 non-statement expression may also have side effects. A
63 @code{CALL_EXPR}, for instance.
65 It would be possible for some local optimizations to work on the
66 GENERIC form of a function; indeed, the adapted tree inliner works
67 fine on GENERIC, but the current compiler performs inlining after
68 lowering to GIMPLE (a restricted form described in the next section).
69 Indeed, currently the frontends perform this lowering before handing
70 off to @code{tree_rest_of_compilation}, but this seems inelegant.
72 If necessary, a front end can use some language-dependent tree codes
73 in its GENERIC representation, so long as it provides a hook for
74 converting them to GIMPLE and doesn't expect them to work with any
75 (hypothetical) optimizers that run before the conversion to GIMPLE@.
76 The intermediate representation used while parsing C and C++ looks
77 very little like GENERIC, but the C and C++ gimplifier hooks are
78 perfectly happy to take it as input and spit out GIMPLE@.
84 GIMPLE is a simplified subset of GENERIC for use in optimization. The
85 particular subset chosen (and the name) was heavily influenced by the
86 SIMPLE IL used by the McCAT compiler project at McGill University,
87 though we have made some different choices. For one thing, SIMPLE
88 doesn't support @code{goto}; a production compiler can't afford that
91 GIMPLE retains much of the structure of the parse trees: lexical
92 scopes are represented as containers, rather than markers. However,
93 expressions are broken down into a 3-address form, using temporary
94 variables to hold intermediate values. Also, control structures are
97 In GIMPLE no container node is ever used for its value; if a
98 @code{COND_EXPR} or @code{BIND_EXPR} has a value, it is stored into a
99 temporary within the controlled blocks, and that temporary is used in
100 place of the container.
102 The compiler pass which lowers GENERIC to GIMPLE is referred to as the
103 @samp{gimplifier}. The gimplifier works recursively, replacing complex
104 statements with sequences of simple statements.
106 @c Currently, the only way to
107 @c tell whether or not an expression is in GIMPLE form is by recursively
108 @c examining it; in the future there will probably be a flag to help avoid
109 @c redundant work. FIXME FIXME
114 * GIMPLE Expressions::
117 * Rough GIMPLE Grammar::
121 @subsection Interfaces
122 @cindex gimplification
124 The tree representation of a function is stored in
125 @code{DECL_SAVED_TREE}. It is lowered to GIMPLE by a call to
126 @code{gimplify_function_tree}.
128 If a front end wants to include language-specific tree codes in the tree
129 representation which it provides to the back end, it must provide a
130 definition of @code{LANG_HOOKS_GIMPLIFY_EXPR} which knows how to
131 convert the front end trees to GIMPLE@. Usually such a hook will involve
132 much of the same code for expanding front end trees to RTL@. This function
133 can return fully lowered GIMPLE, or it can return GENERIC trees and let the
134 main gimplifier lower them the rest of the way; this is often simpler.
136 The C and C++ front ends currently convert directly from front end
137 trees to GIMPLE, and hand that off to the back end rather than first
138 converting to GENERIC@. Their gimplifier hooks know about all the
139 @code{_STMT} nodes and how to convert them to GENERIC forms. There
140 was some work done on a genericization pass which would run first, but
141 the existence of @code{STMT_EXPR} meant that in order to convert all
142 of the C statements into GENERIC equivalents would involve walking the
143 entire tree anyway, so it was simpler to lower all the way. This
144 might change in the future if someone writes an optimization pass
145 which would work better with higher-level trees, but currently the
146 optimizers all expect GIMPLE@.
148 A front end which wants to use the tree optimizers (and already has
149 some sort of whole-function tree representation) only needs to provide
150 a definition of @code{LANG_HOOKS_GIMPLIFY_EXPR}, call
151 @code{gimplify_function_tree} to lower to GIMPLE, and then hand off to
152 @code{tree_rest_of_compilation} to compile and output the function.
154 You can tell the compiler to dump a C-like representation of the GIMPLE
155 form with the flag @option{-fdump-tree-gimple}.
158 @subsection Temporaries
161 When gimplification encounters a subexpression which is too complex, it
162 creates a new temporary variable to hold the value of the subexpression,
163 and adds a new statement to initialize it before the current statement.
164 These special temporaries are known as @samp{expression temporaries}, and are
165 allocated using @code{get_formal_tmp_var}. The compiler tries to
166 always evaluate identical expressions into the same temporary, to simplify
167 elimination of redundant calculations.
169 We can only use expression temporaries when we know that it will not be
170 reevaluated before its value is used, and that it will not be otherwise
171 modified@footnote{These restrictions are derived from those in Morgan 4.8.}.
172 Other temporaries can be allocated using
173 @code{get_initialized_tmp_var} or @code{create_tmp_var}.
175 Currently, an expression like @code{a = b + 5} is not reduced any
176 further. We tried converting it to something like
181 but this bloated the representation for minimal benefit. However, a
182 variable which must live in memory cannot appear in an expression; its
183 value is explicitly loaded into a temporary first. Similarly, storing
184 the value of an expression to a memory variable goes through a
187 @node GIMPLE Expressions
188 @subsection Expressions
189 @cindex GIMPLE Expressions
191 In general, expressions in GIMPLE consist of an operation and the
192 appropriate number of simple operands; these operands must either be a
193 GIMPLE rvalue (@code{is_gimple_val}), i.e.@: a constant or a register
194 variable. More complex operands are factored out into temporaries, so
205 The same rule holds for arguments to a @code{CALL_EXPR}.
207 The target of an assignment is usually a variable, but can also be an
208 @code{INDIRECT_REF} or a compound lvalue as described below.
211 * Compound Expressions::
213 * Conditional Expressions::
214 * Logical Operators::
217 @node Compound Expressions
218 @subsubsection Compound Expressions
219 @cindex Compound Expressions
221 The left-hand side of a C comma expression is simply moved into a separate
224 @node Compound Lvalues
225 @subsubsection Compound Lvalues
226 @cindex Compound Lvalues
228 Currently compound lvalues involving array and structure field references
229 are not broken down; an expression like @code{a.b[2] = 42} is not reduced
230 any further (though complex array subscripts are). This restriction is a
231 workaround for limitations in later optimizers; if we were to convert this
239 alias analysis would not remember that the reference to @code{T1[2]} came
240 by way of @code{a.b}, so it would think that the assignment could alias
241 another member of @code{a}; this broke @code{struct-alias-1.c}. Future
242 optimizer improvements may make this limitation unnecessary.
244 @node Conditional Expressions
245 @subsubsection Conditional Expressions
246 @cindex Conditional Expressions
248 A C @code{?:} expression is converted into an @code{if} statement with
249 each branch assigning to the same temporary. So,
263 Tree level if-conversion pass re-introduces @code{?:} expression, if appropriate.
264 It is used to vectorize loops with conditions using vector conditional operations.
266 Note that in GIMPLE, @code{if} statements are also represented using
267 @code{COND_EXPR}, as described below.
269 @node Logical Operators
270 @subsubsection Logical Operators
271 @cindex Logical Operators
273 Except when they appear in the condition operand of a @code{COND_EXPR},
274 logical `and' and `or' operators are simplified as follows:
275 @code{a = b && c} becomes
284 Note that @code{T1} in this example cannot be an expression temporary,
285 because it has two different assignments.
288 @subsection Statements
291 Most statements will be assignment statements, represented by
292 @code{MODIFY_EXPR}. A @code{CALL_EXPR} whose value is ignored can
293 also be a statement. No other C expressions can appear at statement level;
294 a reference to a volatile object is converted into a @code{MODIFY_EXPR}.
295 In GIMPLE form, type of @code{MODIFY_EXPR} is not meaningful. Instead, use type
298 There are also several varieties of complex statements.
302 * Statement Sequences::
305 * Selection Statements::
308 * GIMPLE Exception Handling::
312 @subsubsection Blocks
315 Block scopes and the variables they declare in GENERIC and GIMPLE are
316 expressed using the @code{BIND_EXPR} code, which in previous versions of
317 GCC was primarily used for the C statement-expression extension.
319 Variables in a block are collected into @code{BIND_EXPR_VARS} in
320 declaration order. Any runtime initialization is moved out of
321 @code{DECL_INITIAL} and into a statement in the controlled block. When
322 gimplifying from C or C++, this initialization replaces the
325 Variable-length arrays (VLAs) complicate this process, as their size often
326 refers to variables initialized earlier in the block. To handle this, we
327 currently split the block at that point, and move the VLA into a new, inner
328 @code{BIND_EXPR}. This strategy may change in the future.
330 @code{DECL_SAVED_TREE} for a GIMPLE function will always be a
331 @code{BIND_EXPR} which contains declarations for the temporary variables
332 used in the function.
334 A C++ program will usually contain more @code{BIND_EXPR}s than there are
335 syntactic blocks in the source code, since several C++ constructs have
336 implicit scopes associated with them. On the other hand, although the C++
337 front end uses pseudo-scopes to handle cleanups for objects with
338 destructors, these don't translate into the GIMPLE form; multiple
339 declarations at the same level use the same @code{BIND_EXPR}.
341 @node Statement Sequences
342 @subsubsection Statement Sequences
343 @cindex Statement Sequences
345 Multiple statements at the same nesting level are collected into a
346 @code{STATEMENT_LIST}. Statement lists are modified and traversed
347 using the interface in @samp{tree-iterator.h}.
349 @node Empty Statements
350 @subsubsection Empty Statements
351 @cindex Empty Statements
353 Whenever possible, statements with no effect are discarded. But if they
354 are nested within another construct which cannot be discarded for some
355 reason, they are instead replaced with an empty statement, generated by
356 @code{build_empty_stmt}. Initially, all empty statements were shared,
357 after the pattern of the Java front end, but this caused a lot of trouble in
360 An empty statement is represented as @code{(void)0}.
366 At one time loops were expressed in GIMPLE using @code{LOOP_EXPR}, but
367 now they are lowered to explicit gotos.
369 @node Selection Statements
370 @subsubsection Selection Statements
371 @cindex Selection Statements
373 A simple selection statement, such as the C @code{if} statement, is
374 expressed in GIMPLE using a void @code{COND_EXPR}. If only one branch is
375 used, the other is filled with an empty statement.
377 Normally, the condition expression is reduced to a simple comparison. If
378 it is a shortcut (@code{&&} or @code{||}) expression, however, we try to
379 break up the @code{if} into multiple @code{if}s so that the implied shortcut
380 is taken directly, much like the transformation done by @code{do_jump} in
383 A @code{SWITCH_EXPR} in GIMPLE contains the condition and a
384 @code{TREE_VEC} of @code{CASE_LABEL_EXPR}s describing the case values
385 and corresponding @code{LABEL_DECL}s to jump to. The body of the
386 @code{switch} is moved after the @code{SWITCH_EXPR}.
392 Other jumps are expressed by either @code{GOTO_EXPR} or @code{RETURN_EXPR}.
394 The operand of a @code{GOTO_EXPR} must be either a label or a variable
395 containing the address to jump to.
397 The operand of a @code{RETURN_EXPR} is either @code{NULL_TREE} or a
398 @code{MODIFY_EXPR} which sets the return value. It would be nice to
399 move the @code{MODIFY_EXPR} into a separate statement, but the special
400 return semantics in @code{expand_return} make that difficult. It may
401 still happen in the future, perhaps by moving most of that logic into
402 @code{expand_assignment}.
405 @subsubsection Cleanups
408 Destructors for local C++ objects and similar dynamic cleanups are
409 represented in GIMPLE by a @code{TRY_FINALLY_EXPR}.
410 @code{TRY_FINALLY_EXPR} has two operands, both of which are a sequence
411 of statements to execute. The first sequence is executed. When it
412 completes the second sequence is executed.
414 The first sequence may complete in the following ways:
418 @item Execute the last statement in the sequence and fall off the
421 @item Execute a goto statement (@code{GOTO_EXPR}) to an ordinary
422 label outside the sequence.
424 @item Execute a return statement (@code{RETURN_EXPR}).
426 @item Throw an exception. This is currently not explicitly represented in
431 The second sequence is not executed if the first sequence completes by
432 calling @code{setjmp} or @code{exit} or any other function that does
433 not return. The second sequence is also not executed if the first
434 sequence completes via a non-local goto or a computed goto (in general
435 the compiler does not know whether such a goto statement exits the
436 first sequence or not, so we assume that it doesn't).
438 After the second sequence is executed, if it completes normally by
439 falling off the end, execution continues wherever the first sequence
440 would have continued, by falling off the end, or doing a goto, etc.
442 @code{TRY_FINALLY_EXPR} complicates the flow graph, since the cleanup
443 needs to appear on every edge out of the controlled block; this
444 reduces the freedom to move code across these edges. Therefore, the
445 EH lowering pass which runs before most of the optimization passes
446 eliminates these expressions by explicitly adding the cleanup to each
447 edge. Rethrowing the exception is represented using @code{RESX_EXPR}.
450 @node GIMPLE Exception Handling
451 @subsubsection Exception Handling
452 @cindex GIMPLE Exception Handling
454 Other exception handling constructs are represented using
455 @code{TRY_CATCH_EXPR}. @code{TRY_CATCH_EXPR} has two operands. The
456 first operand is a sequence of statements to execute. If executing
457 these statements does not throw an exception, then the second operand
458 is ignored. Otherwise, if an exception is thrown, then the second
459 operand of the @code{TRY_CATCH_EXPR} is checked. The second operand
460 may have the following forms:
464 @item A sequence of statements to execute. When an exception occurs,
465 these statements are executed, and then the exception is rethrown.
467 @item A sequence of @code{CATCH_EXPR} expressions. Each @code{CATCH_EXPR}
468 has a list of applicable exception types and handler code. If the
469 thrown exception matches one of the caught types, the associated
470 handler code is executed. If the handler code falls off the bottom,
471 execution continues after the original @code{TRY_CATCH_EXPR}.
473 @item An @code{EH_FILTER_EXPR} expression. This has a list of
474 permitted exception types, and code to handle a match failure. If the
475 thrown exception does not match one of the allowed types, the
476 associated match failure code is executed. If the thrown exception
477 does match, it continues unwinding the stack looking for the next
482 Currently throwing an exception is not directly represented in GIMPLE,
483 since it is implemented by calling a function. At some point in the future
484 we will want to add some way to express that the call will throw an
485 exception of a known type.
487 Just before running the optimizers, the compiler lowers the high-level
488 EH constructs above into a set of @samp{goto}s, magic labels, and EH
489 regions. Continuing to unwind at the end of a cleanup is represented
490 with a @code{RESX_EXPR}.
493 @subsection GIMPLE Example
494 @cindex GIMPLE Example
497 struct A @{ A(); ~A(); @};
504 int j = (--i, i ? 0 : 1);
506 for (int x = 42; x > 0; --x)
573 @node Rough GIMPLE Grammar
574 @subsection Rough GIMPLE Grammar
575 @cindex Rough GIMPLE Grammar
578 function : FUNCTION_DECL
579 DECL_SAVED_TREE -> compound-stmt
581 compound-stmt: STATEMENT_LIST
596 BIND_EXPR_VARS -> chain of DECLs
597 BIND_EXPR_BLOCK -> BLOCK
598 BIND_EXPR_BODY -> compound-stmt
605 switch-stmt : SWITCH_EXPR
608 op2 -> TREE_VEC of CASE_LABEL_EXPRs
609 The CASE_LABEL_EXPRs are sorted by CASE_LOW,
612 goto-stmt : GOTO_EXPR
613 op0 -> LABEL_DECL | val
615 return-stmt : RETURN_EXPR
624 resx-stmt : RESX_EXPR
626 label-stmt : LABEL_EXPR
629 try-stmt : TRY_CATCH_EXPR
640 catch-seq : STATEMENT_LIST
641 members -> CATCH_EXPR
643 modify-stmt : MODIFY_EXPR
647 call-stmt : CALL_EXPR
648 op0 -> val | OBJ_TYPE_REF
651 call-arg-list: TREE_LIST
652 members -> lhs | CONST
657 addressable : addr-expr-arg
660 with-size-arg: addressable
663 indirectref : INDIRECT_REF
675 bitfieldref : BIT_FIELD_REF
680 compref : inner-compref
692 inner-compref: min-lval
741 The optimizers need to associate attributes with statements and
742 variables during the optimization process. For instance, we need to
743 know what basic block a statement belongs to or whether a variable
744 has aliases. All these attributes are stored in data structures
745 called annotations which are then linked to the field @code{ann} in
746 @code{struct tree_common}.
748 Presently, we define annotations for statements (@code{stmt_ann_t}),
749 variables (@code{var_ann_t}) and SSA names (@code{ssa_name_ann_t}).
750 Annotations are defined and documented in @file{tree-flow.h}.
753 @node Statement Operands
754 @section Statement Operands
756 @cindex virtual operands
757 @cindex real operands
760 Almost every GIMPLE statement will contain a reference to a variable
761 or memory location. Since statements come in different shapes and
762 sizes, their operands are going to be located at various spots inside
763 the statement's tree. To facilitate access to the statement's
764 operands, they are organized into lists associated inside each
765 statement's annotation. Each element in an operand list is a pointer
766 to a @code{VAR_DECL}, @code{PARM_DECL} or @code{SSA_NAME} tree node.
767 This provides a very convenient way of examining and replacing
770 Data flow analysis and optimization is done on all tree nodes
771 representing variables. Any node for which @code{SSA_VAR_P} returns
772 nonzero is considered when scanning statement operands. However, not
773 all @code{SSA_VAR_P} variables are processed in the same way. For the
774 purposes of optimization, we need to distinguish between references to
775 local scalar variables and references to globals, statics, structures,
776 arrays, aliased variables, etc. The reason is simple, the compiler
777 can gather complete data flow information for a local scalar. On the
778 other hand, a global variable may be modified by a function call, it
779 may not be possible to keep track of all the elements of an array or
780 the fields of a structure, etc.
782 The operand scanner gathers two kinds of operands: @dfn{real} and
783 @dfn{virtual}. An operand for which @code{is_gimple_reg} returns true
784 is considered real, otherwise it is a virtual operand. We also
785 distinguish between uses and definitions. An operand is used if its
786 value is loaded by the statement (e.g., the operand at the RHS of an
787 assignment). If the statement assigns a new value to the operand, the
788 operand is considered a definition (e.g., the operand at the LHS of
791 Virtual and real operands also have very different data flow
792 properties. Real operands are unambiguous references to the
793 full object that they represent. For instance, given
802 Since @code{a} and @code{b} are non-aliased locals, the statement
803 @code{a = b} will have one real definition and one real use because
804 variable @code{b} is completely modified with the contents of
805 variable @code{a}. Real definition are also known as @dfn{killing
806 definitions}. Similarly, the use of @code{a} reads all its bits.
808 In contrast, virtual operands are used with variables that can have
809 a partial or ambiguous reference. This includes structures, arrays,
810 globals, and aliased variables. In these cases, we have two types of
811 definitions. For globals, structures, and arrays, we can determine from
812 a statement whether a variable of these types has a killing definition.
813 If the variable does, then the statement is marked as having a
814 @dfn{must definition} of that variable. However, if a statement is only
815 defining a part of the variable (i.e.@: a field in a structure), or if we
816 know that a statement might define the variable but we cannot say for sure,
817 then we mark that statement as having a @dfn{may definition}. For
833 The assignment @code{*p = 5} may be a definition of @code{a} or
834 @code{b}. If we cannot determine statically where @code{p} is
835 pointing to at the time of the store operation, we create virtual
836 definitions to mark that statement as a potential definition site for
837 @code{a} and @code{b}. Memory loads are similarly marked with virtual
838 use operands. Virtual operands are shown in tree dumps right before
839 the statement that contains them. To request a tree dump with virtual
840 operands, use the @option{-vops} option to @option{-fdump-tree}:
860 Notice that @code{V_MAY_DEF} operands have two copies of the referenced
861 variable. This indicates that this is not a killing definition of
862 that variable. In this case we refer to it as a @dfn{may definition}
863 or @dfn{aliased store}. The presence of the second copy of the
864 variable in the @code{V_MAY_DEF} operand will become important when the
865 function is converted into SSA form. This will be used to link all
866 the non-killing definitions to prevent optimizations from making
867 incorrect assumptions about them.
869 Operands are updated as soon as the statement is finished via a call
870 to @code{update_stmt}. If statement elements are changed via
871 @code{SET_USE} or @code{SET_DEF}, then no further action is required
872 (ie, those macros take care of updating the statement). If changes
873 are made by manipulating the statement's tree directly, then a call
874 must be made to @code{update_stmt} when complete. Calling one of the
875 @code{bsi_insert} routines or @code{bsi_replace} performs an implicit
876 call to @code{update_stmt}.
878 @subsection Operand Iterators And Access Routines
879 @cindex Operand Iterators
880 @cindex Operand Access Routines
882 Operands are collected by @file{tree-ssa-operands.c}. They are stored
883 inside each statement's annotation and can be accessed through either the
884 operand iterators or an access routine.
886 The following access routines are available for examining operands:
889 @item @code{SINGLE_SSA_@{USE,DEF,TREE@}_OPERAND}: These accessors will return
890 NULL unless there is exactly one operand matching the specified flags. If
891 there is exactly one operand, the operand is returned as either a @code{tree},
892 @code{def_operand_p}, or @code{use_operand_p}.
895 tree t = SINGLE_SSA_TREE_OPERAND (stmt, flags);
896 use_operand_p u = SINGLE_SSA_USE_OPERAND (stmt, SSA_ALL_VIRTUAL_USES);
897 def_operand_p d = SINGLE_SSA_DEF_OPERAND (stmt, SSA_OP_ALL_DEFS);
900 @item @code{ZERO_SSA_OPERANDS}: This macro returns true if there are no
901 operands matching the specified flags.
904 if (ZERO_SSA_OPERANDS (stmt, SSA_OP_ALL_VIRTUALS))
908 @item @code{NUM_SSA_OPERANDS}: This macro Returns the number of operands
909 matching 'flags'. This actually executes a loop to perform the count, so
910 only use this if it is really needed.
913 int count = NUM_SSA_OPERANDS (stmt, flags)
918 If you wish to iterate over some or all operands, use the
919 @code{FOR_EACH_SSA_@{USE,DEF,TREE@}_OPERAND} iterator. For example, to print
920 all the operands for a statement:
924 print_ops (tree stmt)
929 FOR_EACH_SSA_TREE_OPERAND (var, stmt, iter, SSA_OP_ALL_OPERANDS)
930 print_generic_expr (stderr, var, TDF_SLIM);
935 How to choose the appropriate iterator:
938 @item Determine whether you are need to see the operand pointers, or just the
939 trees, and choose the appropriate macro:
944 use_operand_p FOR_EACH_SSA_USE_OPERAND
945 def_operand_p FOR_EACH_SSA_DEF_OPERAND
946 tree FOR_EACH_SSA_TREE_OPERAND
949 @item You need to declare a variable of the type you are interested
950 in, and an ssa_op_iter structure which serves as the loop
951 controlling variable.
953 @item Determine which operands you wish to use, and specify the flags of
954 those you are interested in. They are documented in
955 @file{tree-ssa-operands.h}:
958 #define SSA_OP_USE 0x01 /* @r{Real USE operands.} */
959 #define SSA_OP_DEF 0x02 /* @r{Real DEF operands.} */
960 #define SSA_OP_VUSE 0x04 /* @r{VUSE operands.} */
961 #define SSA_OP_VMAYUSE 0x08 /* @r{USE portion of V_MAY_DEFS.} */
962 #define SSA_OP_VMAYDEF 0x10 /* @r{DEF portion of V_MAY_DEFS.} */
963 #define SSA_OP_VMUSTDEF 0x20 /* @r{V_MUST_DEF definitions.} */
965 /* @r{These are commonly grouped operand flags.} */
966 #define SSA_OP_VIRTUAL_USES (SSA_OP_VUSE | SSA_OP_VMAYUSE)
967 #define SSA_OP_VIRTUAL_DEFS (SSA_OP_VMAYDEF | SSA_OP_VMUSTDEF)
968 #define SSA_OP_ALL_USES (SSA_OP_VIRTUAL_USES | SSA_OP_USE)
969 #define SSA_OP_ALL_DEFS (SSA_OP_VIRTUAL_DEFS | SSA_OP_DEF)
970 #define SSA_OP_ALL_OPERANDS (SSA_OP_ALL_USES | SSA_OP_ALL_DEFS)
974 So if you want to look at the use pointers for all the @code{USE} and
975 @code{VUSE} operands, you would do something like:
981 FOR_EACH_SSA_USE_OPERAND (use_p, stmt, iter, (SSA_OP_USE | SSA_OP_VUSE))
983 process_use_ptr (use_p);
987 The @code{TREE} macro is basically the same as the @code{USE} and
988 @code{DEF} macros, only with the use or def dereferenced via
989 @code{USE_FROM_PTR (use_p)} and @code{DEF_FROM_PTR (def_p)}. Since we
990 aren't using operand pointers, use and defs flags can be mixed.
996 FOR_EACH_SSA_TREE_OPERAND (var, stmt, iter, SSA_OP_VUSE | SSA_OP_VMUSTDEF)
998 print_generic_expr (stderr, var, TDF_SLIM);
1002 @code{V_MAY_DEF}s are broken into two flags, one for the
1003 @code{DEF} portion (@code{SSA_OP_VMAYDEF}) and one for the USE portion
1004 (@code{SSA_OP_VMAYUSE}). If all you want to look at are the
1005 @code{V_MAY_DEF}s together, there is a fourth iterator macro for this,
1006 which returns both a def_operand_p and a use_operand_p for each
1007 @code{V_MAY_DEF} in the statement. Note that you don't need any flags for
1011 use_operand_p use_p;
1012 def_operand_p def_p;
1015 FOR_EACH_SSA_MAYDEF_OPERAND (def_p, use_p, stmt, iter)
1021 @code{V_MUST_DEF}s are broken into two flags, one for the
1022 @code{DEF} portion (@code{SSA_OP_VMUSTDEF}) and one for the kill portion
1023 (@code{SSA_OP_VMUSTKILL}). If all you want to look at are the
1024 @code{V_MUST_DEF}s together, there is a fourth iterator macro for this,
1025 which returns both a def_operand_p and a use_operand_p for each
1026 @code{V_MUST_DEF} in the statement. Note that you don't need any flags for
1030 use_operand_p kill_p;
1031 def_operand_p def_p;
1034 FOR_EACH_SSA_MUSTDEF_OPERAND (def_p, kill_p, stmt, iter)
1041 There are many examples in the code as well, as well as the
1042 documentation in @file{tree-ssa-operands.h}.
1044 There are also a couple of variants on the stmt iterators regarding PHI
1047 @code{FOR_EACH_PHI_ARG} Works exactly like
1048 @code{FOR_EACH_SSA_USE_OPERAND}, except it works over @code{PHI} arguments
1049 instead of statement operands.
1052 /* Look at every virtual PHI use. */
1053 FOR_EACH_PHI_ARG (use_p, phi_stmt, iter, SSA_OP_VIRTUAL_USES)
1058 /* Look at every real PHI use. */
1059 FOR_EACH_PHI_ARG (use_p, phi_stmt, iter, SSA_OP_USES)
1062 /* Look at every every PHI use. */
1063 FOR_EACH_PHI_ARG (use_p, phi_stmt, iter, SSA_OP_ALL_USES)
1067 @code{FOR_EACH_PHI_OR_STMT_@{USE,DEF@}} works exactly like
1068 @code{FOR_EACH_SSA_@{USE,DEF@}_OPERAND}, except it will function on
1069 either a statement or a @code{PHI} node. These should be used when it is
1070 appropriate but they are not quite as efficient as the individual
1071 @code{FOR_EACH_PHI} and @code{FOR_EACH_SSA} routines.
1074 FOR_EACH_PHI_OR_STMT_USE (use_operand_p, stmt, iter, flags)
1079 FOR_EACH_PHI_OR_STMT_DEF (def_operand_p, phi, iter, flags)
1085 @subsection Immediate Uses
1086 @cindex Immediate Uses
1088 Immediate use information is now always available. Using the immediate use
1089 iterators, you may examine every use of any @code{SSA_NAME}. For instance,
1090 to change each use of @code{ssa_var} to @code{ssa_var2}:
1093 use_operand_p imm_use_p;
1094 imm_use_iterator iterator;
1097 FOR_EACH_IMM_USE_SAFE (imm_use_p, iterator, ssa_var)
1098 SET_USE (imm_use_p, ssa_var_2);
1101 There are 2 iterators which can be used. @code{FOR_EACH_IMM_USE_FAST} is used
1102 when the immediate uses are not changed, ie. you are looking at the uses, but
1105 If they do get changed, then care must be taken that things are not changed
1106 under the iterators, so use the @code{FOR_EACH_IMM_USE_SAFE} iterator. It
1107 attempts to preserve the sanity of the use list by moving an iterator element
1108 through the use list, preventing insertions and deletions in the list from
1109 resulting in invalid pointers. This is a little slower since it adds a
1110 placeholder element and moves it through the list. This element must be
1111 also be removed if the loop is terminated early. A macro
1112 (@code{BREAK_FROM SAFE_IMM_USE}) is provided for this:
1115 FOR_EACH_IMM_USE_SAFE (use_p, iter, var)
1117 if (var == last_var)
1118 BREAK_FROM_SAFE_IMM_USE (iter);
1120 SET_USE (use_p, var2);
1124 There are checks in @code{verify_ssa} which verify that the immediate use list
1125 is up to date, as well as checking that an optimization didn't break from the
1126 loop without using this macro. It is safe to simply 'break'; from a
1127 @code{FOR_EACH_IMM_USE_FAST} traverse.
1129 Some useful functions and macros:
1131 @item @code{has_zero_uses (ssa_var)} : Returns true if there are no uses of
1133 @item @code{has_single_use (ssa_var)} : Returns true if there is only a
1134 single use of @code{ssa_var}.
1135 @item @code{single_imm_use (ssa_var, use_operand_p *ptr, tree *stmt)} :
1136 Returns true if there is only a single use of @code{ssa_var}, and also returns
1137 the use pointer and statement it occurs in in the second and third parameters.
1138 @item @code{num_imm_uses (ssa_var)} : Returns the number of immediate uses of
1139 @code{ssa_var}. It is better not to use this if possible since it simply
1140 utilizes a loop to count the uses.
1141 @item @code{PHI_ARG_INDEX_FROM_USE (use_p)} : Given a use within a @code{PHI}
1142 node, return the index number for the use. An assert is triggered if the use
1143 isn't located in a @code{PHI} node.
1144 @item @code{USE_STMT (use_p)} : Return the statement a use occurs in.
1147 Note that uses are not put into an immediate use list until their statement is
1148 actually inserted into the instruction stream via a @code{bsi_*} routine.
1150 It is also still possible to utilize lazy updating of statements, but this
1151 should be used only when absolutely required. Both alias analysis and the
1152 dominator optimizations currently do this.
1154 When lazy updating is being used, the immediate use information is out of date
1155 and cannot be used reliably. Lazy updating is achieved by simply marking
1156 statements modified via calls to @code{mark_stmt_modified} instead of
1157 @code{update_stmt}. When lazy updating is no longer required, all the
1158 modified statements must have @code{update_stmt} called in order to bring them
1159 up to date. This must be done before the optimization is finished, or
1160 @code{verify_ssa} will trigger an abort.
1162 This is done with a simple loop over the instruction stream:
1164 block_stmt_iterator bsi;
1168 for (bsi = bsi_start (bb); !bsi_end_p (bsi); bsi_next (&bsi))
1169 update_stmt_if_modified (bsi_stmt (bsi));
1174 @section Static Single Assignment
1176 @cindex static single assignment
1178 Most of the tree optimizers rely on the data flow information provided
1179 by the Static Single Assignment (SSA) form. We implement the SSA form
1180 as described in @cite{R. Cytron, J. Ferrante, B. Rosen, M. Wegman, and
1181 K. Zadeck. Efficiently Computing Static Single Assignment Form and the
1182 Control Dependence Graph. ACM Transactions on Programming Languages
1183 and Systems, 13(4):451-490, October 1991}.
1185 The SSA form is based on the premise that program variables are
1186 assigned in exactly one location in the program. Multiple assignments
1187 to the same variable create new versions of that variable. Naturally,
1188 actual programs are seldom in SSA form initially because variables
1189 tend to be assigned multiple times. The compiler modifies the program
1190 representation so that every time a variable is assigned in the code,
1191 a new version of the variable is created. Different versions of the
1192 same variable are distinguished by subscripting the variable name with
1193 its version number. Variables used in the right-hand side of
1194 expressions are renamed so that their version number matches that of
1195 the most recent assignment.
1197 We represent variable versions using @code{SSA_NAME} nodes. The
1198 renaming process in @file{tree-ssa.c} wraps every real and
1199 virtual operand with an @code{SSA_NAME} node which contains
1200 the version number and the statement that created the
1201 @code{SSA_NAME}. Only definitions and virtual definitions may
1202 create new @code{SSA_NAME} nodes.
1204 Sometimes, flow of control makes it impossible to determine what is the
1205 most recent version of a variable. In these cases, the compiler
1206 inserts an artificial definition for that variable called
1207 @dfn{PHI function} or @dfn{PHI node}. This new definition merges
1208 all the incoming versions of the variable to create a new name
1209 for it. For instance,
1219 # a_4 = PHI <a_1, a_2, a_3>
1223 Since it is not possible to determine which of the three branches
1224 will be taken at runtime, we don't know which of @code{a_1},
1225 @code{a_2} or @code{a_3} to use at the return statement. So, the
1226 SSA renamer creates a new version @code{a_4} which is assigned
1227 the result of ``merging'' @code{a_1}, @code{a_2} and @code{a_3}.
1228 Hence, PHI nodes mean ``one of these operands. I don't know
1231 The following macros can be used to examine PHI nodes
1233 @defmac PHI_RESULT (@var{phi})
1234 Returns the @code{SSA_NAME} created by PHI node @var{phi} (i.e.,
1238 @defmac PHI_NUM_ARGS (@var{phi})
1239 Returns the number of arguments in @var{phi}. This number is exactly
1240 the number of incoming edges to the basic block holding @var{phi}@.
1243 @defmac PHI_ARG_ELT (@var{phi}, @var{i})
1244 Returns a tuple representing the @var{i}th argument of @var{phi}@.
1245 Each element of this tuple contains an @code{SSA_NAME} @var{var} and
1246 the incoming edge through which @var{var} flows.
1249 @defmac PHI_ARG_EDGE (@var{phi}, @var{i})
1250 Returns the incoming edge for the @var{i}th argument of @var{phi}.
1253 @defmac PHI_ARG_DEF (@var{phi}, @var{i})
1254 Returns the @code{SSA_NAME} for the @var{i}th argument of @var{phi}.
1258 @subsection Preserving the SSA form
1260 @cindex preserving SSA form
1261 Some optimization passes make changes to the function that
1262 invalidate the SSA property. This can happen when a pass has
1263 added new symbols or changed the program so that variables that
1264 were previously aliased aren't anymore. Whenever something like this
1265 happens, the affected symbols must be renamed into SSA form again.
1266 Transformations that emit new code or replicate existing statements
1267 will also need to update the SSA form@.
1269 Since GCC implements two different SSA forms for register and virtual
1270 variables, keeping the SSA form up to date depends on whether you are
1271 updating register or virtual names. In both cases, the general idea
1272 behind incremental SSA updates is similar: when new SSA names are
1273 created, they typically are meant to replace other existing names in
1276 For instance, given the following code:
1280 2 x_1 = PHI (0, x_5)
1292 Suppose that we insert new names @code{x_10} and @code{x_11} (lines
1293 @code{4} and @code{8})@.
1297 2 x_1 = PHI (0, x_5)
1311 We want to replace all the uses of @code{x_1} with the new definitions
1312 of @code{x_10} and @code{x_11}. Note that the only uses that should
1313 be replaced are those at lines @code{5}, @code{9} and @code{11}.
1314 Also, the use of @code{x_7} at line @code{9} should @emph{not} be
1315 replaced (this is why we cannot just mark symbol @code{x} for
1318 Additionally, we may need to insert a PHI node at line @code{11}
1319 because that is a merge point for @code{x_10} and @code{x_11}. So the
1320 use of @code{x_1} at line @code{11} will be replaced with the new PHI
1321 node. The insertion of PHI nodes is optional. They are not strictly
1322 necessary to preserve the SSA form, and depending on what the caller
1323 inserted, they may not even be useful for the optimizers@.
1325 Updating the SSA form is a two step process. First, the pass has to
1326 identify which names need to be updated and/or which symbols need to
1327 be renamed into SSA form for the first time. When new names are
1328 introduced to replace existing names in the program, the mapping
1329 between the old and the new names are registered by calling
1330 @code{register_new_name_mapping} (note that if your pass creates new
1331 code by duplicating basic blocks, the call to @code{tree_duplicate_bb}
1332 will set up the necessary mappings automatically). On the other hand,
1333 if your pass exposes a new symbol that should be put in SSA form for
1334 the first time, the new symbol should be registered with
1335 @code{mark_sym_for_renaming}.
1337 After the replacement mappings have been registered and new symbols
1338 marked for renaming, a call to @code{update_ssa} makes the registered
1339 changes. This can be done with an explicit call or by creating
1340 @code{TODO} flags in the @code{tree_opt_pass} structure for your pass.
1341 There are several @code{TODO} flags that control the behavior of
1345 @item @code{TODO_update_ssa}. Update the SSA form inserting PHI nodes
1346 for newly exposed symbols and virtual names marked for updating.
1347 When updating real names, only insert PHI nodes for a real name
1348 @code{O_j} in blocks reached by all the new and old definitions for
1349 @code{O_j}. If the iterated dominance frontier for @code{O_j}
1350 is not pruned, we may end up inserting PHI nodes in blocks that
1351 have one or more edges with no incoming definition for
1352 @code{O_j}. This would lead to uninitialized warnings for
1353 @code{O_j}'s symbol@.
1355 @item @code{TODO_update_ssa_no_phi}. Update the SSA form without
1356 inserting any new PHI nodes at all. This is used by passes that
1357 have either inserted all the PHI nodes themselves or passes that
1358 need only to patch use-def and def-def chains for virtuals
1362 @item @code{TODO_update_ssa_full_phi}. Insert PHI nodes everywhere
1363 they are needed. No pruning of the IDF is done. This is used
1364 by passes that need the PHI nodes for @code{O_j} even if it
1365 means that some arguments will come from the default definition
1366 of @code{O_j}'s symbol (e.g., @code{pass_linear_transform})@.
1368 WARNING: If you need to use this flag, chances are that your
1369 pass may be doing something wrong. Inserting PHI nodes for an
1370 old name where not all edges carry a new replacement may lead to
1371 silent codegen errors or spurious uninitialized warnings@.
1373 @item @code{TODO_update_ssa_only_virtuals}. Passes that update the
1374 SSA form on their own may want to delegate the updating of
1375 virtual names to the generic updater. Since FUD chains are
1376 easier to maintain, this simplifies the work they need to do.
1377 NOTE: If this flag is used, any OLD->NEW mappings for real names
1378 are explicitly destroyed and only the symbols marked for
1379 renaming are processed@.
1383 @subsection Examining @code{SSA_NAME} nodes
1384 @cindex examining SSA_NAMEs
1386 The following macros can be used to examine @code{SSA_NAME} nodes
1388 @defmac SSA_NAME_DEF_STMT (@var{var})
1389 Returns the statement @var{s} that creates the @code{SSA_NAME}
1390 @var{var}. If @var{s} is an empty statement (i.e., @code{IS_EMPTY_STMT
1391 (@var{s})} returns @code{true}), it means that the first reference to
1392 this variable is a USE or a VUSE@.
1395 @defmac SSA_NAME_VERSION (@var{var})
1396 Returns the version number of the @code{SSA_NAME} object @var{var}.
1400 @subsection Walking use-def chains
1402 @deftypefn {Tree SSA function} void walk_use_def_chains (@var{var}, @var{fn}, @var{data})
1404 Walks use-def chains starting at the @code{SSA_NAME} node @var{var}.
1405 Calls function @var{fn} at each reaching definition found. Function
1406 @var{FN} takes three arguments: @var{var}, its defining statement
1407 (@var{def_stmt}) and a generic pointer to whatever state information
1408 that @var{fn} may want to maintain (@var{data}). Function @var{fn} is
1409 able to stop the walk by returning @code{true}, otherwise in order to
1410 continue the walk, @var{fn} should return @code{false}.
1412 Note, that if @var{def_stmt} is a @code{PHI} node, the semantics are
1413 slightly different. For each argument @var{arg} of the PHI node, this
1417 @item Walk the use-def chains for @var{arg}.
1418 @item Call @code{FN (@var{arg}, @var{phi}, @var{data})}.
1421 Note how the first argument to @var{fn} is no longer the original
1422 variable @var{var}, but the PHI argument currently being examined.
1423 If @var{fn} wants to get at @var{var}, it should call
1424 @code{PHI_RESULT} (@var{phi}).
1427 @subsection Walking the dominator tree
1429 @deftypefn {Tree SSA function} void walk_dominator_tree (@var{walk_data}, @var{bb})
1431 This function walks the dominator tree for the current CFG calling a
1432 set of callback functions defined in @var{struct dom_walk_data} in
1433 @file{domwalk.h}. The call back functions you need to define give you
1434 hooks to execute custom code at various points during traversal:
1437 @item Once to initialize any local data needed while processing
1438 @var{bb} and its children. This local data is pushed into an
1439 internal stack which is automatically pushed and popped as the
1440 walker traverses the dominator tree.
1442 @item Once before traversing all the statements in the @var{bb}.
1444 @item Once for every statement inside @var{bb}.
1446 @item Once after traversing all the statements and before recursing
1447 into @var{bb}'s dominator children.
1449 @item It then recurses into all the dominator children of @var{bb}.
1451 @item After recursing into all the dominator children of @var{bb} it
1452 can, optionally, traverse every statement in @var{bb} again
1453 (i.e., repeating steps 2 and 3).
1455 @item Once after walking the statements in @var{bb} and @var{bb}'s
1456 dominator children. At this stage, the block local data stack
1461 @node Alias analysis
1462 @section Alias analysis
1464 @cindex flow-sensitive alias analysis
1465 @cindex flow-insensitive alias analysis
1467 Alias analysis proceeds in 4 main phases:
1470 @item Structural alias analysis.
1472 This phase walks the types for structure variables, and determines which
1473 of the fields can overlap using offset and size of each field. For each
1474 field, a ``subvariable'' called a ``Structure field tag'' (SFT)@ is
1475 created, which represents that field as a separate variable. All
1476 accesses that could possibly overlap with a given field will have
1477 virtual operands for the SFT of that field.
1488 int tmp1, tmp2, tmp3;
1489 SFT.0_2 = V_MUST_DEF <SFT.0_1>
1491 SFT.1_4 = V_MUST_DEF <SFT.1_3>
1499 tmp3_7 = tmp1_5 + tmp2_6;
1504 If you copy the type tag for a variable for some reason, you probably
1505 also want to copy the subvariables for that variable.
1507 @item Points-to and escape analysis.
1509 This phase walks the use-def chains in the SSA web looking for
1513 @item Assignments of the form @code{P_i = &VAR}
1514 @item Assignments of the form P_i = malloc()
1515 @item Pointers and ADDR_EXPR that escape the current function.
1518 The concept of `escaping' is the same one used in the Java world.
1519 When a pointer or an ADDR_EXPR escapes, it means that it has been
1520 exposed outside of the current function. So, assignment to
1521 global variables, function arguments and returning a pointer are
1524 This is where we are currently limited. Since not everything is
1525 renamed into SSA, we lose track of escape properties when a
1526 pointer is stashed inside a field in a structure, for instance.
1527 In those cases, we are assuming that the pointer does escape.
1529 We use escape analysis to determine whether a variable is
1530 call-clobbered. Simply put, if an ADDR_EXPR escapes, then the
1531 variable is call-clobbered. If a pointer P_i escapes, then all
1532 the variables pointed-to by P_i (and its memory tag) also escape.
1534 @item Compute flow-sensitive aliases
1536 We have two classes of memory tags. Memory tags associated with
1537 the pointed-to data type of the pointers in the program. These
1538 tags are called ``type memory tag'' (TMT)@. The other class are
1539 those associated with SSA_NAMEs, called ``name memory tag'' (NMT)@.
1540 The basic idea is that when adding operands for an INDIRECT_REF
1541 *P_i, we will first check whether P_i has a name tag, if it does
1542 we use it, because that will have more precise aliasing
1543 information. Otherwise, we use the standard type tag.
1545 In this phase, we go through all the pointers we found in
1546 points-to analysis and create alias sets for the name memory tags
1547 associated with each pointer P_i. If P_i escapes, we mark
1548 call-clobbered the variables it points to and its tag.
1551 @item Compute flow-insensitive aliases
1553 This pass will compare the alias set of every type memory tag and
1554 every addressable variable found in the program. Given a type
1555 memory tag TMT and an addressable variable V@. If the alias sets
1556 of TMT and V conflict (as computed by may_alias_p), then V is
1557 marked as an alias tag and added to the alias set of TMT@.
1560 For instance, consider the following function:
1579 After aliasing analysis has finished, the type memory tag for
1580 pointer @code{p} will have two aliases, namely variables @code{a} and
1582 Every time pointer @code{p} is dereferenced, we want to mark the
1583 operation as a potential reference to @code{a} and @code{b}.
1594 # p_1 = PHI <p_4(1), p_6(2)>;
1596 # a_7 = V_MAY_DEF <a_3>;
1597 # b_8 = V_MAY_DEF <b_5>;
1600 # a_9 = V_MAY_DEF <a_7>
1610 In certain cases, the list of may aliases for a pointer may grow
1611 too large. This may cause an explosion in the number of virtual
1612 operands inserted in the code. Resulting in increased memory
1613 consumption and compilation time.
1615 When the number of virtual operands needed to represent aliased
1616 loads and stores grows too large (configurable with @option{--param
1617 max-aliased-vops}), alias sets are grouped to avoid severe
1618 compile-time slow downs and memory consumption. The alias
1619 grouping heuristic proceeds as follows:
1622 @item Sort the list of pointers in decreasing number of contributed
1625 @item Take the first pointer from the list and reverse the role
1626 of the memory tag and its aliases. Usually, whenever an
1627 aliased variable Vi is found to alias with a memory tag
1628 T, we add Vi to the may-aliases set for T@. Meaning that
1629 after alias analysis, we will have:
1632 may-aliases(T) = @{ V1, V2, V3, ..., Vn @}
1635 This means that every statement that references T, will get
1636 @code{n} virtual operands for each of the Vi tags. But, when
1637 alias grouping is enabled, we make T an alias tag and add it
1638 to the alias set of all the Vi variables:
1641 may-aliases(V1) = @{ T @}
1642 may-aliases(V2) = @{ T @}
1644 may-aliases(Vn) = @{ T @}
1647 This has two effects: (a) statements referencing T will only get
1648 a single virtual operand, and, (b) all the variables Vi will now
1649 appear to alias each other. So, we lose alias precision to
1650 improve compile time. But, in theory, a program with such a high
1651 level of aliasing should not be very optimizable in the first
1654 @item Since variables may be in the alias set of more than one
1655 memory tag, the grouping done in step (2) needs to be extended
1656 to all the memory tags that have a non-empty intersection with
1657 the may-aliases set of tag T@. For instance, if we originally
1658 had these may-aliases sets:
1661 may-aliases(T) = @{ V1, V2, V3 @}
1662 may-aliases(R) = @{ V2, V4 @}
1665 In step (2) we would have reverted the aliases for T as:
1668 may-aliases(V1) = @{ T @}
1669 may-aliases(V2) = @{ T @}
1670 may-aliases(V3) = @{ T @}
1673 But note that now V2 is no longer aliased with R@. We could
1674 add R to may-aliases(V2), but we are in the process of
1675 grouping aliases to reduce virtual operands so what we do is
1676 add V4 to the grouping to obtain:
1679 may-aliases(V1) = @{ T @}
1680 may-aliases(V2) = @{ T @}
1681 may-aliases(V3) = @{ T @}
1682 may-aliases(V4) = @{ T @}
1685 @item If the total number of virtual operands due to aliasing is
1686 still above the threshold set by max-alias-vops, go back to (2).