@c Copyright (c) 2004 Free Software Foundation, Inc. @c Free Software Foundation, Inc. @c This is part of the GCC manual. @c For copying conditions, see the file gcc.texi. @c --------------------------------------------------------------------- @c Tree SSA @c --------------------------------------------------------------------- @node Tree SSA @chapter Analysis and Optimization of GIMPLE Trees @cindex Tree SSA @cindex Optimization infrastructure for GIMPLE GCC uses three main intermediate languages to represent the program during compilation: GENERIC, GIMPLE and RTL@. GENERIC is a language-independent representation generated by each front end. It is used to serve as an interface between the parser and optimizer. GENERIC is a common representation that is able to represent programs written in all the languages supported by GCC@. GIMPLE and RTL are used to optimize the program. GIMPLE is used for target and language independent optimizations (e.g., inlining, constant propagation, tail call elimination, redundancy elimination, etc). Much like GENERIC, GIMPLE is a language independent, tree based representation. However, it differs from GENERIC in that the GIMPLE grammar is more restrictive: expressions contain no more than 3 operands (except function calls), it has no control flow structures and expressions with side-effects are only allowed on the right hand side of assignments. See the chapter describing GENERIC and GIMPLE for more details. This chapter describes the data structures and functions used in the GIMPLE optimizers (also known as ``tree optimizers'' or ``middle end''). In particular, it focuses on all the macros, data structures, functions and programming constructs needed to implement optimization passes for GIMPLE@. @menu * GENERIC:: A high-level language-independent representation. * GIMPLE:: A lower-level factored tree representation. * Annotations:: Attributes for statements and variables. * Statement Operands:: Variables referenced by GIMPLE statements. * SSA:: Static Single Assignment representation. * Alias analysis:: Representing aliased loads and stores. @end menu @node GENERIC @section GENERIC @cindex GENERIC The purpose of GENERIC is simply to provide a language-independent way of representing an entire function in trees. To this end, it was necessary to add a few new tree codes to the back end, but most everything was already there. If you can express it with the codes in @code{gcc/tree.def}, it's GENERIC. Early on, there was a great deal of debate about how to think about statements in a tree IL. In GENERIC, a statement is defined as any expression whose value, if any, is ignored. A statement will always have @code{TREE_SIDE_EFFECTS} set (or it will be discarded), but a non-statement expression may also have side effects. A @code{CALL_EXPR}, for instance. It would be possible for some local optimizations to work on the GENERIC form of a function; indeed, the adapted tree inliner works fine on GENERIC, but the current compiler performs inlining after lowering to GIMPLE (a restricted form described in the next section). Indeed, currently the frontends perform this lowering before handing off to @code{tree_rest_of_compilation}, but this seems inelegant. If necessary, a front end can use some language-dependent tree codes in its GENERIC representation, so long as it provides a hook for converting them to GIMPLE and doesn't expect them to work with any (hypothetical) optimizers that run before the conversion to GIMPLE. The intermediate representation used while parsing C and C++ looks very little like GENERIC, but the C and C++ gimplifier hooks are perfectly happy to take it as input and spit out GIMPLE. @node GIMPLE @section GIMPLE @cindex GIMPLE GIMPLE is a simplified subset of GENERIC for use in optimization. The particular subset chosen (and the name) was heavily influenced by the SIMPLE IL used by the McCAT compiler project at McGill University, though we have made some different choices. For one thing, SIMPLE doesn't support @code{goto}; a production compiler can't afford that kind of restriction. GIMPLE retains much of the structure of the parse trees: lexical scopes are represented as containers, rather than markers. However, expressions are broken down into a 3-address form, using temporary variables to hold intermediate values. Also, control structures are lowered to gotos. In GIMPLE no container node is ever used for its value; if a @code{COND_EXPR} or @code{BIND_EXPR} has a value, it is stored into a temporary within the controlled blocks, and that temporary is used in place of the container. The compiler pass which lowers GENERIC to GIMPLE is referred to as the @samp{gimplifier}. The gimplifier works recursively, replacing complex statements with sequences of simple statements. @c Currently, the only way to @c tell whether or not an expression is in GIMPLE form is by recursively @c examining it; in the future there will probably be a flag to help avoid @c redundant work. FIXME FIXME @menu * Interfaces:: * Temporaries:: * GIMPLE Expressions:: * Statements:: * GIMPLE Example:: * Rough GIMPLE Grammar:: @end menu @node Interfaces @subsection Interfaces @cindex gimplification The tree representation of a function is stored in @code{DECL_SAVED_TREE}. It is lowered to GIMPLE by a call to @code{gimplify_function_tree}. If a front end wants to include language-specific tree codes in the tree representation which it provides to the back end, it must provide a definition of @code{LANG_HOOKS_GIMPLIFY_EXPR} which knows how to convert the front end trees to GIMPLE. Usually such a hook will involve much of the same code for expanding front end trees to RTL. This function can return fully lowered GIMPLE, or it can return GENERIC trees and let the main gimplifier lower them the rest of the way; this is often simpler. The C and C++ front ends currently convert directly from front end trees to GIMPLE, and hand that off to the back end rather than first converting to GENERIC. Their gimplifier hooks know about all the @code{_STMT} nodes and how to convert them to GENERIC forms. There was some work done on a genericization pass which would run first, but the existence of @code{STMT_EXPR} meant that in order to convert all of the C statements into GENERIC equivalents would involve walking the entire tree anyway, so it was simpler to lower all the way. This might change in the future if someone writes an optimization pass which would work better with higher-level trees, but currently the optimizers all expect GIMPLE. A front end which wants to use the tree optimizers (and already has some sort of whole-function tree representation) only needs to provide a definition of @code{LANG_HOOKS_GIMPLIFY_EXPR}, call @code{gimplify_function_tree} to lower to GIMPLE, and then hand off to @code{tree_rest_of_compilation} to compile and output the function. You can tell the compiler to dump a C-like representation of the GIMPLE form with the flag @code{-fdump-tree-gimple}. @node Temporaries @subsection Temporaries @cindex Temporaries When gimplification encounters a subexpression which is too complex, it creates a new temporary variable to hold the value of the subexpression, and adds a new statement to initialize it before the current statement. These special temporaries are known as @samp{expression temporaries}, and are allocated using @code{get_formal_tmp_var}. The compiler tries to always evaluate identical expressions into the same temporary, to simplify elimination of redundant calculations. We can only use expression temporaries when we know that it will not be reevaluated before its value is used, and that it will not be otherwise modified@footnote{These restrictions are derived from those in Morgan 4.8.}. Other temporaries can be allocated using @code{get_initialized_tmp_var} or @code{create_tmp_var}. Currently, an expression like @code{a = b + 5} is not reduced any further. We tried converting it to something like @smallexample T1 = b + 5; a = T1; @end smallexample but this bloated the representation for minimal benefit. However, a variable which must live in memory cannot appear in an expression; its value is explicitly loaded into a temporary first. Similarly, storing the value of an expression to a memory variable goes through a temporary. @node GIMPLE Expressions @subsection Expressions @cindex GIMPLE Expressions In general, expressions in GIMPLE consist of an operation and the appropriate number of simple operands; these operands must either be a GIMPLE rvalue (@code{is_gimple_val}), i.e. a constant or a register variable. More complex operands are factored out into temporaries, so that @smallexample a = b + c + d @end smallexample becomes @smallexample T1 = b + c; a = T1 + d; @end smallexample The same rule holds for arguments to a @code{CALL_EXPR}. The target of an assignment is usually a variable, but can also be an @code{INDIRECT_REF} or a compound lvalue as described below. @menu * Compound Expressions:: * Compound Lvalues:: * Conditional Expressions:: * Logical Operators:: @end menu @node Compound Expressions @subsubsection Compound Expressions @cindex Compound Expressions The left-hand side of a C comma expression is simply moved into a separate statement. @node Compound Lvalues @subsubsection Compound Lvalues @cindex Compound Lvalues Currently compound lvalues involving array and structure field references are not broken down; an expression like @code{a.b[2] = 42} is not reduced any further (though complex array subscripts are). This restriction is a workaround for limitations in later optimizers; if we were to convert this to @smallexample T1 = &a.b; T1[2] = 42; @end smallexample alias analysis would not remember that the reference to @code{T1[2]} came by way of @code{a.b}, so it would think that the assignment could alias another member of @code{a}; this broke @code{struct-alias-1.c}. Future optimizer improvements may make this limitation unnecessary. @node Conditional Expressions @subsubsection Conditional Expressions @cindex Conditional Expressions A C @code{?:} expression is converted into an @code{if} statement with each branch assigning to the same temporary. So, @smallexample a = b ? c : d; @end smallexample becomes @smallexample if (b) T1 = c; else T1 = d; a = T1; @end smallexample Note that in GIMPLE, @code{if} statements are also represented using @code{COND_EXPR}, as described below. @node Logical Operators @subsubsection Logical Operators @cindex Logical Operators Except when they appear in the condition operand of a @code{COND_EXPR}, logical `and' and `or' operators are simplified as follows: @code{a = b && c} becomes @smallexample T1 = (bool)b; if (T1) T1 = (bool)c; a = T1; @end smallexample Note that @code{T1} in this example cannot be an expression temporary, because it has two different assignments. @node Statements @subsection Statements @cindex Statements Most statements will be assignment statements, represented by @code{MODIFY_EXPR}. A @code{CALL_EXPR} whose value is ignored can also be a statement. No other C expressions can appear at statement level; a reference to a volatile object is converted into a @code{MODIFY_EXPR}. There are also several varieties of complex statements. @menu * Blocks:: * Statement Sequences:: * Empty Statements:: * Loops:: * Selection Statements:: * Jumps:: * Cleanups:: * GIMPLE Exception Handling:: @end menu @node Blocks @subsubsection Blocks @cindex Blocks Block scopes and the variables they declare in GENERIC and GIMPLE are expressed using the @code{BIND_EXPR} code, which in previous versions of GCC was primarily used for the C statement-expression extension. Variables in a block are collected into @code{BIND_EXPR_VARS} in declaration order. Any runtime initialization is moved out of @code{DECL_INITIAL} and into a statement in the controlled block. When gimplifying from C or C++, this initialization replaces the @code{DECL_STMT}. Variable-length arrays (VLAs) complicate this process, as their size often refers to variables initialized earlier in the block. To handle this, we currently split the block at that point, and move the VLA into a new, inner @code{BIND_EXPR}. This strategy may change in the future. @code{DECL_SAVED_TREE} for a GIMPLE function will always be a @code{BIND_EXPR} which contains declarations for the temporary variables used in the function. A C++ program will usually contain more @code{BIND_EXPR}s than there are syntactic blocks in the source code, since several C++ constructs have implicit scopes associated with them. On the other hand, although the C++ front end uses pseudo-scopes to handle cleanups for objects with destructors, these don't translate into the GIMPLE form; multiple declarations at the same level use the same BIND_EXPR. @node Statement Sequences @subsubsection Statement Sequences @cindex Statement Sequences Multiple statements at the same nesting level are collected into a @code{STATEMENT_LIST}. Statement lists are modified and traversed using the interface in @samp{tree-iterator.h}. @node Empty Statements @subsubsection Empty Statements @cindex Empty Statements Whenever possible, statements with no effect are discarded. But if they are nested within another construct which cannot be discarded for some reason, they are instead replaced with an empty statement, generated by @code{build_empty_stmt}. Initially, all empty statements were shared, after the pattern of the Java front end, but this caused a lot of trouble in practice. An empty statement is represented as @code{(void)0}. @node Loops @subsubsection Loops @cindex Loops At one time loops were expressed in GIMPLE using @code{LOOP_EXPR}, but now they are lowered to explicit gotos. @node Selection Statements @subsubsection Selection Statements @cindex Selection Statements A simple selection statement, such as the C @code{if} statement, is expressed in GIMPLE using a void @code{COND_EXPR}. If only one branch is used, the other is filled with an empty statement. Normally, the condition expression is reduced to a simple comparison. If it is a shortcut (@code{&&} or @code{||}) expression, however, we try to break up the @code{if} into multiple @code{if}s so that the implied shortcut is taken directly, much like the transformation done by @code{do_jump} in the RTL expander. A @code{SWITCH_EXPR} in GIMPLE contains the condition and a @code{TREE_VEC} of @code{CASE_LABEL_EXPR}s describing the case values and corresponding @code{LABEL_DECL}s to jump to. The body of the @code{switch} is moved after the @code{SWITCH_EXPR}. @node Jumps @subsubsection Jumps @cindex Jumps Other jumps are expressed by either @code{GOTO_EXPR} or @code{RETURN_EXPR}. The operand of a @code{GOTO_EXPR} must be either a label or a variable containing the address to jump to. The operand of a @code{RETURN_EXPR} is either @code{NULL_TREE} or a @code{MODIFY_EXPR} which sets the return value. It would be nice to move the @code{MODIFY_EXPR} into a separate statement, but the special return semantics in @code{expand_return} make that difficult. It may still happen in the future, perhaps by moving most of that logic into @code{expand_assignment}. @node Cleanups @subsubsection Cleanups @cindex Cleanups Destructors for local C++ objects and similar dynamic cleanups are represented in GIMPLE by a @code{TRY_FINALLY_EXPR}. When the controlled block exits, the cleanup is run. @code{TRY_FINALLY_EXPR} complicates the flow graph, since the cleanup needs to appear on every edge out of the controlled block; this reduces our freedom to move code across these edges. Therefore, the EH lowering pass which runs before most of the optimization passes eliminates these expressions by explicitly adding the cleanup to each edge. @node GIMPLE Exception Handling @subsubsection Exception Handling @cindex GIMPLE Exception Handling Other exception handling constructs are represented using @code{TRY_CATCH_EXPR}. The handler operand of a @code{TRY_CATCH_EXPR} can be a normal statement to be executed if the controlled block throws an exception, or it can have one of two special forms: @enumerate @item A @code{CATCH_EXPR} executes its handler if the thrown exception matches one of the allowed types. Multiple handlers can be expressed by a sequence of @code{CATCH_EXPR} statements. @item An @code{EH_FILTER_EXPR} executes its handler if the thrown exception does not match one of the allowed types. @end enumerate Currently throwing an exception is not directly represented in GIMPLE, since it is implemented by calling a function. At some point in the future we will want to add some way to express that the call will throw an exception of a known type. Just before running the optimizers, the compiler lowers the high-level EH constructs above into a set of @samp{goto}s, magic labels, and EH regions. Continuing to unwind at the end of a cleanup is represented with a @code{RESX_EXPR}. @node GIMPLE Example @subsection GIMPLE Example @cindex GIMPLE Example @smallexample struct A @{ A(); ~A(); @}; int i; int g(); void f() @{ A a; int j = (--i, i ? 0 : 1); for (int x = 42; x > 0; --x) @{ i += g()*4 + 32; @} @} @end smallexample becomes @smallexample void f() @{ int i.0; int T.1; int iftmp.2; int T.3; int T.4; int T.5; int T.6; @{ struct A a; int j; __comp_ctor (&a); try @{ i.0 = i; T.1 = i.0 - 1; i = T.1; i.0 = i; if (i.0 == 0) iftmp.2 = 1; else iftmp.2 = 0; j = iftmp.2; @{ int x; x = 42; goto test; loop:; T.3 = g (); T.4 = T.3 * 4; i.0 = i; T.5 = T.4 + i.0; T.6 = T.5 + 32; i = T.6; x = x - 1; test:; if (x > 0) goto loop; else goto break_; break_:; @} @} finally @{ __comp_dtor (&a); @} @} @} @end smallexample @node Rough GIMPLE Grammar @subsection Rough GIMPLE Grammar @cindex Rough GIMPLE Grammar @smallexample function: FUNCTION_DECL DECL_SAVED_TREE -> block block: BIND_EXPR BIND_EXPR_VARS -> DECL chain BIND_EXPR_BLOCK -> BLOCK BIND_EXPR_BODY -> compound-stmt compound-stmt: COMPOUND_EXPR op0 -> non-compound-stmt op1 -> stmt stmt: compound-stmt | non-compound-stmt non-compound-stmt: block | if-stmt | switch-stmt | jump-stmt | label-stmt | try-stmt | modify-stmt | call-stmt if-stmt: COND_EXPR op0 -> condition op1 -> stmt op2 -> stmt switch-stmt: SWITCH_EXPR op0 -> val op1 -> NULL_TREE op2 -> TREE_VEC of CASE_LABEL_EXPRs jump-stmt: GOTO_EXPR op0 -> LABEL_DECL | '*' ID | RETURN_EXPR op0 -> modify-stmt | NULL_TREE label-stmt: LABEL_EXPR op0 -> LABEL_DECL try-stmt: TRY_CATCH_EXPR op0 -> stmt op1 -> handler | TRY_FINALLY_EXPR op0 -> stmt op1 -> stmt handler: catch-seq | EH_FILTER_EXPR | stmt catch-seq: CATCH_EXPR | COMPOUND_EXPR op0 -> CATCH_EXPR op1 -> catch-seq modify-stmt: MODIFY_EXPR op0 -> lhs op1 -> rhs call-stmt: CALL_EXPR op0 -> _DECL | '&' _DECL op1 -> arglist arglist: NULL_TREE | TREE_LIST op0 -> val op1 -> arglist varname : compref | _DECL lhs: varname | '*' _DECL pseudo-lval: _DECL | '*' _DECL compref : COMPONENT_REF op0 -> compref | pseudo-lval | ARRAY_REF op0 -> compref | pseudo-lval op1 -> val condition : val | val relop val val : _DECL | CONST rhs: varname | CONST | '*' _DECL | '&' varname | call_expr | unop val | val binop val | '(' cast ')' val unop: '+' | '-' | '!' | '~' binop: relop | '-' | '+' | '/' | '*' | '%' | '&' | '|' | '<<' | '>>' | '^' relop: All tree codes of class '<' @end smallexample @node Annotations @section Annotations @cindex annotations The optimizers need to associate attributes with statements and variables during the optimization process. For instance, we need to know what basic block does a statement belong to or whether a variable has aliases. All these attributes are stored in data structures called annotations which are then linked to the field @code{ann} in @code{struct tree_common}. Presently, we define annotations for statements (@code{stmt_ann_t}), variables (@code{var_ann_t}) and SSA names (@code{ssa_name_ann_t}). Annotations are defined and documented in @file{tree-flow.h}. @node Statement Operands @section Statement Operands @cindex operands @cindex virtual operands @cindex real operands @findex get_stmt_operands @findex modify_stmt Almost every GIMPLE statement will contain a reference to a variable or memory location. Since statements come in different shapes and sizes, their operands are going to be located at various spots inside the statement's tree. To facilitate access to the statement's operands, they are organized into arrays associated inside each statement's annotation. Each element in an operand array is a pointer to a @code{VAR_DECL}, @code{PARM_DECL} or @code{SSA_NAME} tree node. This provides a very convenient way of examining and replacing operands. Data flow analysis and optimization is done on all tree nodes representing variables. Any node for which @code{SSA_VAR_P} returns nonzero is considered when scanning statement operands. However, not all @code{SSA_VAR_P} variables are processed in the same way. For the purposes of optimization, we need to distinguish between references to local scalar variables and references to globals, statics, structures, arrays, aliased variables, etc. The reason is simple, the compiler can gather complete data flow information for a local scalar. On the other hand, a global variable may be modified by a function call, it may not be possible to keep track of all the elements of an array or the fields of a structure, etc. The operand scanner gathers two kinds of operands: @dfn{real} and @dfn{virtual}. An operand for which @code{is_gimple_reg} returns true is considered real, otherwise it is a virtual operand. We also distinguish between uses and definitions. An operand is used if its value is loaded by the statement (e.g., the operand at the RHS of an assignment). If the statement assigns a new value to the operand, the operand is considered a definition (e.g., the operand at the LHS of an assignment). Virtual and real operands also have very different data flow properties. Real operands are unambiguous references to the full object that they represent. For instance, given @smallexample @{ int a, b; a = b @} @end smallexample Since @code{a} and @code{b} are non-aliased locals, the statement @code{a = b} will have one real definition and one real use because variable @code{b} is completely modified with the contents of variable @code{a}. Real definition are also known as @dfn{killing definitions}. Similarly, the use of @code{a} reads all its bits. In contrast, virtual operands represent partial or ambiguous references to a variable. For instance, given @smallexample @{ int a, b, *p; if (...) p = &a; else p = &b; *p = 5; return *p; @} @end smallexample The assignment @code{*p = 5} may be a definition of @code{a} or @code{b}. If we cannot determine statically where @code{p} is pointing to at the time of the store operation, we create virtual definitions to mark that statement as a potential definition site for @code{a} and @code{b}. Memory loads are similarly marked with virtual use operands. Virtual operands are shown in tree dumps right before the statement that contains them. To request a tree dump with virtual operands, use the @option{-vops} option to @option{-fdump-tree}: @smallexample @{ int a, b, *p; if (...) p = &a; else p = &b; # a = VDEF # b = VDEF *p = 5; # VUSE # VUSE return *p; @} @end smallexample Notice that @code{VDEF} operands have two copies of the referenced variable. This indicates that this is not a killing definition of that variable. In this case we refer to it as a @dfn{may definition} or @dfn{aliased store}. The presence of the second copy of the variable in the @code{VDEF} operand will become important when the function is converted into SSA form. This will be used to link all the non-killing definitions to prevent optimizations from making incorrect assumptions about them. Operands are collected by @file{tree-ssa-operands.c}. They are stored inside each statement's annotation and can be accessed with @code{DEF_OPS}, @code{USE_OPS}, @code{VDEF_OPS} and @code{VUSE_OPS}. The following are all the accessor macros available to access USE operands. To access all the other operand arrays, just change the name accordingly: @defmac USE_OPS (@var{ann}) Returns the array of operands used by the statement with annotation @var{ann}. @end defmac @defmac STMT_USE_OPS (@var{stmt}) Alternate version of USE_OPS that takes the statement @var{stmt} as input. @end defmac @defmac NUM_USES (@var{ops}) Return the number of USE operands in array @var{ops}. @end defmac @defmac USE_OP_PTR (@var{ops}, @var{i}) Return a pointer to the @var{i}th operand in array @var{ops}. @end defmac @defmac USE_OP (@var{ops}, @var{i}) Return the @var{i}th operand in array @var{ops}. @end defmac The following function shows how to print all the operands of a given statement: @smallexample void print_ops (tree stmt) @{ vuse_optype vuses; vdef_optype vdefs; def_optype defs; use_optype uses; stmt_ann_t ann; size_t i; get_stmt_operands (stmt); ann = stmt_ann (stmt); defs = DEF_OPS (ann); for (i = 0; i < NUM_DEFS (defs); i++) print_generic_expr (stderr, DEF_OP (defs, i), 0); uses = USE_OPS (ann); for (i = 0; i < NUM_USES (uses); i++) print_generic_expr (stderr, USE_OP (uses, i), 0); vdefs = VDEF_OPS (ann); for (i = 0; i < NUM_VDEFS (vdefs); i++) print_generic_expr (stderr, VDEF_OP (vdefs, i), 0); vuses = VUSE_OPS (ann); for (i = 0; i < NUM_VUSES (vuses); i++) print_generic_expr (stderr, VUSE_OP (vuses, i), 0); @} @end smallexample To collect the operands, you first need to call @code{get_stmt_operands}. Since that is a potentially expensive operation, statements are only scanned if they have been marked modified by a call to @code{modify_stmt}. So, if your pass replaces operands in a statement, make sure to call @code{modify_stmt}. @node SSA @section Static Single Assignment @cindex SSA @cindex static single assignment Most of the tree optimizers rely on the data flow information provided by the Static Single Assignment (SSA) form. We implement the SSA form as described in @cite{R. Cytron, J. Ferrante, B. Rosen, M. Wegman, and K. Zadeck. Efficiently Computing Static Single Assignment Form and the Control Dependence Graph. ACM Transactions on Programming Languages and Systems, 13(4):451-490, October 1991}. The SSA form is based on the premise that program variables are assigned in exactly one location in the program. Multiple assignments to the same variable create new versions of that variable. Naturally, actual programs are seldom in SSA form initially because variables tend to be assigned multiple times. The compiler modifies the program representation so that every time a variable is assigned in the code, a new version of the variable is created. Different versions of the same variable are distinguished by subscripting the variable name with its version number. Variables used in the right-hand side of expressions are renamed so that their version number matches that of the most recent assignment. We represent variable versions using @code{SSA_NAME} nodes. The renaming process in @file{tree-ssa.c} wraps every real and virtual operand with an @code{SSA_NAME} node which contains the version number and the statement that created the @code{SSA_NAME}. Only definitions and virtual definitions may create new @code{SSA_NAME} nodes. Sometimes, flow of control makes it impossible to determine what is the most recent version of a variable. In these cases, the compiler inserts an artificial definition for that variable called @dfn{PHI function} or @dfn{PHI node}. This new definition merges all the incoming versions of the variable to create a new name for it. For instance, @smallexample if (...) a_1 = 5; else if (...) a_2 = 2; else a_3 = 13; # a_4 = PHI return a_4; @end smallexample Since it is not possible to determine which of the three branches will be taken at runtime, we don't know which of @code{a_1}, @code{a_2} or @code{a_3} to use at the return statement. So, the SSA renamer creates a new version @code{a_4} which is assigned the result of ``merging'' @code{a_1}, @code{a_2} and @code{a_3}. Hence, PHI nodes mean ``one of these operands. I don't know which''. The following macros can be used to examine PHI nodes @defmac PHI_RESULT (@var{phi}) Returns the @code{SSA_NAME} created by PHI node @var{phi} (i.e., @var{phi}'s LHS). @end defmac @defmac PHI_NUM_ARGS (@var{phi}) Returns the number of arguments in @var{phi}. This number is exactly the number of incoming edges to the basic block holding @var{phi}@. @end defmac @defmac PHI_ARG_ELT (@var{phi}, @var{i}) Returns a tuple representing the @var{i}th argument of @var{phi}@. Each element of this tuple contains an @code{SSA_NAME} @var{var} and the incoming edge through which @var{var} flows. @end defmac @defmac PHI_ARG_EDGE (@var{phi}, @var{i}) Returns the incoming edge for the @var{i}th argument of @var{phi}. @end defmac @defmac PHI_ARG_DEF (@var{phi}, @var{i}) Returns the @code{SSA_NAME} for the @var{i}th argument of @var{phi}. @end defmac @subsection Preserving the SSA form @findex vars_to_rename @cindex preserving SSA form Some optimization passes make changes to the function that invalidate the SSA property. This can happen when a pass has added new variables or changed the program so that variables that were previously aliased aren't anymore. Whenever something like this happens, the affected variables must be renamed into SSA form again. To do this, you should mark the new variables in the global bitmap @code{vars_to_rename}. Once your pass has finished, the pass manager will invoke the SSA renamer to put the program into SSA once more. @subsection Examining @code{SSA_NAME} nodes @cindex examining SSA_NAMEs The following macros can be used to examine @code{SSA_NAME} nodes @defmac SSA_NAME_DEF_STMT (@var{var}) Returns the statement @var{s} that creates the @code{SSA_NAME} @var{var}. If @var{s} is an empty statement (i.e., @code{IS_EMPTY_STMT (@var{s})} returns @code{true}), it means that the first reference to this variable is a USE or a VUSE@. @end defmac @defmac SSA_NAME_VERSION (@var{var}) Returns the version number of the @code{SSA_NAME} object @var{var}. @end defmac @subsection Walking use-def chains @deftypefn {Tree SSA function} void walk_use_def_chains (@var{var}, @var{fn}, @var{data}) Walks use-def chains starting at the @code{SSA_NAME} node @var{var}. Calls function @var{fn} at each reaching definition found. Function @var{FN} takes three arguments: @var{var}, its defining statement (@var{def_stmt}) and a generic pointer to whatever state information that @var{fn} may want to maintain (@var{data}). Function @var{fn} is able to stop the walk by returning @code{true}, otherwise in order to continue the walk, @var{fn} should return @code{false}. Note, that if @var{def_stmt} is a @code{PHI} node, the semantics are slightly different. For each argument @var{arg} of the PHI node, this function will: @enumerate @item Walk the use-def chains for @var{arg}. @item Call @code{FN (@var{arg}, @var{phi}, @var{data})}. @end enumerate Note how the first argument to @var{fn} is no longer the original variable @var{var}, but the PHI argument currently being examined. If @var{fn} wants to get at @var{var}, it should call @code{PHI_RESULT} (@var{phi}). @end deftypefn @subsection Walking the dominator tree @deftypefn {Tree SSA function} void walk_dominator_tree (@var{walk_data}, @var{bb}) This function walks the dominator tree for the current CFG calling a set of callback functions defined in @var{struct dom_walk_data} in @file{domwalk.h}. The call back functions you need to define give you hooks to execute custom code at various points during traversal: @enumerate @item Once to initialize any local data needed while processing @var{bb} and its children. This local data is pushed into an internal stack which is automatically pushed and popped as the walker traverses the dominator tree. @item Once before traversing all the statements in the @var{bb}. @item Once for every statement inside @var{bb}. @item Once after traversing all the statements and before recursing into @var{bb}'s dominator children. @item It then recurses into all the dominator children of @var{bb}. @item After recursing into all the dominator children of @var{bb} it can, optionally, traverse every statement in @var{bb} again (i.e., repeating steps 2 and 3). @item Once after walking the statements in @var{bb} and @var{bb}'s dominator children. At this stage, the block local data stack is popped. @end enumerate @end deftypefn @node Alias analysis @section Alias analysis @cindex alias @cindex flow-sensitive alias analysis @cindex flow-insensitive alias analysis Alias analysis proceeds in 3 main phases: @enumerate @item Points-to and escape analysis. This phase walks the use-def chains in the SSA web looking for three things: @itemize @bullet @item Assignments of the form @code{P_i = &VAR} @item Assignments of the form P_i = malloc() @item Pointers and ADDR_EXPR that escape the current function. @end itemize The concept of `escaping' is the same one used in the Java world. When a pointer or an ADDR_EXPR escapes, it means that it has been exposed outside of the current function. So, assignment to global variables, function arguments and returning a pointer are all escape sites. This is where we are currently limited. Since not everything is renamed into SSA, we lose track of escape properties when a pointer is stashed inside a field in a structure, for instance. In those cases, we are assuming that the pointer does escape. We use escape analysis to determine whether a variable is call-clobbered. Simply put, if an ADDR_EXPR escapes, then the variable is call-clobbered. If a pointer P_i escapes, then all the variables pointed-to by P_i (and its memory tag) also escape. @item Compute flow-sensitive aliases We have two classes of memory tags. Memory tags associated with the pointed-to data type of the pointers in the program. These tags are called ``type memory tag'' (TMT). The other class are those associated with SSA_NAMEs, called ``name memory tag'' (NMT). The basic idea is that when adding operands for an INDIRECT_REF *P_i, we will first check whether P_i has a name tag, if it does we use it, because that will have more precise aliasing information. Otherwise, we use the standard type tag. In this phase, we go through all the pointers we found in points-to analysis and create alias sets for the name memory tags associated with each pointer P_i. If P_i escapes, we mark call-clobbered the variables it points to and its tag. @item Compute flow-insensitive aliases This pass will compare the alias set of every type memory tag and every addressable variable found in the program. Given a type memory tag TMT and an addressable variable V@. If the alias sets of TMT and V conflict (as computed by may_alias_p), then V is marked as an alias tag and added to the alias set of TMT@. @end enumerate For instance, consider the following function: @example foo (int i) @{ int *p, *q, a, b; if (i > 10) p = &a; else q = &b; *p = 3; *q = 5; a = b + 2; return *p; @} @end example After aliasing analysis has finished, the type memory tag for pointer @code{p} will have two aliases, namely variables @code{a} and @code{b}. Every time pointer @code{p} is dereferenced, we want to mark the operation as a potential reference to @code{a} and @code{b}. @example foo (int i) @{ int *p, a, b; if (i_2 > 10) p_4 = &a; else p_6 = &b; # p_1 = PHI ; # a_7 = VDEF ; # b_8 = VDEF ; *p_1 = 3; # a_9 = VDEF # VUSE a_9 = b_8 + 2; # VUSE ; # VUSE ; return *p_1; @} @end example In certain cases, the list of may aliases for a pointer may grow too large. This may cause an explosion in the number of virtual operands inserted in the code. Resulting in increased memory consumption and compilation time. When the number of virtual operands needed to represent aliased loads and stores grows too large (configurable with @option{--param max-aliased-vops}), alias sets are grouped to avoid severe compile-time slow downs and memory consumption. The alias grouping heuristic proceeds as follows: @enumerate @item Sort the list of pointers in decreasing number of contributed virtual operands. @item Take the first pointer from the list and reverse the role of the memory tag and its aliases. Usually, whenever an aliased variable Vi is found to alias with a memory tag T, we add Vi to the may-aliases set for T@. Meaning that after alias analysis, we will have: @smallexample may-aliases(T) = @{ V1, V2, V3, ..., Vn @} @end smallexample This means that every statement that references T, will get @code{n} virtual operands for each of the Vi tags. But, when alias grouping is enabled, we make T an alias tag and add it to the alias set of all the Vi variables: @smallexample may-aliases(V1) = @{ T @} may-aliases(V2) = @{ T @} ... may-aliases(Vn) = @{ T @} @end smallexample This has two effects: (a) statements referencing T will only get a single virtual operand, and, (b) all the variables Vi will now appear to alias each other. So, we lose alias precision to improve compile time. But, in theory, a program with such a high level of aliasing should not be very optimizable in the first place. @item Since variables may be in the alias set of more than one memory tag, the grouping done in step (2) needs to be extended to all the memory tags that have a non-empty intersection with the may-aliases set of tag T@. For instance, if we originally had these may-aliases sets: @smallexample may-aliases(T) = @{ V1, V2, V3 @} may-aliases(R) = @{ V2, V4 @} @end smallexample In step (2) we would have reverted the aliases for T as: @smallexample may-aliases(V1) = @{ T @} may-aliases(V2) = @{ T @} may-aliases(V3) = @{ T @} @end smallexample But note that now V2 is no longer aliased with R@. We could add R to may-aliases(V2), but we are in the process of grouping aliases to reduce virtual operands so what we do is add V4 to the grouping to obtain: @smallexample may-aliases(V1) = @{ T @} may-aliases(V2) = @{ T @} may-aliases(V3) = @{ T @} may-aliases(V4) = @{ T @} @end smallexample @item If the total number of virtual operands due to aliasing is still above the threshold set by max-alias-vops, go back to (2). @end enumerate