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@c Copyright (c) 2004, 2005, 2007, 2008, 2010

@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 tuples

@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

* Annotations::         Attributes for variables.

* SSA Operands::        SSA names referenced by GIMPLE statements.

* SSA::                 Static Single Assignment representation.

* Alias analysis::      Representing aliased loads and stores.

* Memory model::        Memory model used by the middle-end.

@end menu

@node Annotations

@section Annotations

@cindex annotations

The optimizers need to associate attributes with variables during the

optimization process.  For instance, we need to know 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 variables (@code{var_ann_t}).

Annotations are defined and documented in @file{tree-flow.h}.

@node SSA Operands

@section SSA Operands

@cindex operands

@cindex virtual operands

@cindex real operands

@findex update_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 lists associated inside each

statement's annotation.  Each element in an operand list 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{a} is completely modified with the contents of

variable @code{b}.  Real definition are also known as @dfn{killing

definitions}.  Similarly, the use of @code{b} reads all its bits.

In contrast, virtual operands are used with variables that can have

a partial or ambiguous reference.  This includes structures, arrays,

globals, and aliased variables.  In these cases, we have two types of

definitions.  For globals, structures, and arrays, we can determine from

a statement whether a variable of these types has a killing definition.

If the variable does, then the statement is marked as having a

@dfn{must definition} of that variable.  However, if a statement is only

defining a part of the variable (i.e.@: a field in a structure), or if we

know that a statement might define the variable but we cannot say for sure,

then we mark that statement as having a @dfn{may definition}.  For

instance, given

@smallexample

@{

  int a, b, *p;

  if (@dots{})

    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 (@dots{})

    p = &a;

  else

    p = &b;

  # a = VDEF <a>

  # b = VDEF <b>

  *p = 5;

  # VUSE <a>

  # VUSE <b>

  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 updated as soon as the statement is finished via a call

to @code{update_stmt}.  If statement elements are changed via

@code{SET_USE} or @code{SET_DEF}, then no further action is required

(i.e., those macros take care of updating the statement).  If changes

are made by manipulating the statement's tree directly, then a call

must be made to @code{update_stmt} when complete.  Calling one of the

@code{bsi_insert} routines or @code{bsi_replace} performs an implicit

call to @code{update_stmt}.

@subsection Operand Iterators And Access Routines

@cindex Operand Iterators

@cindex Operand Access Routines

Operands are collected by @file{tree-ssa-operands.c}.  They are stored

inside each statement's annotation and can be accessed through either the

operand iterators or an access routine.

The following access routines are available for examining operands:

@enumerate

@item @code{SINGLE_SSA_@{USE,DEF,TREE@}_OPERAND}: These accessors will return

NULL unless there is exactly one operand matching the specified flags.  If

there is exactly one operand, the operand is returned as either a @code{tree},

@code{def_operand_p}, or @code{use_operand_p}.

@smallexample

tree t = SINGLE_SSA_TREE_OPERAND (stmt, flags);

use_operand_p u = SINGLE_SSA_USE_OPERAND (stmt, SSA_ALL_VIRTUAL_USES);

def_operand_p d = SINGLE_SSA_DEF_OPERAND (stmt, SSA_OP_ALL_DEFS);

@end smallexample

@item @code{ZERO_SSA_OPERANDS}: This macro returns true if there are no

operands matching the specified flags.

@smallexample

if (ZERO_SSA_OPERANDS (stmt, SSA_OP_ALL_VIRTUALS))

  return;

@end smallexample

@item @code{NUM_SSA_OPERANDS}: This macro Returns the number of operands

matching 'flags'.  This actually executes a loop to perform the count, so

only use this if it is really needed.

@smallexample

int count = NUM_SSA_OPERANDS (stmt, flags)

@end smallexample

@end enumerate

If you wish to iterate over some or all operands, use the

@code{FOR_EACH_SSA_@{USE,DEF,TREE@}_OPERAND} iterator.  For example, to print

all the operands for a statement:

@smallexample

void

print_ops (tree stmt)

@{

  ssa_op_iter;

  tree var;

  FOR_EACH_SSA_TREE_OPERAND (var, stmt, iter, SSA_OP_ALL_OPERANDS)

    print_generic_expr (stderr, var, TDF_SLIM);

@}

@end smallexample

How to choose the appropriate iterator:

@enumerate

@item Determine whether you are need to see the operand pointers, or just the

trees, and choose the appropriate macro:

@smallexample

Need            Macro:

----            -------

use_operand_p   FOR_EACH_SSA_USE_OPERAND

def_operand_p   FOR_EACH_SSA_DEF_OPERAND

tree            FOR_EACH_SSA_TREE_OPERAND

@end smallexample

@item You need to declare a variable of the type you are interested

in, and an ssa_op_iter structure which serves as the loop controlling

variable.

@item Determine which operands you wish to use, and specify the flags of

those you are interested in.  They are documented in

@file{tree-ssa-operands.h}:

@smallexample

#define SSA_OP_USE              0x01    /* @r{Real USE operands.}  */

#define SSA_OP_DEF              0x02    /* @r{Real DEF operands.}  */

#define SSA_OP_VUSE             0x04    /* @r{VUSE operands.}  */

#define SSA_OP_VMAYUSE          0x08    /* @r{USE portion of VDEFS.}  */

#define SSA_OP_VDEF             0x10    /* @r{DEF portion of VDEFS.}  */

/* @r{These are commonly grouped operand flags.}  */

#define SSA_OP_VIRTUAL_USES     (SSA_OP_VUSE | SSA_OP_VMAYUSE)

#define SSA_OP_VIRTUAL_DEFS     (SSA_OP_VDEF)

#define SSA_OP_ALL_USES         (SSA_OP_VIRTUAL_USES | SSA_OP_USE)

#define SSA_OP_ALL_DEFS         (SSA_OP_VIRTUAL_DEFS | SSA_OP_DEF)

#define SSA_OP_ALL_OPERANDS     (SSA_OP_ALL_USES | SSA_OP_ALL_DEFS)

@end smallexample

@end enumerate

So if you want to look at the use pointers for all the @code{USE} and

@code{VUSE} operands, you would do something like:

@smallexample

  use_operand_p use_p;

  ssa_op_iter iter;

  FOR_EACH_SSA_USE_OPERAND (use_p, stmt, iter, (SSA_OP_USE | SSA_OP_VUSE))

    @{

      process_use_ptr (use_p);

    @}

@end smallexample

The @code{TREE} macro is basically the same as the @code{USE} and

@code{DEF} macros, only with the use or def dereferenced via

@code{USE_FROM_PTR (use_p)} and @code{DEF_FROM_PTR (def_p)}.  Since we

aren't using operand pointers, use and defs flags can be mixed.

@smallexample

  tree var;

  ssa_op_iter iter;

  FOR_EACH_SSA_TREE_OPERAND (var, stmt, iter, SSA_OP_VUSE)

    @{

       print_generic_expr (stderr, var, TDF_SLIM);

    @}

@end smallexample

@code{VDEF}s are broken into two flags, one for the

@code{DEF} portion (@code{SSA_OP_VDEF}) and one for the USE portion

(@code{SSA_OP_VMAYUSE}).  If all you want to look at are the

@code{VDEF}s together, there is a fourth iterator macro for this,

which returns both a def_operand_p and a use_operand_p for each

@code{VDEF} in the statement.  Note that you don't need any flags for

this one.

@smallexample

  use_operand_p use_p;

  def_operand_p def_p;

  ssa_op_iter iter;

  FOR_EACH_SSA_MAYDEF_OPERAND (def_p, use_p, stmt, iter)

    @{

      my_code;

    @}

@end smallexample

There are many examples in the code as well, as well as the

documentation in @file{tree-ssa-operands.h}.

There are also a couple of variants on the stmt iterators regarding PHI

nodes.

@code{FOR_EACH_PHI_ARG} Works exactly like

@code{FOR_EACH_SSA_USE_OPERAND}, except it works over @code{PHI} arguments

instead of statement operands.

@smallexample

/* Look at every virtual PHI use.  */

FOR_EACH_PHI_ARG (use_p, phi_stmt, iter, SSA_OP_VIRTUAL_USES)

@{

   my_code;

@}

/* Look at every real PHI use.  */

FOR_EACH_PHI_ARG (use_p, phi_stmt, iter, SSA_OP_USES)

  my_code;

/* Look at every PHI use.  */

FOR_EACH_PHI_ARG (use_p, phi_stmt, iter, SSA_OP_ALL_USES)

  my_code;

@end smallexample

@code{FOR_EACH_PHI_OR_STMT_@{USE,DEF@}} works exactly like

@code{FOR_EACH_SSA_@{USE,DEF@}_OPERAND}, except it will function on

either a statement or a @code{PHI} node.  These should be used when it is

appropriate but they are not quite as efficient as the individual

@code{FOR_EACH_PHI} and @code{FOR_EACH_SSA} routines.

@smallexample

FOR_EACH_PHI_OR_STMT_USE (use_operand_p, stmt, iter, flags)

  @{

     my_code;

  @}

FOR_EACH_PHI_OR_STMT_DEF (def_operand_p, phi, iter, flags)

  @{

     my_code;

  @}

@end smallexample

@subsection Immediate Uses

@cindex Immediate Uses

Immediate use information is now always available.  Using the immediate use

iterators, you may examine every use of any @code{SSA_NAME}. For instance,

to change each use of @code{ssa_var} to @code{ssa_var2} and call fold_stmt on

each stmt after that is done:

@smallexample

  use_operand_p imm_use_p;

  imm_use_iterator iterator;

  tree ssa_var, stmt;

  FOR_EACH_IMM_USE_STMT (stmt, iterator, ssa_var)

    @{

      FOR_EACH_IMM_USE_ON_STMT (imm_use_p, iterator)

        SET_USE (imm_use_p, ssa_var_2);

      fold_stmt (stmt);

    @}

@end smallexample

There are 2 iterators which can be used. @code{FOR_EACH_IMM_USE_FAST} is

used when the immediate uses are not changed, i.e., you are looking at the

uses, but not setting them.

If they do get changed, then care must be taken that things are not changed

under the iterators, so use the @code{FOR_EACH_IMM_USE_STMT} and

@code{FOR_EACH_IMM_USE_ON_STMT} iterators.  They attempt to preserve the

sanity of the use list by moving all the uses for a statement into

a controlled position, and then iterating over those uses.  Then the

optimization can manipulate the stmt when all the uses have been

processed.  This is a little slower than the FAST version since it adds a

placeholder element and must sort through the list a bit for each statement.

This placeholder element must be also be removed if the loop is

terminated early.  The macro @code{BREAK_FROM_IMM_USE_SAFE} is provided

to do this :

@smallexample

  FOR_EACH_IMM_USE_STMT (stmt, iterator, ssa_var)

    @{

      if (stmt == last_stmt)

        BREAK_FROM_SAFE_IMM_USE (iter);

      FOR_EACH_IMM_USE_ON_STMT (imm_use_p, iterator)

        SET_USE (imm_use_p, ssa_var_2);

      fold_stmt (stmt);

    @}

@end smallexample

There are checks in @code{verify_ssa} which verify that the immediate use list

is up to date, as well as checking that an optimization didn't break from the

loop without using this macro.  It is safe to simply 'break'; from a

@code{FOR_EACH_IMM_USE_FAST} traverse.

Some useful functions and macros:

@enumerate

@item  @code{has_zero_uses (ssa_var)} : Returns true if there are no uses of

@code{ssa_var}.

@item   @code{has_single_use (ssa_var)} : Returns true if there is only a

single use of @code{ssa_var}.

@item   @code{single_imm_use (ssa_var, use_operand_p *ptr, tree *stmt)} :

Returns true if there is only a single use of @code{ssa_var}, and also returns

the use pointer and statement it occurs in, in the second and third parameters.

@item   @code{num_imm_uses (ssa_var)} : Returns the number of immediate uses of

@code{ssa_var}. It is better not to use this if possible since it simply

utilizes a loop to count the uses.

@item  @code{PHI_ARG_INDEX_FROM_USE (use_p)} : Given a use within a @code{PHI}

node, return the index number for the use.  An assert is triggered if the use

isn't located in a @code{PHI} node.

@item  @code{USE_STMT (use_p)} : Return the statement a use occurs in.

@end enumerate

Note that uses are not put into an immediate use list until their statement is

actually inserted into the instruction stream via a @code{bsi_*} routine.

It is also still possible to utilize lazy updating of statements, but this

should be used only when absolutely required.  Both alias analysis and the

dominator optimizations currently do this.

When lazy updating is being used, the immediate use information is out of date

and cannot be used reliably.  Lazy updating is achieved by simply marking

statements modified via calls to @code{mark_stmt_modified} instead of

@code{update_stmt}.  When lazy updating is no longer required, all the

modified statements must have @code{update_stmt} called in order to bring them

up to date.  This must be done before the optimization is finished, or

@code{verify_ssa} will trigger an abort.

This is done with a simple loop over the instruction stream:

@smallexample

  block_stmt_iterator bsi;

  basic_block bb;

  FOR_EACH_BB (bb)

    @{

      for (bsi = bsi_start (bb); !bsi_end_p (bsi); bsi_next (&bsi))

        update_stmt_if_modified (bsi_stmt (bsi));

    @}

@end smallexample

@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.

@cindex PHI nodes

Sometimes, flow of control makes it impossible to determine 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 (@dots{})

  a_1 = 5;

else if (@dots{})

  a_2 = 2;

else

  a_3 = 13;

# a_4 = PHI <a_1, a_2, a_3>

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 update_ssa

@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 symbols or changed the program so that variables that

were previously aliased aren't anymore.  Whenever something like this

happens, the affected symbols must be renamed into SSA form again.

Transformations that emit new code or replicate existing statements

will also need to update the SSA form@.

Since GCC implements two different SSA forms for register and virtual

variables, keeping the SSA form up to date depends on whether you are

updating register or virtual names.  In both cases, the general idea

behind incremental SSA updates is similar: when new SSA names are

created, they typically are meant to replace other existing names in

the program@.

For instance, given the following code:

@smallexample

     1  L0:

     2  x_1 = PHI (0, x_5)

     3  if (x_1 < 10)

     4    if (x_1 > 7)

     5      y_2 = 0

     6    else

     7      y_3 = x_1 + x_7

     8    endif

     9    x_5 = x_1 + 1

     10   goto L0;

     11 endif

@end smallexample

Suppose that we insert new names @code{x_10} and @code{x_11} (lines

@code{4} and @code{8})@.

@smallexample

     1  L0:

     2  x_1 = PHI (0, x_5)

     3  if (x_1 < 10)

     4    x_10 = @dots{}

     5    if (x_1 > 7)

     6      y_2 = 0

     7    else

     8      x_11 = @dots{}

     9      y_3 = x_1 + x_7

     10   endif

     11   x_5 = x_1 + 1

     12   goto L0;

     13 endif

@end smallexample

We want to replace all the uses of @code{x_1} with the new definitions

of @code{x_10} and @code{x_11}.  Note that the only uses that should

be replaced are those at lines @code{5}, @code{9} and @code{11}.

Also, the use of @code{x_7} at line @code{9} should @emph{not} be

replaced (this is why we cannot just mark symbol @code{x} for

renaming)@.

Additionally, we may need to insert a PHI node at line @code{11}

because that is a merge point for @code{x_10} and @code{x_11}.  So the

use of @code{x_1} at line @code{11} will be replaced with the new PHI

node.  The insertion of PHI nodes is optional.  They are not strictly

necessary to preserve the SSA form, and depending on what the caller

inserted, they may not even be useful for the optimizers@.

Updating the SSA form is a two step process.  First, the pass has to

identify which names need to be updated and/or which symbols need to

be renamed into SSA form for the first time.  When new names are

introduced to replace existing names in the program, the mapping

between the old and the new names are registered by calling

@code{register_new_name_mapping} (note that if your pass creates new

code by duplicating basic blocks, the call to @code{tree_duplicate_bb}

will set up the necessary mappings automatically).  On the other hand,

if your pass exposes a new symbol that should be put in SSA form for

the first time, the new symbol should be registered with

@code{mark_sym_for_renaming}.

After the replacement mappings have been registered and new symbols

marked for renaming, a call to @code{update_ssa} makes the registered

changes.  This can be done with an explicit call or by creating

@code{TODO} flags in the @code{tree_opt_pass} structure for your pass.

There are several @code{TODO} flags that control the behavior of

@code{update_ssa}:

@itemize @bullet

@item @code{TODO_update_ssa}.  Update the SSA form inserting PHI nodes

for newly exposed symbols and virtual names marked for updating.

When updating real names, only insert PHI nodes for a real name

@code{O_j} in blocks reached by all the new and old definitions for

@code{O_j}.  If the iterated dominance frontier for @code{O_j}

is not pruned, we may end up inserting PHI nodes in blocks that

have one or more edges with no incoming definition for

@code{O_j}.  This would lead to uninitialized warnings for

@code{O_j}'s symbol@.

@item @code{TODO_update_ssa_no_phi}.  Update the SSA form without

inserting any new PHI nodes at all.  This is used by passes that

have either inserted all the PHI nodes themselves or passes that

need only to patch use-def and def-def chains for virtuals

(e.g., DCE)@.

@item @code{TODO_update_ssa_full_phi}.  Insert PHI nodes everywhere

they are needed.  No pruning of the IDF is done.  This is used

by passes that need the PHI nodes for @code{O_j} even if it

means that some arguments will come from the default definition

of @code{O_j}'s symbol (e.g., @code{pass_linear_transform})@.

WARNING: If you need to use this flag, chances are that your

pass may be doing something wrong.  Inserting PHI nodes for an

old name where not all edges carry a new replacement may lead to

silent codegen errors or spurious uninitialized warnings@.

@item @code{TODO_update_ssa_only_virtuals}.  Passes that update the

SSA form on their own may want to delegate the updating of

virtual names to the generic updater.  Since FUD chains are

easier to maintain, this simplifies the work they need to do.

NOTE: If this flag is used, any OLD->NEW mappings for real names

are explicitly destroyed and only the symbols marked for

renaming are processed@.

@end itemize

@subsection Preserving the virtual SSA form

@cindex preserving virtual SSA form

The virtual SSA form is harder to preserve than the non-virtual SSA form

mainly because the set of virtual operands for a statement may change at

what some would consider unexpected times.  In general, statement

modifications should be bracketed between calls to

@code{push_stmt_changes} and @code{pop_stmt_changes}.  For example,

@smallexample

    munge_stmt (tree stmt)

    @{

       push_stmt_changes (&stmt);

       @dots{} rewrite STMT @dots{}

       pop_stmt_changes (&stmt);

    @}

@end smallexample

The call to @code{push_stmt_changes} saves the current state of the

statement operands and the call to @code{pop_stmt_changes} compares

the saved state with the current one and does the appropriate symbol

marking for the SSA renamer.

It is possible to modify several statements at a time, provided that

@code{push_stmt_changes} and @code{pop_stmt_changes} are called in

LIFO order, as when processing a stack of statements.

Additionally, if the pass discovers that it did not need to make

changes to the statement after calling @code{push_stmt_changes}, it

can simply discard the topmost change buffer by calling

@code{discard_stmt_changes}.  This will avoid the expensive operand

re-scan operation and the buffer comparison that determines if symbols

need to be marked for renaming.

@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 in GIMPLE SSA form consists of two pieces.  First

the virtual SSA web ties conflicting memory accesses and provides

a SSA use-def chain and SSA immediate-use chains for walking

possibly dependent memory accesses.  Second an alias-oracle can

be queried to disambiguate explicit and implicit memory references.

@enumerate

@item Memory SSA form.

All statements that may use memory have exactly one accompanied use of

a virtual SSA name that represents the state of memory at the

given point in the IL.

All statements that may define memory have exactly one accompanied

definition of a virtual SSA name using the previous state of memory

and defining the new state of memory after the given point in the IL.

@smallexample

int i;

int foo (void)

@{

  # .MEM_3 = VDEF <.MEM_2(D)>

  i = 1;

  # VUSE <.MEM_3>

  return i;

@}

@end smallexample

The virtual SSA names in this case are @code{.MEM_2(D)} and

@code{.MEM_3}.  The store to the global variable @code{i}

defines @code{.MEM_3} invalidating @code{.MEM_2(D)}.  The

load from @code{i} uses that new state @code{.MEM_3}.

The virtual SSA web serves as constraints to SSA optimizers

preventing illegitimate code-motion and optimization.  It

also provides a way to walk related memory statements.

@item Points-to and escape analysis.

Points-to analysis builds a set of constraints from the GIMPLE

SSA IL representing all pointer operations and facts we do

or do not know about pointers.  Solving this set of constraints

yields a conservatively correct solution for each pointer

variable in the program (though we are only interested in

SSA name pointers) as to what it may possibly point to.

This points-to solution for a given SSA name pointer is stored

in the @code{pt_solution} sub-structure of the

@code{SSA_NAME_PTR_INFO} record.  The following accessor

functions are available:

@itemize @bullet

@item @code{pt_solution_includes}

@item @code{pt_solutions_intersect}

@end itemize

Points-to analysis also computes the solution for two special

set of pointers, @code{ESCAPED} and @code{CALLUSED}.  Those

represent all memory that has escaped the scope of analysis

or that is used by pure or nested const calls.

@item Type-based alias analysis

Type-based alias analysis is frontend dependent though generic

support is provided by the middle-end in @code{alias.c}.  TBAA

code is used by both tree optimizers and RTL optimizers.

Every language that wishes to perform language-specific alias analysis

should define a function that computes, given a @code{tree}

node, an alias set for the node.  Nodes in different alias sets are not

allowed to alias.  For an example, see the C front-end function

@code{c_get_alias_set}.

@item Tree alias-oracle

The tree alias-oracle provides means to disambiguate two memory

references and memory references against statements.  The following

queries are available:

@itemize @bullet

@item @code{refs_may_alias_p}

@item @code{ref_maybe_used_by_stmt_p}

@item @code{stmt_may_clobber_ref_p}

@end itemize

In addition to those two kind of statement walkers are available

walking statements related to a reference ref.

@code{walk_non_aliased_vuses} walks over dominating memory defining

statements and calls back if the statement does not clobber ref

providing the non-aliased VUSE.  The walk stops at

the first clobbering statement or if asked to.

@code{walk_aliased_vdefs} walks over dominating memory defining

statements and calls back on each statement clobbering ref

providing its aliasing VDEF.  The walk stops if asked to.

@end enumerate

@node Memory model

@section Memory model

@cindex memory model

The memory model used by the middle-end models that of the C/C++

languages.  The middle-end has the notion of an effective type

of a memory region which is used for type-based alias analysis.

The following is a refinement of ISO C99 6.5/6, clarifying the block copy case

to follow common sense and extending the concept of a dynamic effective

type to objects with a declared type as required for C++.

@smallexample

The effective type of an object for an access to its stored value is

the declared type of the object or the effective type determined by

a previous store to it.  If a value is stored into an object through

an lvalue having a type that is not a character type, then the

type of the lvalue becomes the effective type of the object for that

access and for subsequent accesses that do not modify the stored value.

If a value is copied into an object using @code{memcpy} or @code{memmove},

or is copied as an array of character type, then the effective type

of the modified object for that access and for subsequent accesses that

do not modify the value is undetermined.  For all other accesses to an

object, the effective type of the object is simply the type of the

lvalue used for the access.

@end smallexample