path: root/gcc/doc/tree-ssa.texi

@c Copyright (c) 2004, 2005, 2007, 2008 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 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.
@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{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 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 proceeds in 4 main phases:

@enumerate
@item   Structural alias analysis.

This phase walks the types for structure variables, and determines which
of the fields can overlap using offset and size of each field.  For each
field, a ``subvariable'' called a ``Structure field tag'' (SFT)@ is
created, which represents that field as a separate variable.  All
accesses that could possibly overlap with a given field will have
virtual operands for the SFT of that field.

@smallexample
struct foo
@{
  int a;
  int b;
@}
struct foo temp;
int bar (void)
@{
  int tmp1, tmp2, tmp3;
  SFT.0_2 = VDEF <SFT.0_1>
  temp.a = 5;
  SFT.1_4 = VDEF <SFT.1_3>
  temp.b = 6;
  
  VUSE <SFT.1_4>
  tmp1_5 = temp.b;
  VUSE <SFT.0_2>
  tmp2_6 = temp.a;

  tmp3_7 = tmp1_5 + tmp2_6;
  return tmp3_7;
@}
@end smallexample

If you copy the symbol tag for a variable for some reason, you probably
also want to copy the subvariables for that variable.

@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 ``symbol memory tag'' (SMT)@.  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 symbol 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 symbol memory tag and
every addressable variable found in the program.  Given a symbol
memory tag SMT and an addressable variable V@.  If the alias sets
of SMT and V conflict (as computed by may_alias_p), then V is
marked as an alias tag and added to the alias set of SMT@.

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}.
@end enumerate

For instance, consider the following function:

@smallexample
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 smallexample

After aliasing analysis has finished, the symbol 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}.

@smallexample
foo (int i)
@{
  int *p, a, b;

  if (i_2 > 10)
    p_4 = &a;
  else
    p_6 = &b;
  # p_1 = PHI <p_4(1), p_6(2)>;

  # a_7 = VDEF <a_3>;
  # b_8 = VDEF <b_5>;
  *p_1 = 3;

  # a_9 = VDEF <a_7>
  # VUSE <b_8>
  a_9 = b_8 + 2;

  # VUSE <a_9>;
  # VUSE <b_8>;
  return *p_1;
@}
@end smallexample

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, @dots{}, 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 @}
@dots{}
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