Propagation of profile samples through the CFG.

This adds a propagation heuristic to convert instruction samples
into branch weights. It implements a similar heuristic to the one
implemented by Dehao Chen on GCC.

The propagation proceeds in 3 phases:

1- Assignment of block weights. All the basic blocks in the function
   are initial assigned the same weight as their most frequently
   executed instruction.

2- Creation of equivalence classes. Since samples may be missing from
   blocks, we can fill in the gaps by setting the weights of all the
   blocks in the same equivalence class to the same weight. To compute
   the concept of equivalence, we use dominance and loop information.
   Two blocks B1 and B2 are in the same equivalence class if B1
   dominates B2, B2 post-dominates B1 and both are in the same loop.

3- Propagation of block weights into edges. This uses a simple
   propagation heuristic. The following rules are applied to every
   block B in the CFG:

   - If B has a single predecessor/successor, then the weight
     of that edge is the weight of the block.

   - If all the edges are known except one, and the weight of the
     block is already known, the weight of the unknown edge will
     be the weight of the block minus the sum of all the known
     edges. If the sum of all the known edges is larger than B's weight,
     we set the unknown edge weight to zero.

   - If there is a self-referential edge, and the weight of the block is
     known, the weight for that edge is set to the weight of the block
     minus the weight of the other incoming edges to that block (if
     known).

Since this propagation is not guaranteed to finalize for every CFG, we
only allow it to proceed for a limited number of iterations (controlled
by -sample-profile-max-propagate-iterations). It currently uses the same
GCC default of 100.

Before propagation starts, the pass builds (for each block) a list of
unique predecessors and successors. This is necessary to handle
identical edges in multiway branches. Since we visit all blocks and all
edges of the CFG, it is cleaner to build these lists once at the start
of the pass.

Finally, the patch fixes the computation of relative line locations.
The profiler emits lines relative to the function header. To discover
it, we traverse the compilation unit looking for the subprogram
corresponding to the function. The line number of that subprogram is the
line where the function begins. That becomes line zero for all the
relative locations.

git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@198972 91177308-0d34-0410-b5e6-96231b3b80d8
Extend and simplify the sample profile input file.

1- Use the line_iterator class to read profile files.

2- Allow comments in profile file. Lines starting with '#'
   are completely ignored while reading the profile.

3- Add parsing support for discriminators and indirect call samples.

   Our external profiler can emit more profile information that we are
   currently not handling. This patch does not add new functionality to
   support this information, but it allows profile files to provide it.

   I will add actual support later on (for at least one of these
   features, I need support for DWARF discriminators in Clang).

   A sample line may contain the following additional information:

   Discriminator. This is used if the sampled program was compiled with
   DWARF discriminator support
   (http://wiki.dwarfstd.org/index.php?title=Path_Discriminators). This
   is currently only emitted by GCC and we just ignore it.

   Potential call targets and samples. If present, this line contains a
   call instruction. This models both direct and indirect calls. Each
   called target is listed together with the number of samples. For
   example,

                    130: 7  foo:3  bar:2  baz:7

   The above means that at relative line offset 130 there is a call
   instruction that calls one of foo(), bar() and baz(). With baz()
   being the relatively more frequent call target.

   Differential Revision: http://llvm-reviews.chandlerc.com/D2355

4- Simplify format of profile input file.

   This implements earlier suggestions to simplify the format of the
   sample profile file. The symbol table is not necessary and function
   profiles do not need to know the number of samples in advance.

   Differential Revision: http://llvm-reviews.chandlerc.com/D2419

git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@198973 91177308-0d34-0410-b5e6-96231b3b80d8