Sink an otherwise unused variable's initializer into the asserts that
used it. Fixes an unused variable warning from GCC on release builds.

llvm-svn: 142799

Now that we have comparison on probabilities, add some static functions
to get important constant branch probabilities and use them for finding
the best branch out of a set of possibilities.

llvm-sv

Now that we have comparison on probabilities, add some static functions
to get important constant branch probabilities and use them for finding
the best branch out of a set of possibilities.

llvm-svn: 142762

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Remove a commented out line of code that snuck by my auditing.

llvm-svn: 142761

Completely re-write the algorithm behind MachineBlockPlacement based on
discussions with Andy. Fundamentally, the previous algorithm is both
counter productive on several fronts and prioritizing thin

Completely re-write the algorithm behind MachineBlockPlacement based on
discussions with Andy. Fundamentally, the previous algorithm is both
counter productive on several fronts and prioritizing things which
aren't necessarily the most important: static branch prediction.

The new algorithm uses the existing loop CFG structure information to
walk through the CFG itself to layout blocks. It coalesces adjacent
blocks within the loop where the CFG allows based on the most likely
path taken. Finally, it topologically orders the block chains that have
been formed. This allows it to choose a (mostly) topologically valid
ordering which still priorizes fallthrough within the structural
constraints.

As a final twist in the algorithm, it does violate the CFG when it
discovers a "hot" edge, that is an edge that is more than 4x hotter than
the competing edges in the CFG. These are forcibly merged into
a fallthrough chain.

Future transformations that need te be added are rotation of loop exit
conditions to be fallthrough, and better isolation of cold block chains.
I'm also planning on adding statistics to model how well the algorithm
does at laying out blocks based on the probabilities it receives.

The old tests mostly still pass, and I have some new tests to add, but
the nested loops are still behaving very strangely. This almost seems
like working-as-intended as it rotated the exit branch to be
fallthrough, but I'm not convinced this is actually the best layout. It
is well supported by the probabilities for loops we currently get, but
those are pretty broken for nested loops, so this may change later.

llvm-svn: 142743

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Add loop aligning to MachineBlockPlacement based on review discussion so
it's a bit more plausible to use this instead of CodePlacementOpt. The
code for this was shamelessly stolen from CodePlacement

Add loop aligning to MachineBlockPlacement based on review discussion so
it's a bit more plausible to use this instead of CodePlacementOpt. The
code for this was shamelessly stolen from CodePlacementOpt, and then
trimmed down a bit. There doesn't seem to be much utility in returning
true/false from this pass as we may or may not have rewritten all of the
blocks. Also, the statistic of counting how many loops were aligned
doesn't seem terribly important so I removed it. If folks would like it
to be included, I'm happy to add it back.

This was probably the most egregious of the missing features, and now
I'm going to start gathering some performance numbers and looking at
specific loop structures that have different layout between the two.

Test is updated to include both basic loop alignment and nested loop
alignment.

llvm-svn: 142645

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Implement a block placement pass based on the branch probability and
block frequency analyses. This differs substantially from the existing
block-placement pass in LLVM:

1) It operates on the Machin

Implement a block placement pass based on the branch probability and
block frequency analyses. This differs substantially from the existing
block-placement pass in LLVM:

1) It operates on the Machine-IR in the CodeGen layer. This exposes much
more (and more precise) information and opportunities. Also, the
results are more stable due to fewer transforms ocurring after the
pass runs.
2) It uses the generalized probability and frequency analyses. These can
model static heuristics, code annotation derived heuristics as well
as eventual profile loading. By basing the optimization on the
analysis interface it can work from any (or a combination) of these
inputs.
3) It uses a more aggressive algorithm, both building chains from tho
bottom up to maximize benefit, and using an SCC-based walk to layout
chains of blocks in a profitable ordering without O(N^2) iterations
which the old pass involves.

The pass is currently gated behind a flag, and not enabled by default
because it still needs to grow some important features. Most notably, it
needs to support loop aligning and careful layout of loop structures
much as done by hand currently in CodePlacementOpt. Once it supports
these, and has sufficient testing and quality tuning, it should replace
both of these passes.

Thanks to Nick Lewycky and Richard Smith for help authoring & debugging
this, and to Jakob, Andy, Eric, Jim, and probably a few others I'm
forgetting for reviewing and answering all my questions. Writing
a backend pass is *sooo* much better now than it used to be. =D

llvm-svn: 142641

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