Use llvm::erase_value (NFC)

[llvm] Fix comment typos (NFC)

Remove unneeded cl::ZeroOrMore for cl::opt options

Similar to 557efc9a8b68628c2c944678c6471dac30ed9e8e.
This commit handles options where cl::ZeroOrMore is more than one line below
cl::opt.

speeding up ext-tsp for huge instances

Differential Revision: https://reviews.llvm.org/D120780

Cleanup includes: TransformsUtils

Estimation on the impact on preprocessor output:
before: 1065307662
after: 1064800684

Discourse thread: https://discourse.llvm.org/t/include-what-you-use-include-

Cleanup includes: TransformsUtils

Estimation on the impact on preprocessor output:
before: 1065307662
after: 1064800684

Discourse thread: https://discourse.llvm.org/t/include-what-you-use-include-cleanup
Differential Revision: https://reviews.llvm.org/D120741

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[llvm] Use = default (NFC)

[CSSPGO] Turn on ext-tsp by default for CSSPGO.

I'm seeing ext-tsp helps CSSPGO for our intern large benchmarks so I'm turning on it for CSSPGO. For non-CS AutoFDO, ext-tsp doesn't seem to help, pro

[CSSPGO] Turn on ext-tsp by default for CSSPGO.

I'm seeing ext-tsp helps CSSPGO for our intern large benchmarks so I'm turning on it for CSSPGO. For non-CS AutoFDO, ext-tsp doesn't seem to help, probably because of lower profile counts quality.

Reviewed By: wenlei

Differential Revision: https://reviews.llvm.org/D119048

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ext-tsp basic block layout

A new basic block ordering improving existing MachineBlockPlacement.

The algorithm tries to find a layout of nodes (basic blocks) of a given CFG
optimizing jump locality

ext-tsp basic block layout

A new basic block ordering improving existing MachineBlockPlacement.

The algorithm tries to find a layout of nodes (basic blocks) of a given CFG
optimizing jump locality and thus processor I-cache utilization. This is
achieved via increasing the number of fall-through jumps and co-locating
frequently executed nodes together. The name follows the underlying
optimization problem, Extended-TSP, which is a generalization of classical
(maximum) Traveling Salesmen Problem.

The algorithm is a greedy heuristic that works with chains (ordered lists)
of basic blocks. Initially all chains are isolated basic blocks. On every
iteration, we pick a pair of chains whose merging yields the biggest increase
in the ExtTSP value, which models how i-cache "friendly" a specific chain is.
A pair of chains giving the maximum gain is merged into a new chain. The
procedure stops when there is only one chain left, or when merging does not
increase ExtTSP. In the latter case, the remaining chains are sorted by
density in decreasing order.

An important aspect is the way two chains are merged. Unlike earlier
algorithms (e.g., based on the approach of Pettis-Hansen), two
chains, X and Y, are first split into three, X1, X2, and Y. Then we
consider all possible ways of gluing the three chains (e.g., X1YX2, X1X2Y,
X2X1Y, X2YX1, YX1X2, YX2X1) and choose the one producing the largest score.
This improves the quality of the final result (the search space is larger)
while keeping the implementation sufficiently fast.

Differential Revision: https://reviews.llvm.org/D113424

show more ...

ext-tsp basic block layout

A new basic block ordering improving existing MachineBlockPlacement.

The algorithm tries to find a layout of nodes (basic blocks) of a given CFG
optimizing jump locality

ext-tsp basic block layout

A new basic block ordering improving existing MachineBlockPlacement.

The algorithm tries to find a layout of nodes (basic blocks) of a given CFG
optimizing jump locality and thus processor I-cache utilization. This is
achieved via increasing the number of fall-through jumps and co-locating
frequently executed nodes together. The name follows the underlying
optimization problem, Extended-TSP, which is a generalization of classical
(maximum) Traveling Salesmen Problem.

The algorithm is a greedy heuristic that works with chains (ordered lists)
of basic blocks. Initially all chains are isolated basic blocks. On every
iteration, we pick a pair of chains whose merging yields the biggest increase
in the ExtTSP value, which models how i-cache "friendly" a specific chain is.
A pair of chains giving the maximum gain is merged into a new chain. The
procedure stops when there is only one chain left, or when merging does not
increase ExtTSP. In the latter case, the remaining chains are sorted by
density in decreasing order.

An important aspect is the way two chains are merged. Unlike earlier
algorithms (e.g., based on the approach of Pettis-Hansen), two
chains, X and Y, are first split into three, X1, X2, and Y. Then we
consider all possible ways of gluing the three chains (e.g., X1YX2, X1X2Y,
X2X1Y, X2YX1, YX1X2, YX2X1) and choose the one producing the largest score.
This improves the quality of the final result (the search space is larger)
while keeping the implementation sufficiently fast.

Differential Revision: https://reviews.llvm.org/D113424

show more ...