[all-commits] [llvm/llvm-project] 540489: [llvm-profdata] Implement llvm-profdata overlap fo...

[WenleiHe via All-commits]

  Branch: refs/heads/master
  Home:   https://github.com/llvm/llvm-project
  Commit: 540489de6816486f98221952d7a54f0293c68d1e
      https://github.com/llvm/llvm-project/commit/540489de6816486f98221952d7a54f0293c68d1e
  Author: weihe <weihe at dev103.prn2.facebook.com>
  Date:   2020-08-08 (Sat, 08 Aug 2020)

  Changed paths:
    A llvm/test/tools/llvm-profdata/Inputs/sample-overlap-0.proftext
    A llvm/test/tools/llvm-profdata/Inputs/sample-overlap-1.proftext
    A llvm/test/tools/llvm-profdata/Inputs/sample-overlap-2.proftext
    A llvm/test/tools/llvm-profdata/Inputs/sample-overlap-3.proftext
    A llvm/test/tools/llvm-profdata/Inputs/sample-overlap-4.proftext
    A llvm/test/tools/llvm-profdata/Inputs/sample-overlap-5.proftext
    A llvm/test/tools/llvm-profdata/sample-overlap.test
    M llvm/tools/llvm-profdata/llvm-profdata.cpp

  Log Message:
  -----------
  [llvm-profdata] Implement llvm-profdata overlap for sample profiles

Implemented the `llvm-profdata overlap` feature for sample profiles. It reports weighted //similarity// and unweighted //overlap// metrics at program and function level for two input profiles. Similarity metrics are symmetric with regards to the order of two input profiles. By default, the tool only reports program-level summary. Users can look into function-level details via additional options `--function`, `--similarity-cutoff`, and `--value-cutoff`.

The similarity metrics are designed as follows:
* Program-level summary
    * Whole program profile similarity is an aggregate over function-level similarity `FS`: `PS = sum(FS(A) * avg_weight(A))` for all function `A`.
    * Whole program sample overlap: `PSO = common_samples / total_samples`.
    * Function overlap: `FO = #common_function / #total_function`.
    * Hot-function overlap: `HFO = #common_hot_function / #total_hot_function`.
    * Hot-block overlap: `HBO = #common_hot_block / #total_hot_block`.
* Function-level details
    * Function-level similarity is an aggregate over line/block-level similarities `BS` of all sample lines/blocks in the function, weighted by the closeness of the function's weights in two profiles: `FS = sum(BS(i)) * (1 - weight_distance(A))`.
    * Function-level sample overlap: `FSO = common_samples / total_samples` for samples in the function.

Reviewed By: wenlei, hoyFB, wmi

Differential Revision: https://reviews.llvm.org/D83852