tree: 25f37905b0a8c9e88a429c675ac2dec0fda8156e [search]
  1. build/
  2. mergeSort/
  3. qsort/
  4. size/
  5. sym/
  6. vcgen/
  7. .gitignore
  8. accumulate_profile.py
  9. arith_eval.ml
  10. binarytrees.ghc-6.hs
  11. binarytrees.ocaml-2.ml
  12. binarytrees.st.hs
  13. binarytrees.st.mlton-2.sml
  14. binarytrees.st.sml
  15. binarytrees.st.swift
  16. binarytrees.swift
  17. binarytrees5.ml
  18. binarytrees5_multicore.ml
  19. compile.sh
  20. const_fold.hs
  21. const_fold.ml
  22. const_fold.sml
  23. const_fold.swift
  24. cross.yaml
  25. dag_hassorry_issue.lean
  26. dag_hassorry_issue.lean.args
  27. dag_hassorry_issue.lean.out.expected
  28. delayed_assign.lean
  29. deriv.hs
  30. deriv.ml
  31. deriv.sml
  32. deriv.swift
  33. flake.lock
  34. flake.nix
  35. full-stdlib.exec.yaml
  36. ghc-gc.py
  37. lean-gc.py
  38. Makefile
  39. mlkit-gc.py
  40. ocaml-gc.py
  41. perf.py
  42. qsort.hs
  43. qsort.ml
  44. qsort.sml
  45. qsort.swift
  46. rbmap.hs
  47. rbmap.ml
  48. rbmap.sml
  49. rbmap.swift
  50. rbmap2.lean
  51. rbmap3.lean
  52. rbmap500k.lean
  53. rbmap_checkpoint.hs
  54. rbmap_checkpoint.ml
  55. rbmap_checkpoint.sml
  56. rbmap_checkpoint.swift
  57. rbmap_checkpoint2.lean
  58. rbmap_checkpoint2.sml
  59. rbmap_checkpoint_cpp_lean3.cpp
  60. rbmap_checkpoint_cpp_std.cpp
  61. rbmap_cpp_lean3.cpp
  62. rbmap_cpp_std.cpp
  63. README.md
  64. report.py
  65. run.sh
  66. speedcenter.yaml
  67. states35.lean
  68. test_single.sh
  69. unionfind_clean.lean
tests/bench/README.md

Lean Benchmark Suites

This folder contains multiple small Lean programs for benchmarking used by two separate benchmark suites based on the temci benchmarking tool:

  • The light-weight “Speedcenter” suite benchmarks the current build of Lean. It can be used for quick comparisons on the cmdline and powers the Lean Speedcenter website.
  • The heavy-weight “Cross” suite benchmarks multiple Lean configurations and other functional compilers against each other and generates CSV and HTML reports from that. It was created for the paper “Counting Immutable Beans - Reference Counting Optimized for Purely Functional Programming” (IFL19).

Speedcenter Suite

Requirements:

  • A local Lean build in ../../build/release. Build at least the bin target.
  • temci. Using Nix, open a nix-shell in the project root directory to add a compatible version to your PATH. Alternatively, try pip3 install git+https://github.com/parttimenerd/temci.git.

To execute the suite and save the results in base.yaml, run (in this folder)

temci exec --config speedcenter.yaml --out base.yaml

Other interesting exec flags:

  • use --runs N to modify the default number of 10 runs per benchmark
  • use --included_blocks fast to excluded slow benchmarks like the stdlib benchmark. You can replace fast with any benchmark name or label in speedcenter.exec.yaml.

If you have multiple saved result files, you can compare them with

temci report --config speedcenter.yaml report1.yaml report2.yaml ...

Cross Suite

We recommend using Nix for building/obtaining all Lean variants and used compilers in a reproducible way. After installing Nix, running the benchmarks is as easy as

nix develop
make

This will record 50 runs for each benchmark configuration (this can be changed with runs in cross.yaml), generate results in report_lean.csv and report_cross.csv, and print them to stdout in a tabulated format. It will also generate HTML reports in report/ comparing the time-based benchmarks.

In order to reduce noise in the benchmarking data, you may instead want to try calling make inside a temci shell:

temci short shell --sudo --preset usable --cpuset_active make

Using root powers, this will temporarily configure your machine similarly to the LLVM benchmarking recommendations and move all your other processes to a single CPU core.