Skip to content

Conversation

mhauru
Copy link
Member

@mhauru mhauru commented Sep 29, 2025

Now that the "del" flag is gone (#1058), the only flag that is ever used is "trans". Hence, no need to bother with having the Dict{String, BitVector} for Metadata.flags, and can instead have a single BitVector for Metadata.trans. EDIT: Renamed to Metadata.is_transformed.

You may wonder, given that Metadata is presumably on its way out, why bother? Two reasons:

  • I tried running the benchmark suite locally with VectorVarInfo, and there were some horrendous performance regressions there compared to using Metadata. Hence, we might not be about to switch over the VarNamedVector imminently.
  • The above experience made me wonder why there was such a performance difference, and whether the Metadata.flags field might actually be a significant cost compared to a BitVector.

My local benchmarking suggests that indeed, this makes a difference:

Before

┌───────────────────────┬───────┬─────────────┬───────────────────┬────────┬────────────────┬─────────────────┐
│                 Model │   Dim │  AD Backend │           VarInfo │ Linked │ t(eval)/t(ref) │ t(grad)/t(eval) │
├───────────────────────┼───────┼─────────────┼───────────────────┼────────┼────────────────┼─────────────────┤
│ Simple assume observe │     1 │ forwarddiff │             typed │  false │           16.0 │             1.7 │
│           Smorgasbord │   201 │ forwarddiff │             typed │  false │          790.6 │            46.1 │
│           Smorgasbord │   201 │ forwarddiff │ simple_namedtuple │   true │          382.0 │            84.3 │
│           Smorgasbord │   201 │ forwarddiff │           untyped │   true │         1431.7 │            36.0 │
│           Smorgasbord │   201 │ forwarddiff │       simple_dict │   true │        10511.1 │            21.6 │
│           Smorgasbord │   201 │ reversediff │             typed │   true │         1495.9 │            42.4 │
│           Smorgasbord │   201 │    mooncake │             typed │   true │         1637.4 │             3.4 │
│    Loop univariate 1k │  1000 │    mooncake │             typed │   true │         8635.9 │             3.2 │
│       Multivariate 1k │  1000 │    mooncake │             typed │   true │         1266.1 │             8.5 │
│   Loop univariate 10k │ 10000 │    mooncake │             typed │   true │        90116.3 │             3.2 │
│      Multivariate 10k │ 10000 │    mooncake │             typed │   true │        10364.2 │             9.7 │
│               Dynamic │    10 │    mooncake │             typed │   true │          235.0 │             5.7 │
│              Submodel │     1 │    mooncake │             typed │   true │           24.0 │             4.2 │
│                   LDA │    12 │ reversediff │             typed │   true │         1391.7 │             2.0 │
└───────────────────────┴───────┴─────────────┴───────────────────┴────────┴────────────────┴─────────────────┘

After

┌───────────────────────┬───────┬─────────────┬───────────────────┬────────┬────────────────┬─────────────────┐
│                 Model │   Dim │  AD Backend │           VarInfo │ Linked │ t(eval)/t(ref) │ t(grad)/t(eval) │
├───────────────────────┼───────┼─────────────┼───────────────────┼────────┼────────────────┼─────────────────┤
│ Simple assume observe │     1 │ forwarddiff │             typed │  false │           10.8 │             2.5 │
│           Smorgasbord │   201 │ forwarddiff │             typed │  false │          695.1 │            53.0 │
│           Smorgasbord │   201 │ forwarddiff │ simple_namedtuple │   true │          319.1 │           104.9 │
│           Smorgasbord │   201 │ forwarddiff │           untyped │   true │         1114.3 │            45.0 │
│           Smorgasbord │   201 │ forwarddiff │       simple_dict │   true │        10323.5 │            22.3 │
│           Smorgasbord │   201 │ reversediff │             typed │   true │         1190.0 │            52.4 │
│           Smorgasbord │   201 │    mooncake │             typed │   true │         1263.0 │             3.8 │
│    Loop univariate 1k │  1000 │    mooncake │             typed │   true │         5606.7 │             4.4 │
│       Multivariate 1k │  1000 │    mooncake │             typed │   true │         1236.0 │             8.7 │
│   Loop univariate 10k │ 10000 │    mooncake │             typed │   true │        63260.7 │             4.2 │
│      Multivariate 10k │ 10000 │    mooncake │             typed │   true │        11029.4 │             9.4 │
│               Dynamic │    10 │    mooncake │             typed │   true │          216.4 │             6.4 │
│              Submodel │     1 │    mooncake │             typed │   true │           19.0 │             4.6 │
│                   LDA │    12 │ reversediff │             typed │   true │         1341.4 │             2.0 │
└───────────────────────┴───────┴─────────────┴───────────────────┴────────┴────────────────┴─────────────────┘

Curious to see whether GHA benchmarks come out looking similar.

Copy link
Contributor

github-actions bot commented Sep 29, 2025

Benchmark Report for Commit a011dd6

Computer Information

Julia Version 1.11.7
Commit f2b3dbda30a (2025-09-08 12:10 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
  CPU: 4 × AMD EPYC 7763 64-Core Processor
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, znver3)
Threads: 1 default, 0 interactive, 1 GC (on 4 virtual cores)

Benchmark Results

┌───────────────────────┬───────┬─────────────┬───────────────────┬────────┬────────────────┬─────────────────┐
│                 Model │   Dim │  AD Backend │           VarInfo │ Linked │ t(eval)/t(ref) │ t(grad)/t(eval) │
├───────────────────────┼───────┼─────────────┼───────────────────┼────────┼────────────────┼─────────────────┤
│ Simple assume observe │     1 │ forwarddiff │             typed │  false │            7.4 │             1.6 │
│           Smorgasbord │   201 │ forwarddiff │             typed │  false │          598.5 │            49.3 │
│           Smorgasbord │   201 │ forwarddiff │ simple_namedtuple │   true │          423.2 │            57.6 │
│           Smorgasbord │   201 │ forwarddiff │           untyped │   true │         1063.4 │            32.1 │
│           Smorgasbord │   201 │ forwarddiff │       simple_dict │   true │         6740.1 │            29.0 │
│           Smorgasbord │   201 │ reversediff │             typed │   true │          914.1 │            46.1 │
│           Smorgasbord │   201 │    mooncake │             typed │   true │          875.0 │             5.8 │
│    Loop univariate 1k │  1000 │    mooncake │             typed │   true │         4455.6 │             5.6 │
│       Multivariate 1k │  1000 │    mooncake │             typed │   true │         1020.9 │             9.3 │
│   Loop univariate 10k │ 10000 │    mooncake │             typed │   true │        51734.7 │             4.9 │
│      Multivariate 10k │ 10000 │    mooncake │             typed │   true │         8677.5 │            10.3 │
│               Dynamic │    10 │    mooncake │             typed │   true │          132.2 │            10.9 │
│              Submodel │     1 │    mooncake │             typed │   true │           10.4 │             5.6 │
│                   LDA │    12 │ reversediff │             typed │   true │          992.7 │             2.1 │
└───────────────────────┴───────┴─────────────┴───────────────────┴────────┴────────────────┴─────────────────┘

Copy link

codecov bot commented Sep 29, 2025

Codecov Report

❌ Patch coverage is 88.50575% with 10 lines in your changes missing coverage. Please review.
✅ Project coverage is 82.36%. Comparing base (ec65b4f) to head (db64645).
⚠️ Report is 2 commits behind head on breaking.

Files with missing lines Patch % Lines
src/abstract_varinfo.jl 66.66% 3 Missing ⚠️
src/simple_varinfo.jl 78.57% 3 Missing ⚠️
src/threadsafe.jl 75.00% 2 Missing ⚠️
ext/DynamicPPLEnzymeCoreExt.jl 0.00% 1 Missing ⚠️
src/varinfo.jl 97.67% 1 Missing ⚠️
Additional details and impacted files
@@             Coverage Diff              @@
##           breaking    #1060      +/-   ##
============================================
- Coverage     82.38%   82.36%   -0.03%     
============================================
  Files            42       42              
  Lines          3820     3787      -33     
============================================
- Hits           3147     3119      -28     
+ Misses          673      668       -5     

☔ View full report in Codecov by Sentry.
📢 Have feedback on the report? Share it here.

🚀 New features to boost your workflow:
  • ❄️ Test Analytics: Detect flaky tests, report on failures, and find test suite problems.

Copy link
Contributor

DynamicPPL.jl documentation for PR #1060 is available at:
https://TuringLang.github.io/DynamicPPL.jl/previews/PR1060/

@mhauru
Copy link
Member Author

mhauru commented Sep 30, 2025

CI benchmarks. Target branch:

┌───────────────────────┬───────┬─────────────┬───────────────────┬────────┬────────────────┬─────────────────┐
│                 Model │   Dim │  AD Backend │           VarInfo │ Linked │ t(eval)/t(ref) │ t(grad)/t(eval) │
├───────────────────────┼───────┼─────────────┼───────────────────┼────────┼────────────────┼─────────────────┤
│ Simple assume observe │     1 │ forwarddiff │             typed │  false │            8.5 │             1.6 │
│           Smorgasbord │   201 │ forwarddiff │             typed │  false │          635.2 │            43.6 │
│           Smorgasbord │   201 │ forwarddiff │ simple_namedtuple │   true │          411.8 │            52.7 │
│           Smorgasbord │   201 │ forwarddiff │           untyped │   true │         1163.6 │            29.7 │
│           Smorgasbord │   201 │ forwarddiff │       simple_dict │   true │         6444.2 │            28.6 │
│           Smorgasbord │   201 │ reversediff │             typed │   true │         1022.9 │            40.9 │
│           Smorgasbord │   201 │    mooncake │             typed │   true │          980.1 │             4.5 │
│    Loop univariate 1k │  1000 │    mooncake │             typed │   true │         5750.3 │             4.3 │
│       Multivariate 1k │  1000 │    mooncake │             typed │   true │          964.6 │             9.1 │
│   Loop univariate 10k │ 10000 │    mooncake │             typed │   true │        64679.1 │             3.9 │
│      Multivariate 10k │ 10000 │    mooncake │             typed │   true │         8179.8 │            10.3 │
│               Dynamic │    10 │    mooncake │             typed │   true │          129.7 │            11.3 │
│              Submodel │     1 │    mooncake │             typed │   true │           12.2 │             5.1 │
│                   LDA │    12 │ reversediff │             typed │   true │         1006.2 │             2.0 │
└───────────────────────┴───────┴─────────────┴───────────────────┴────────┴────────────────┴─────────────────┘

This branch:

┌───────────────────────┬───────┬─────────────┬───────────────────┬────────┬────────────────┬─────────────────┐
│                 Model │   Dim │  AD Backend │           VarInfo │ Linked │ t(eval)/t(ref) │ t(grad)/t(eval) │
├───────────────────────┼───────┼─────────────┼───────────────────┼────────┼────────────────┼─────────────────┤
│ Simple assume observe │     1 │ forwarddiff │             typed │  false │            7.4 │             1.7 │
│           Smorgasbord │   201 │ forwarddiff │             typed │  false │          597.3 │            49.0 │
│           Smorgasbord │   201 │ forwarddiff │ simple_namedtuple │   true │          422.1 │            57.4 │
│           Smorgasbord │   201 │ forwarddiff │           untyped │   true │          969.2 │            35.2 │
│           Smorgasbord │   201 │ forwarddiff │       simple_dict │   true │         6575.6 │            31.0 │
│           Smorgasbord │   201 │ reversediff │             typed │   true │          883.4 │            47.6 │
│           Smorgasbord │   201 │    mooncake │             typed │   true │          854.6 │             5.1 │
│    Loop univariate 1k │  1000 │    mooncake │             typed │   true │         4305.0 │             5.6 │
│       Multivariate 1k │  1000 │    mooncake │             typed │   true │          991.4 │             9.5 │
│   Loop univariate 10k │ 10000 │    mooncake │             typed │   true │        50138.4 │             5.1 │
│      Multivariate 10k │ 10000 │    mooncake │             typed │   true │         9003.3 │            10.1 │
│               Dynamic │    10 │    mooncake │             typed │   true │          128.2 │            11.4 │
│              Submodel │     1 │    mooncake │             typed │   true │            9.9 │             5.9 │
│                   LDA │    12 │ reversediff │             typed │   true │          989.8 │             2.1 │
└───────────────────────┴───────┴─────────────┴───────────────────┴────────┴────────────────┴─────────────────┘

Roughly in line with what I saw locally. Seems worth it to me, especially if you look at the Loop univariate 1k and 10k models.

@yebai
Copy link
Member

yebai commented Sep 30, 2025

I suggest we take this chance to rename Metadata.trans to a more readable term, e.g., Metadata.is_unconstrained / Metadata.is_transformed.

@mhauru
Copy link
Member Author

mhauru commented Sep 30, 2025

Good idea, done.

@mhauru mhauru requested a review from penelopeysm September 30, 2025 16:19
Comment on lines 494 to 496
islinked(vi::SimpleVarInfo) = istrans(vi)
islinked(vi::SimpleVarInfo) = is_transformed(vi)
Copy link
Member

@penelopeysm penelopeysm Sep 30, 2025

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

like this line is just the same function but duplicated. so it feels like to me we could just pick one and roll with it!

@mhauru mhauru requested a review from penelopeysm October 9, 2025 15:18
Copy link
Member

@penelopeysm penelopeysm left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Happy to merge after this! Very pleased with the improved performance

@penelopeysm
Copy link
Member

@mhauru I'll leave you to click the green button :)

@mhauru mhauru merged commit 01bf0bc into breaking Oct 10, 2025
18 of 19 checks passed
@mhauru mhauru deleted the mhauru/delete-flags branch October 10, 2025 08:55
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Labels

None yet

Projects

None yet

Development

Successfully merging this pull request may close these issues.

3 participants