HGCAL Pattern Recognition using FastJet #36172

rovere · 2021-11-18T17:34:03Z

PR description:

A novel pattern recognition plugin has been added to the TICL framework based on FastJet.
At present, only anti-kt clustering algorithm has been added. All algorithms from the rich FastJet library could be tested using different configurations.
A processModifier has been added to allow the end-user to enable this plugin. The modifier is called fastJetTICL.
The modifier has been added in such a way that all the validation plots for the Tracksters produced by the FastJet pattern recognition will be automatically produced.
At present jets are translated into Tracksters. As a future development, if needed, we could save also the reconstructed jets.
It would be nice to have this code integrated into the release, even if not bundled to any official workflow, to allow interested people to develop on top of that.

You can find some more information about its performance (it's quite hard to call them as such, as of yet...) here.
This PR has also been recently announced during this reconstruction meeting.

PR validation:

Run on Phase2 dedicated workflows and private multiparticle samples w/o issues.

cmsbuild · 2021-11-18T17:40:50Z

+code-checks

Logs: https://cmssdt.cern.ch/SDT/code-checks/cms-sw-PR-36172/26734

This PR adds an extra 28KB to repository

cmsbuild · 2021-11-18T17:41:17Z

A new Pull Request was created by @rovere (Marco Rovere) for master.

It involves the following packages:

Configuration/ProcessModifiers (operations)
RecoHGCal/TICL (upgrade, reconstruction)

@perrotta, @cmsbuild, @AdrianoDee, @srimanob, @slava77, @jpata, @qliphy, @fabiocos, @davidlange6 can you please review it and eventually sign? Thanks.
@missirol, @makortel, @felicepantaleo, @Martin-Grunewald, @apsallid, @sobhatta, @lecriste, @hatakeyamak, @ebrondol, @fabiocos this is something you requested to watch as well.
@perrotta, @dpiparo, @qliphy you are the release manager for this.

cms-bot commands are listed here

rovere · 2021-11-18T17:44:41Z

assign hgcal-dpg

cmsbuild · 2021-11-18T17:45:05Z

New categories assigned: hgcal-dpg

@felicepantaleo,@rovere,@pfs,@cseez you have been requested to review this Pull request/Issue and eventually sign? Thanks

rovere · 2021-11-18T17:48:37Z

@cmsbuild please test

cmsbuild · 2021-11-18T20:59:05Z

+1

Summary: https://cmssdt.cern.ch/SDT/jenkins-artifacts/pull-request-integration/PR-077fa0/20616/summary.html
COMMIT: c302229
CMSSW: CMSSW_12_2_X_2021-11-18-1100/slc7_amd64_gcc900
User test area: For local testing, you can use /cvmfs/cms-ci.cern.ch/week1/cms-sw/cmssw/36172/20616/install.sh to create a dev area with all the needed externals and cmssw changes.

Comparison Summary

Summary:

No significant changes to the logs found
Reco comparison results: 8 differences found in the comparisons
DQMHistoTests: Total files compared: 42
DQMHistoTests: Total histograms compared: 3327156
DQMHistoTests: Total failures: 11
DQMHistoTests: Total nulls: 1
DQMHistoTests: Total successes: 3327122
DQMHistoTests: Total skipped: 22
DQMHistoTests: Total Missing objects: 0
DQMHistoSizes: Histogram memory added: -0.004 KiB( 41 files compared)
DQMHistoSizes: changed ( 312.0 ): -0.004 KiB MessageLogger/Warnings
Checked 177 log files, 37 edm output root files, 42 DQM output files
TriggerResults: no differences found

jpata · 2021-11-23T12:46:23Z

For my understanding, is the TF model the same across these four modules?

cmssw/RecoHGCal/TICL/plugins/PatternRecognitionbyFastJet.cc

Line 219 in c302229

tensorflow::TensorShape shape({batchSize, eidNLayers_, eidNClusters_, eidNFeatures_});
cmssw/RecoHGCal/TICL/plugins/TrackstersMergeProducer.cc

Line 594 in c302229

tensorflow::TensorShape shape({batchSize, eidNLayers_, eidNClusters_, eidNFeatures_});
cmssw/RecoHGCal/TICL/plugins/PatternRecognitionbyCA.cc

Line 384 in c302229

tensorflow::TensorShape shape({batchSize, eidNLayers_, eidNClusters_, eidNFeatures_});
cmssw/RecoHGCal/TICL/plugins/PatternRecognitionbyCLUE3D.cc

Line 354 in c302229

tensorflow::TensorShape shape({batchSize, eidNLayers_, eidNClusters_, eidNFeatures_});

Perhaps there is an opportunity to reduce code duplication here by a shared evaluator.

rovere · 2021-11-23T14:27:51Z

Ciao @jpata yes indeed, the model is the same, for the time being.
In parallel, we are working on the factorization that was already suggested some months ago to save memory by re-using the same session for the same model in several plugins. That will come, at some point in the near future.
In a little farther away future, depending on the use cases for the different plugins, it is quite likely we will have different models for the different plugins. In this sense, the shared evaluator will be less important, since shaping batching and everything that comes with that will likely be different.
Benedikt, as you know, is actively working on this front.

jpata · 2021-11-25T16:03:30Z

Perhaps a workflow can be introduced if this is intended for production:

rovere · 2021-11-26T08:40:58Z

Ciao @jpata I took the same path we had taken for the CLUE3D case, i.e., add a procModifier w/o any additional proliferation of dedicated workflows.
If/when at some point this PR algorithm will be part of the Phase2 reconstruction, it will automatically be monitored. Up until now, I believe that the procModifier is small and practical enough to allow users to investigate the new possibilities brought in by FastJet.
What do you think?

jpata · 2021-11-26T12:33:04Z

Generally we try to make an effort that new functionality would also be regularly tested in IBs, when possible and practical.
How many different configurations of modifiers are there for HGCAL reconstruction? Perhaps it could be a good time to introduce some workflows for the major ones.
Also, do you have some pre/post numbers on CPU and memory consumption with igprof?

rovere · 2021-11-26T15:49:20Z

Ciao @jpata
there are currently 2 procModifiers, one for CLUE3D and another one for FastJet. Well, perhaps I should have said one, since this PR is not merged.
I have numbers in the slides linked in the description. Definitely not conclusive and for sure nothing igprof related.
Yet a good comparison against what is currently run by default in release.
What are you practically suggesting to do in order to integrate this PR?

jpata · 2021-11-27T08:20:24Z

a test workflow
igprof CPU and MEM numbers

jpata · 2021-11-29T15:45:53Z

An alternative to a workflow is that you enable the modifier here temporarily, we run the tests and get some numbers, then you disable the modifier again.

jpata · 2021-12-06T15:28:37Z

kind ping on this.

enable the modifier here temporarily, we run the tests and get some numbers, then disable the modifier again.

jpata · 2022-01-06T15:44:22Z

kind ping @cms-sw/pdmv-l2

rovere · 2022-01-10T13:42:01Z

Hello there,
another kind ping @cms-sw/pdmv-l2

bbilin · 2022-01-10T13:44:45Z

+1
sorry for the latency, just got back.

rovere · 2022-01-10T13:46:06Z

thanks!

jpata · 2022-01-10T15:48:43Z

(the sig didn't work, +1 / +pdmv should be the first line in the comment)

bbilin · 2022-01-10T16:16:59Z

+pdmv

qliphy · 2022-01-11T01:15:59Z

please test
just to refresh the test results

cmsbuild · 2022-01-11T04:50:56Z

+1

Summary: https://cmssdt.cern.ch/SDT/jenkins-artifacts/pull-request-integration/PR-077fa0/21616/summary.html
COMMIT: 3a0c1b3
CMSSW: CMSSW_12_3_X_2022-01-10-1100/slc7_amd64_gcc10
User test area: For local testing, you can use /cvmfs/cms-ci.cern.ch/week1/cms-sw/cmssw/36172/21616/install.sh to create a dev area with all the needed externals and cmssw changes.

Comparison Summary

Summary:

No significant changes to the logs found
Reco comparison results: 7 differences found in the comparisons
DQMHistoTests: Total files compared: 43
DQMHistoTests: Total histograms compared: 3461659
DQMHistoTests: Total failures: 11
DQMHistoTests: Total nulls: 0
DQMHistoTests: Total successes: 3461626
DQMHistoTests: Total skipped: 22
DQMHistoTests: Total Missing objects: 0
DQMHistoSizes: Histogram memory added: 0.0 KiB( 42 files compared)
Checked 181 log files, 42 edm output root files, 43 DQM output files
TriggerResults: no differences found

perrotta · 2022-01-11T11:21:00Z

+operations

Two new special TICL pattern recognition workflows defined for clue3D (not related to this PR, but welcome anyhow) and FastJet
They have been succesfully tested offline, and should become available to bot once this PR will be merged

cmsbuild · 2022-01-11T11:21:24Z

This pull request is fully signed and it will be integrated in one of the next master IBs (tests are also fine). This pull request will now be reviewed by the release team before it's merged. @perrotta, @dpiparo, @qliphy (and backports should be raised in the release meeting by the corresponding L2)

perrotta · 2022-01-11T11:24:06Z

RecoHGCal/TICL/plugins/PatternRecognitionbyFastJet.h

+    static void fillPSetDescription(edm::ParameterSetDescription& iDesc);
+
+  private:
+    edm::ESGetToken<CaloGeometry, CaloGeometryRecord> caloGeomToken_;


This should also be const (but it is not fundamental, and I won't reset so many signatures only for that...)

perrotta · 2022-01-11T11:24:25Z

+1

cmsbuild added this to the CMSSW_12_2_X milestone Nov 18, 2021

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cmsbuild added tests-started and removed tests-pending labels Nov 18, 2021

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cmsbuild added upgrade-approved and removed upgrade-pending labels Dec 21, 2021

cmsbuild mentioned this pull request Dec 21, 2021

Phase 2 tracker: add T28 and T29 (geometries with bricked pixels for IT sensor design studies) #36457

Merged

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Phase2 tracker: add T30 (geometry with more realistic TFPX) #36660

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for external PR tests, make sure to include latest cmssw merges cms-sw/cms-bot#1686

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HGCAL Pattern Recognition using FastJet #36172

HGCAL Pattern Recognition using FastJet #36172

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HGCAL Pattern Recognition using FastJet #36172

HGCAL Pattern Recognition using FastJet #36172

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PR description:

PR validation:

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Comparison Summary

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