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FIXME: list authors' names and email addresses. | ||
* [Martin Kwok](https://github.com/kakwok) | ||
* Abdollah Mohammadi | ||
* Elisa Fontanesi |
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--- | ||
title: "Introduction" | ||
teaching: 0 | ||
teaching: 30 | ||
exercises: 0 | ||
questions: | ||
- "Key question (FIXME)" | ||
objectives: | ||
- "First learning objective. (FIXME)" | ||
keypoints: | ||
- "First key point. Brief Answer to questions. (FIXME)" | ||
- "Overview of CMS trigger system" | ||
--- | ||
FIXME | ||
We will learn the overview of CMS trigger system, both L1 and HLT, with [slides](https://indico.cern.ch/event/1443889/). | ||
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{% include links.md %} | ||
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--- | ||
title: "HLT timing studies" | ||
teaching: 30 | ||
exercises: 0 | ||
objectives: | ||
- "Measure the time it takes to run an HLT menu" | ||
- "Reference repo: [link](https://github.com/loeschet/TimingExerciseTriggerHATS2023/blob/main/README.md)" | ||
--- | ||
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### Exercise 1: CPU/GPU Timing measurements without creation of a CMSSW environment | ||
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1. Log in to lxplus and clone [the timing repository](https://gitlab.cern.ch/cms-tsg/steam/timing) somewhere (e.g. in your EOS space) | ||
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~~~ | ||
git clone https://gitlab.cern.ch/cms-tsg/steam/timing.git | ||
cd timing | ||
~~~ | ||
{: .language-bash} | ||
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2. Submit a timing job to the timing machine using `CMSSW_13_2_0`, the GRun menu V152 and the default dataset on the timing machine. Additionally, tell the program to merge in pull request [#42534](https://github.com/cms-sw/cmssw/pull/42534) Also use a user-specified tag to better identify your job later in the queue. | ||
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~~~ | ||
python3 submit.py /dev/CMSSW_13_0_0/GRun/V152 --cmssw CMSSW_13_2_0 --pull-requests 42534 --tag YOUR_TAG_HERE | ||
~~~ | ||
{: .language-bash} | ||
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3. Check the status of your job using the `job_manager.py` script. | ||
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~~~ | ||
python3 job_manager.py | ||
~~~ | ||
{: .language-bash} | ||
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{% include links.md %} | ||
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--- | ||
title: "Measuring trigger efficiencies" | ||
teaching: 30 | ||
exercises: 0 | ||
objectives: | ||
- "Learn how to access the trigger information stored in MiniAOD and NanoAOD" | ||
- "Learn what is trigger objects and how to access them" | ||
- "Measure trigger efficiency using the tag-and-probe method" | ||
--- | ||
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> ## Prerequisites | ||
> Set up your machine following instructions in [setup][lesson-setup] first. | ||
{: .prereq} | ||
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The goal of the following exercises is to learn how to access and play with the trigger objects in our data and compute the efficiency of a specific HLT path, having a look also at its Level 1 (L1) seed. The focus will be on a HLT path used during the 2016 data-taking to select events with a certain amount of missing transverse energy: `HLT_PFMET170_HBHECleaned_v*`. | ||
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{% include links.md %} | ||
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