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Setup |
Download files required for the lesson |
00:00 |
1. Introduction
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What makes research data analyses reproducible?
Is preserving code, data, and containers enough?
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00:11 |
2. First example
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How to run analyses on REANA cloud?
What are the basic REANA command-line client usage scenarios?
How to monitor my analysis using REANA web interface?
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00:31 |
3. Developing serial workflows
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How to write serial workflows?
What is declarative programming?
How to develop workflows progressively?
Can I temporarily override workflow parameters?
Do I always have to build new Docker image when my code changes?
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01:01 |
4. HiggsToTauTau analysis: serial
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Challenge: write the HiggsToTauTau analysis workflow and run it on REANA
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01:26 |
5. Coffee break
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Coffee break
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01:41 |
6. Developing parallel workflows
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How to scale up and run thousands of jobs?
What is a DAG?
What is a Scatter-Gather paradigm?
How to run Yadage workflows on REANA?
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02:06 |
7. HiggsToTauTau analysis: parallel
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Challenge: write the HiggsToTauTau analysis parallel workflow and run it on REANA
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02:36 |
8. A glimpse on advanced topics
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Can I publish workflow results on EOS?
Can I use Kerberos to access restricted resources?
Can I use CVMFS software repositories?
Can I dispatch heavy computations to HTCondor?
Can I dispatch heavy computations to Slurm?
Can I open Jupyter notebooks on my REANA workspace?
Can I connect my GitLab repositories with REANA?
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02:56 |
9. Wrap-up
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What have we learned today?
Where to go from here?
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03:01 |
Finish |
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The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.