Giovanni Petrucciani's feedback from CMGRDF
CMGRDF: A framework to define computation graphs built on top of RDataFrame. Tailored towards interactive plotting for complex analysis use cases in CMS.
Q&A
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How can you derive that different operations require the same files?
- There is alist of operations to be performed and a list of data sources. By comparing the sets of operators to the list of files we can build a map where if we find files are already being used we can attach to the existing computation graph.
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What are the numbers in parenthesis at slide showing analysis description?
- 70 is without optimizing the graph building and just building one graph per selection.
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Cache based on the input, what kind of input?
- For each dataset I create a hash from the filename, possibly timestamp. Once the list of operations is present, I include a hash of the whole computation graph.
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Does this work at every step of the computation graph?
- No, at the moment it only caches the final results of the whole computation graph to disk.
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Do you have an idea about the sparseness?
- We have already prescale and selecting events before starting the analysis. The ~1TB of input dataset thus is pre-skimmed, although there are quite many branches that are left from the original nanoAOD that we don't read.
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I can't see the JIT stack traces with VTUNE?
- Try with
CLING_PROFILE=1 in the environment
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Can some of the JITted code be pre-compiled?
- We already pre-compile some things, not all. I don't know how much we can improve in that sense.
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What is happening in the building of the graphs that is not RDF JIT?
- It's the time of the creation of the nodes. Either spent in CMGRDF code or directly within RDF. To be investigated.
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For snapshot, you write directly to EOS?
- Yes!
- Would be nice if you could comment on the github issue.
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Request multicore workers via condor and run ROOT IMT.
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gSystem->Load, example of when crashes?
- I had some examples, not easily reproducible.
- Would be nice to create one.
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