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Split the number of CPUs in modules with two tools in a piped command and each of them with an explicit declaration of the CPUs to be used. See #498

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Closes #498

  • This comment contains a description of changes (with reason).
  • Ensure that the test works with either Docker / Singularity. Conda CI tests can be quite flaky:
    • PROFILE=docker pytest --tag <MODULE> --symlink --keep-workflow-wd
    • PROFILE=singularity pytest --tag <MODULE> --symlink --keep-workflow-wd
    • PROFILE=conda pytest --tag <MODULE> --symlink --keep-workflow-wd

@JoseEspinosa JoseEspinosa requested review from drpatelh and ewels May 17, 2021 14:40
@JoseEspinosa JoseEspinosa added the enhancement New feature or request label May 17, 2021
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@ewels ewels left a comment

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LGTM 👌 Just need to fix the tests..

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@maxulysse maxulysse left a comment

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<3

@JoseEspinosa
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LGTM 👌 Just need to fix the tests..

These are the infamous conda tests... I can not also resolve the environment locally, so I guess that as usual, since docker and singularity are passing we can ignore it... 😓

@JoseEspinosa JoseEspinosa merged commit 0bbd7ac into nf-core:master May 18, 2021
@JoseEspinosa JoseEspinosa deleted the cpus_piped_cmds branch June 18, 2021 12:43
@ramprasadn
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ramprasadn commented Sep 21, 2021

Sorry for resurrecting this thread four months after it was closed, but I wonder if splitting by 2 affects the performance of the aligner a bit.

Looks like when we have a piped command, its almost always an aligner paired with samtools view, and samtools view is not a resource intensive process. In that case, the aligner should be getting more resources instead of samtools, right? What do you guys think?

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Fix number of cpus for modules with piped tools

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