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  • Transfer mechanism: Documentation implies that only files with an mtime newer than when the transfer_input_files finished will be transferred back to the submit host.  While running a dag, the files in my working directory (which is in both transfer_input_files and transfer_output_files) seem to always have an mtime around the most recent step in the DAG suggesting that the entire working directory is copied from the execution host to the submit host at the end of each DAG step.  Perhaps this means the transfer mechanism only looks at the mtime of the files/dirs specified in transfer_output_files and doesn't descend into the directories.
    • Subdirectories are treated differently

  • Flocking: When we flock to CHTC what is the data path for transfer_input_files?  Is it our submit host and CHTC's execution host, is CHTCs submit host involved ?
    • Dataflow is from our schedd (submit host) to their execute host but CCB will reverse the connection.  Their execution hosts are publicly addressable but that may not be necessary.

  • How can we  data path for transfer_input_files to our clients given multiple networks.  Currently we assume it will use the 1Gb link but we have IB links.    Is there a way for condor to use the IB link just for transferring files, is that hostname based ? Other ideas?
    • CHTC doesn't have a good solution for this.
    • We could upgrade from 1Gb to 10Gb
    • We could use the IB names for everything (problematic for submit hosts that don't have IB)
    • We could not use transfer mechanism and instead use something else like scp
    • We could use a custom transfer plugin

  • Are there known issues with distributed scratch via NFS or Lustre w.r.t tmpdir or other,  e.g. OpenMPI complains about tmpdir being on network FS?
    • Some problems with log files on the submit host but rare.
  • Any general best practices to support MPI in terms of class ads or other.
    • Use the shared memory transport for security

  •  Is there a way DAGMan can be told to ignore errors, in some cases we want a DAG to mindlessly continue vs retry.
    • The job is considered successful based on the return of the post script.  If there isn't a post script, the success is based on the return of the job.


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