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It is not clear yet how these machine learning runs can best integrate with flux, beyond submitting a job to Flux. We will need to think about this. One design, however, I think could work really nicely here is: 1. Use Foundry for storing data, download a dataset via the broker pre command. 2. Use flux filemap in the batch script (with batch:true and batchRaw: true) to map the data to nodes 3. Run some job that uses the data across the nodes (e.g., MPI or similar) Signed-off-by: vsoch <vsoch@users.noreply.github.com>
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It is not clear yet how these machine learning runs can best integrate with flux, beyond submitting a job to Flux. We will need to think about this. One design, however, I think could work really nicely here is: