llnl / llnl/maestrowf

Add switch to prioritize depth first execution

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enhancement
Dominant language
Python
Stars
161
Forks
49
PR merge metrics
No merged PRs in 30d

Description

The idea here is to enable a single parameter values' dependent steps to start running before all of the parameter values in the parent step have been executed. The use case is to help data management on very large studies: e.g. a post processing step for a given large simulation could get started immediately and enable cleanup/compression/reduction of the data, mitigating the need to have storage space that can fit all the simulations' data at once.

Contributor guide

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First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

The issue names no files, tests, or entry points. Start by locating the workflow scheduler and execution-order logic, then determine how dependent steps are represented and configured. Done means a parameter can opt into depth-first execution while preserving existing behavior by default, with coverage for the ordering and large-study use case.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
tooling
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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