pycroscopy / pycroscopy/pyTEMlib
Parallelization for EDS Spectrum Fitting
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Description
I am requesting the addition of parallelization in the pyTEMlib.eds_tools.fit_model function for use on an HPC.
The residuals function may simply need to have spectrum input confirmed as a dask array and then either converted or add .compute() for dask to run it in parallel.
There may be other room for improvement including where some of the mathematic operations could be converted to dask versions such as da.dot, or da.abs, but I am not sure how much speed improvement this would add.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the pyTEMlib.eds_tools.fit_model entry point and its residuals function, which the issue identifies as the main areas for investigation. Determine how spectrum input is represented and whether the fitting operations can execute in parallel on an HPC. Done means fit_model supports parallel execution with an evaluated speed improvement.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- hpc
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100