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Opened Oct 28, 2019 by Andreas Singraber@singraberReporter16 of 18 tasks completed16/18 tasks
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Module: N2P2 - Symmetry Function Memory Footprint Reduction

  • Overview 8
  • Commits 5
  • Pipelines 4
  • Changes 1

This module improves memory management in N2P2. More specifically, a new strategy to store symmetry function derivatives is implemented. In this way the memory footprint during training is drastically reduced.

Roadmap

  • Create Boost tests for symmetry function calculation and training.
  • Implement "element-combination-aware" storage for symmetry function derivatives.
  • Provide example and check memory footprint before/after.
  • Source code documentation.
  • Complete module README.

Module verification checklist (for reviewers)

Checklist when the module is first submitted

  • Have the relevant labels been added to the MR
  • If submitted on someone elses behalf, has the software author been referenced (if they have a GitLab account)

Checklist when module is no longer "WIP"

  • Is the module documentation sufficiently detailed?
  • Is it mergeable? (i.e., there should be no merge conflicts)
  • Are the build instructions sufficient - source code locations, build instructions, etc.? (If not the MR should be updated)
  • Did it pass the tests that were described? (Are there unit/regression tests? Do they pass?)
  • Are the tests sufficient?
  • If the module introduces new functionality, is it tested? (Unit/regression tests?)
  • Is the associated source code well formatted? (typos, line length, brackets,...it should be consistent with existing source)
  • Is all new source code sufficiently documented? (functions, their arguments,...)
  • Is there a description of any applications the module has? (This is a hard requirement for E-CAM PDRAs)

After Merging

  • Make sure the module appears in a toctree
  • Add a link to the final result on https://e-cam.readthedocs.io
Edited Jan 19, 2021 by David W.H. Swenson
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Reference: e-cam/E-CAM-Library!197
Source branch: n2p2_reduce_symfunc_memory