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  • Code & Results quality

Last edited by Gabriel Wlazłowski Feb 27, 2024
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Code & Results quality

Introduction

The priorities for W-SLDA Toolkit developers are as follow (from highest to lowest):

  1. Correctness of computation.
  2. Performace.
  3. User-friendly interface.

The highest priority is computation correctness, which is the fundamental issue in computational physics.

W-SLDA Toolkit quality

Within W-SLDA Toolkit we apply the following strategies to ensure a high level of confidence of the computation correctness:

Level 1: Inspection of the results

It is the most standard method (and in many groups the only one). Namely,
   results are correct if they look to be correct.
While it may look to be rather a weak method of testing of computation correctness, in practice, it works very well. Typically, we know what to expect as the results (more or less), at least at the level of qualitative behavior. Physics is equipped with various methods, experiments, etc, and making extensive comparisons with them automatically leads to the inspection of sources of discrepancies (if present). From point of view of the implementation, the W-SLDA Toolkit delivers extensive support for results analysis.

Actions taken within W-SLDA Toolkit to support the level 1 quality checks:

  • W-data format: conceptually easy data format that allows a variety of tools/languages to be used for data analysis.
  • Integration with VisIt: advanced platform for data visualisation & analysis.
  • Auxiliary tools & Extensions: we provide various examples of tested codes for data analysis.

Level 2: Internal tests

Level 3: Open-source & Transparency

Links to interesting articles related to code & results quality

  • Does your code stand up to scrutiny?
  • David A. W. Soergel, Rampant software errors may undermine scientific results
  • Zeeya Merali, Computational science: ...Error
  • Jeffrey M. Perkel, How to fix your scientific coding errors
Clone repository
  • API version
  • Automatic interpolations
  • Auxiliary tools
  • Browsing the code
  • Broyden algorithm
  • C and CUDA
  • Campaign of calculations
  • Checking correctness of settings
  • Chemical potentials control
  • Code & Results quality
  • Common failures of static codes
  • Common failures of time dependent codes
  • Computation domain
  • Configuring GPU machine
  • Constraining densities and potentials
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