License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.CP.2021.25
URN: urn:nbn:de:0030-drops-153165
URL: https://drops.dagstuhl.de/opus/volltexte/2021/15316/
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Fichte, Johannes K. ; Hecher, Markus ; McCreesh, Ciaran ; Shahab, Anas

Complications for Computational Experiments from Modern Processors

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LIPIcs-CP-2021-25.pdf (1 MB)


Abstract

In this paper, we revisit the approach to empirical experiments for combinatorial solvers. We provide a brief survey on tools that can help to make empirical work easier. We illustrate origins of uncertainty in modern hardware and show how strong the influence of certain aspects of modern hardware and its experimental setup can be in an actual experimental evaluation. More specifically, there can be situations where (i) two different researchers run a reasonable-looking experiment comparing the same solvers and come to different conclusions and (ii) one researcher runs the same experiment twice on the same hardware and reaches different conclusions based upon how the hardware is configured and used. We investigate these situations from a hardware perspective. Furthermore, we provide an overview on standard measures, detailed explanations on effects, potential errors, and biased suggestions for useful tools. Alongside the tools, we discuss their feasibility as experiments often run on clusters to which the experimentalist has only limited access. Our work sheds light on a number of benchmarking-related issues which could be considered to be folklore or even myths.

BibTeX - Entry

@InProceedings{fichte_et_al:LIPIcs.CP.2021.25,
  author =	{Fichte, Johannes K. and Hecher, Markus and McCreesh, Ciaran and Shahab, Anas},
  title =	{{Complications for Computational Experiments from Modern Processors}},
  booktitle =	{27th International Conference on Principles and Practice of Constraint Programming (CP 2021)},
  pages =	{25:1--25:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-211-2},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{210},
  editor =	{Michel, Laurent D.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2021/15316},
  URN =		{urn:nbn:de:0030-drops-153165},
  doi =		{10.4230/LIPIcs.CP.2021.25},
  annote =	{Keywords: Experimenting, Combinatorial Solving, Empirical Work}
}

Keywords: Experimenting, Combinatorial Solving, Empirical Work
Collection: 27th International Conference on Principles and Practice of Constraint Programming (CP 2021)
Issue Date: 2021
Date of publication: 15.10.2021
Supplementary Material: Benchmark results can be found on Zenodo: https://doi.org/10.5281/zenodo.5542156.


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