Understanding computation time: a critical discussion of time as a computational performance metric

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Abstract

Computation time is an important performance metric that scientists and software engineers use to determine whether an algorithm is capable of running within a reasonable time frame. We provide an accessible critical review of the factors that influence computation time, highlighting problems in its reporting in current research and the negative practical impact that this has on developers, recommending best practice for its measurement and reporting. Discussing how computers and coders measure time, a discrepancy is exposed between best practice in the primarily theoretical field of computational complexity, and the difficulty for non-specialists in applying such theoretical findings. We therefore recommend establishing a better reporting practice, highlighting future work needed to expose the effects of poor reporting. Freely shareable templates are provided to help developers and researchers report this information more accurately, helping others to build upon their work, and thereby reducing the needless global duplication of computational and human effort.
Original languageEnglish
Title of host publicationTime in variance
EditorsArkadiusz Misztal, Paul A. Harris, Jo Alyson Parker
Place of PublicationLeiden
PublisherBrill
Chapter12
Pages220-248
ISBN (Electronic)9789004470170
ISBN (Print)9789004470163
DOIs
Publication statusPublished - 23 Sept 2021
EventThe 17th triennial conference of the International Society for the Study of Time: Time in Variance - Loyola Marymount University, California, United States
Duration: 23 Jun 201929 Jun 2019
http://www.studyoftime.org/ContentPage.aspx?ID=1043

Publication series

NameThe study of time
Volume17
ISSN (Print)0170-9704

Conference

ConferenceThe 17th triennial conference of the International Society for the Study of Time
Country/TerritoryUnited States
CityCalifornia
Period23/06/1929/06/19
Internet address

Keywords

  • Time
  • Computation
  • Computation time
  • Computational complexity
  • Software
  • Hardware
  • Time complexity
  • GPU
  • CPU
  • TPU

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