[SIGCIS-Members] the nature of computational error

[Richard Vahrenkamp]

Although physicists often use rules of thumb, the precision of
calculation became an important point in John von Neumann's policy
against the analogue computer. The precision of individual calculations
on analog machines is lower than on digital machines. But the final
results of integrating a differential equation were the same on analog
machines as on digital ones, as comparisons in the 1950s showed, see my
paper The Computing Boom in the US Aeronautical Industry, 1945–1965, in:
ICON – The Journal of the International Committee for the History of
Technology, volume 24, 2019, pp. 127–149.


Best, Richard



On 03.07.2020 22:18, Paul N. Edwards wrote:
> Rounding error is ubiquitous and unavoidable in digital computers, but with high precision computing (64-bit, 128-bit) it’s so small as to be negligible.
>
> However, in cases where the same computation is performed many thousands or millions of times, it can still accumulate to a point that it’s significant.
>
> MacKenzie, D. (1993). Negotiating Arithmetic, Constructing Proof: The Sociology of Mathematics and Information Technology. Social Studies of Science, 23(1), 37-65.
>
> Also see the short examples of this in my book A Vast Machine: Computer Models, Climate Data, and the Politics of Global Warming (MIT Press, 2010), pages 177-178.
>
> Best,
>
> Paul
>
>
>
> On Jul 3, 2020, at 10:54, Matthew Kirschenbaum <mkirschenbaum at gmail.com<mailto:mkirschenbaum at gmail.com>> wrote:
>
> Hello all,
>
> I am interested in a better understanding of the nature of computational error. My sense is that actual, literal (mathematical) mistakes in modern computers are quite rare; the notorious Pentium bug of the early 1990s is the exception that proves the rule. Most bugs are, rather, code proceeding to a perfectly correct logical outcome that just so happens to be inimical or intractable to the user and/or other dependent elements of the system. The Y2K "bug," for instance, was actually code executing in ways that were entirely internally self-consistent, however much havoc the code would wreak (or was expected to wreak).
>
> Can anyone recommend reading that will help me formulate such thoughts with greater confidence and accuracy? Or serve as a corrective? I'd like to read something fundamental and even philosophical about, as my subject line has it, the nature of computational error. I'd also be interested in collecting other instances comparable to the Pentium bug--bugs that were actual flaws and mistakes hardwired at the deepest levels of a system.
>
> Thank you-- Matt
>
>
> --
> Matthew Kirschenbaum
> Professor of English and Digital Studies
> Director, Graduate Certificate in Digital Studies
> Printer's Devil, BookLab
> University of Maryland
> mgk at umd.edu<mailto:mgk at umd.edu>
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>
> ________________________
> Paul N. Edwards<https://profiles.stanford.edu/paul-edwards>
>
> Director, Program on Science, Technology & Society<http://sts.stanford.edu>
> William J. Perry Fellow in International Security and Senior Research Scholar
> Center for International Security and Cooperation<http://cisac.fsi.stanford.edu/>
> Co-Director, Stanford Existential Risks Initiative<https://cisac.fsi.stanford.edu/stanford-existential-risks-initiative>
> Stanford University
>
> Professor of Information<http://www.si.umich.edu/> and History<http://www.lsa.umich.edu/history/> (Emeritus)
> University of Michigan
>
>
> _______________________________________________
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--
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Prof. Dr. Richard Vahrenkamp
Logistik Consulting Berlin
Phone 0177- 628 3325
E-Mail: Vahrenkamp2016 at gmx.de
Web: www.vahrenkamp.org
Trendelenburgstr. 16
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