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edf-hpc
verrou
C2018–2022
edf-hpc / verrou

verrou

floating-point errors checker

2Distinct people
3Mentions
0Explicit recommenders
74GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

floating-point errors checker

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year3 dated mentions

Observed mentions: 2018-09-23 19:21:13 UTC to 2022-06-05 10:43:51 UTC.

012018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20182019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments20202021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2022

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC101
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC000
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC000
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC101
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC101

What Hacker News says

3 sources
At the risk of just talking to myself, I'll note that a google scholar search on the [1] above led me to this phd [2] which in turn led me to two newer tools, Verrou [3] and Verificarlo [4] which involve Valgrind and Docker, respectively, though I'd have to understand what exactly is being contained by Docker for Verrou. But it makes me appreciate more the minimalist approach of Knizia et al. in [1], which does involve recompilation of modified assembly, but that's something I'm doing multiple times with student code already. [2] https://tel.archives-ouvertes.fr/tel-03110553/document [3] https://github.com/edf-hpc/verrou [4] https://github.com/verificarlo/verificarlo
In C library for multiple-precision floating-point arithmetic with correct rounding
I am not familiar with NSan (and impatient to read the paper) but a common problem with tools based on higher precision shadow values is that they can be easily defeated by a large cancelation (`(1e200 + 1) - 1e200` will return 0 in both 64 and 200 bits arithmteic). My solution to this problem (which also has performance benefits) is to use an error-free transform based arithmetic (they give you roughly doubled precision but are also very resilient to cancelation). See Shaman [0] for a C++ reference implementation, you can change your types and it will display only the significant digits of your results. If you want something that does not require modifying your source code, I would recommend Verrou [1], a Valgrind-based tool using stochastic arithmetic. For those interested in the subject, my PhD [1] (which is written in English despite
Read the rest
the French title) gives further information on all those methods, their pros and cons. [0]: https://gitlab.com/numerical_shaman/shaman [1]: https://github.com/edf-hpc/verrou [2]: https://tel.archives-ouvertes.fr/tel-03116750
In NSan: a floating-point numerical sanitizer
I have a paper that should be out in few months (I might do a show Hackernews). It details a method+tool, which provides fine-grained information out of the box, that I used on published simulation codes. In the meantime, if you want a way to explore this subject on your own applications, I would recommend Verrou[0]. It has its shortcomings but it is probably the current easiest way to evaluate the impact of floating-point arithmetic on your code (I did not work on it but exchanged a lot with their team). [0] https://github.com/edf-hpc/verrou
In High Performance Computing: Are We Just Getting Wrong Answers Faster? (1998) [pdf]

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