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taschini
crlibm
C2021–2025
taschini / crlibm

crlibm

A mirror of the CRLibm project from INRIA Forge

2Distinct people
2Mentions
0Explicit recommenders
51GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

A mirror of the CRLibm project from INRIA Forge

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, 1:49:46 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 year2 dated mentions

Observed mentions: 2021-08-26 20:33:19 UTC to 2025-02-11 08:02:24 UTC.

012021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20212022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments20232024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2025

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
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 UTC000
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC000
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC000
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC101

What Hacker News says

2 sources
Floating-point is hard, and standards seem like they cater to lawyers rather than devs. But a few things are slightly misleading in the post. 1. It correctly quotes the IEEE754-2008 standard: > A conforming function shall return results correctly rounded for the applicable rounding direction for all operands in its domain and even points out that the citation is from "Section 9. *Recommended* operations" (emphasis mine). But then it goes on to describes this as a "*requirement*" of the standard (it is not). This is not just a mistype, the post actually implies that implementations not following this recommendation are wrong: > [...] none of the major mathematical libraries that are used throughout computing are actually rounding correctly as demanded in any version of IEEE 754 after the original 1985 release. or: > [...] ranging from beni
Read the rest
gn disregard for the standard to placing the burden of correctness on the user who should know that the functions are wrong: “It is following the specification people believe it’s following.” As far as I know, IEEE754 mandates correct rounding for elementary operations and sqrt(), and only for those. 2. All the mentions of 1 ULP in the beginning are a red herring. As the article itself mentions later, the standard never cares about 1 ULP. Some people do care about 1 ULP, just because it is something that can be achieved at a reasonable cost for transcendentals, so why not do it. But not the standard. 3. The author seems to believe that 0.5 ULP would be better than 1 ULP for numerical accuracy reasons: > I was resounding told that the absolute error in the numbers are too small to be a problem. Frankly, I did not believe this. I would personally also tell that to the author. But there is a much more important reason why correct rounding would be a tremendous advantage: reproducibility. There is always only one correct rounding. As a consequence, with correct rounding, different implementations return bit-for-bit identical results. The author even mentions falling victim to FP non-reproducibility in another part of the article. 4. This last point is excusable because the article is from 2020, but "solving" the fp32 incorrect-rounding problem by using fp64 is naive (not guaranteed to always work, although it will with high probability) and inefficient. It also does not say what to do for fp64. We can do correct rounding much faster now [1, 2]. So much faster that it is getting really close to non-correctly-rounded, so some libm may one day decide to switch to that. [1] https://github.com/rutgers-apl/rlibm [2] https://github.com/taschini/crlibm
In Elementary Functions and Not Following IEEE754 Floating-Point Standard (2020)

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