arb
freebsd-src
arb | freebsd-src | |
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11 | 133 | |
457 | 7,490 | |
0.9% | 0.9% | |
2.2 | 10.0 | |
about 2 months ago | 1 day ago | |
C | C | |
GNU Lesser General Public License v3.0 only | GNU General Public License v3.0 or later |
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Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
arb
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Patriot Missile Floating point Software Problem lead to deaths 28 Americans
You can instead list your criteria for good number format and look at alternatives with those lenses. Floating point is designed for a good balance between dynamic range and precision, and IEEE 754 binary formats can be seen as a FP standard particularly optimized for numerical calculation.
There are several other FP formats. The most popular one is IEEE 754 minus subnormal numbers, followed by bfloat16, IEEE 754 decimal formats (formerly IEEE 854) and posits. Only first two have good hardware supports. The lack of subnormal number means that `a <=> b` can't be no longer rewritten to `a - b <=> 0` among others but is widely believed to be faster. (I don't fully agree, but it's indeed true for existing contemporary hardwares.) IEEE 754 decimal formats are notable for lack of normalization guarantee. Posits are, in some sense, what IEEE 754 would have been if designed today, and in fact aren't that fundamentally different from IEEE 754 in my opinion.
Fixed-point formats share pros and cons of finitely sized integer numbers and you should have no difficulty to analyze them. In short, they offer a smaller dynamic range compared to FP, but its truncation model is much simpler to reason. In turn you will get a varying precision and out-of-bound issues.
Rational number formats look very promising at the beginning, but they are much harder to implement efficiently. You will need a fast GCD algorithm (not Euclidean) and also have to handle out-of-bound numerators and denumerators. In fact, many rational number formats rely on arbitrary-precision integers precisely for avoiding those issues, and inherit the same set of issues---unbounded memory usage and computational overhead. Approximate rational number formats are much rarer, and I'm only aware of the Inigo Quilez's floating-bar experiment [1] in this space.
[1] https://iquilezles.org/articles/floatingbar/
Interval/ball/affine arithmetics and others are means to automatically approximate an error analysis. They have a good property of being never incorrect, but it is still really easy for them to throw up and give a correct but useless answer like [-inf, inf]. Also they are somewhat awkward in a typical procedural paradigm because comparisons will return a tri-state boolean (true, false, unsure). Nevertheless they are often useful when correctly used. Fredrik Johansson's Arb [2] is a good starting point in my opinion.
[2] https://arblib.org/
Finally you can model a number as a function that returns a successively accurate approximation. This is called the constructive or exact real number, and simultaneously most expensive and most correct. One of the most glaring problems is that an equality is not always decidable, and practical applications tend to have various heuristics to get around this fact. Amazingly enough, Android's built-in calculator is one of the most used applications that use this model [3].
[3] https://dl.acm.org/doi/pdf/10.1145/2911981
- Beyond Automatic Differentiation
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Cosine Implementation in C
https://github.com/JuliaMath/Bessels.jl/blob/master/src/bess...
Thanks! I love it, so easy to understand and follow.
My favourite work on the subject is Fredrik Johansson's:
https://github.com/fredrik-johansson/arb
Whenever I feel down and without energy I just read something in there
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Math with Significant Figures
Probably the most popular package for dealing with error propagation and arbitrary precision arithmetic in Python is mpmath, more specifically the mp.iv module. For more serious applications I'd take a look at MPFR and Arb, both in C. And there are tons of ball arithmetic and interval arithmetic libraries in Fortran.
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Function betrayal
You're in good company too. Using intervals to bound error is the entire idea behind the arb library.
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What are some best practices in dealing with precision errors in computing?
The error bounds approach is probably what you’re looking for. A better search term for that is “interval arithmetic.” There are many good software packages for interval arithmetic, like Arb.
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Numeric equality
I do agree with your list, so that is something! I will add, balls are underrated, ditto intervals (nominally more efficient, but on x86 switching rounding modes is 20-30 cycles...)
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Cutting-edge research on numerical representations?
Ball arithmetic looks interesting. As far as I know, arb is the primary implementation.
- Is there a language which can keep track of the potential epsilon error when doing calculations?
- Beware of Fast-Math
freebsd-src
- You shouldn't run a BSD on a PC
- Linux Crisis Tools
- What about the vfs.zfs.bclone_enabled sysctl now?
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Personal FreeBSD PKGBASE Update Server
2023-06-26: https://github.com/freebsd/freebsd-src/commit/ee0aa1ce12b3caea34477a31e9d2111a329e33b9 to main (tagged release/14.0.0).
- What version of ZFS at FreeBSD solves the block cloning issue?
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Installing FreeBSD 14 Stable on an T480 Laptop w/ an Encrypted Home Directory
It's not yet in FreeBSD base so if you want to test it you'll have to use the patch from the PR: https://github.com/freebsd/freebsd-src/pull/881
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FreeBSD 14.0 Delivering Great Performance Uplift
Lots of great work by many people. But I bet this guy and his optimizations to the vfs and locking has made a significant impact.
https://github.com/freebsd/freebsd-src/commits?author=mjguzi...
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ZFS 2.2.1: Block Cloning disabled due to data corruption
and then there were deep concerns about the stability of same, so vfs.zfs.bclone_enabled = 0 was left in-place
https://github.com/freebsd/freebsd-src/commit/068913e4ba3dd9...
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FreeBSD 14.0-Release Announcement
Well there are some examples:
https://github.com/freebsd/freebsd-src/tree/main/share/examp...
But yeah that pf.conf could be expanded allot, but there are many source to cobble a conf together. My conf is massive but 99.9% commented out so i have my "template" for nearly everything, from mail to web to blacklistd etc.
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Git cherry-pick and revert use 3-way merge
The BSD version is sort of very recent, for what it's worth -- FreeBSD imported a not fully functional version in 2017 and has seen more work on it in 2022: https://github.com/freebsd/freebsd-src/commits/main/usr.bin/... , but the default version shipped is still GNU diff3: https://man.freebsd.org/cgi/man.cgi?query=diff3&apropos=0&se... .
What are some alternatives?
Arblib.jl - Thin, efficient wrapper around Arb library (http://arblib.org/)
podman - Podman: A tool for managing OCI containers and pods.
calc - C-style arbitrary precision calculator
musl - unofficial musl mirror git://git.musl-libc.org/musl
MultiFloats.jl - Fast, SIMD-accelerated extended-precision arithmetic for Julia
darwin-xnu - Legacy mirror of Darwin Kernel. Replaced by https://github.com/apple-oss-distributions/xnu
tiny-bignum-c - Small portable multiple-precision unsigned integer arithmetic in C
src - Read-only git conversion of OpenBSD's official CVS src repository. Pull requests not accepted - send diffs to the tech@ mailing list.
The-RLIBM-Project - A combined repository for all RLIBM prototypes
coreutils - upstream mirror
SuiteSparse - SuiteSparse: a suite of sparse matrix packages by @DrTimothyAldenDavis et al. with native CMake support
rss-proxy - RSS-proxy allows you to do create an RSS or ATOM feed of almost any website, just by analyzing just the static HTML structure.