Stuffed-Na(a)N: stuff your NaNs | Hacker News Reader

Stuffed-Na(a)N: stuff your NaNs

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156 pointsdgroshev58 comments

This is usually called NaN-boxing and is often used to implement dynamic languages.

https://piotrduperas.com/posts/nan-boxing

I appreciate this article a lot more because it contains an iota of benchmarking with an explanation about why this might be more performant. Especially since my first thought was 'wouldn't this require more instructions to be executed?'

The original post seems really weird to me. I would have dismissed it as someone's hobby project, but... that doesn't seem like what it's trying to be.

It's a joke project.

"More instructions to execute" is not synonymous with "slower".

NaNboxing lets you use less memory on certain use cases. Because memory access is slow and caches are fixed size, this is usually a performance win, even if you have to do a few extra ops on every access.

I mean, a modern computer is operating the gigahertz range. Adding a few extra bitwise instructions might be something like a nanosecond. Which is absolutely fleeting compared to memory operations.

I wonder if IEEE-754 designers anticipated this use case during development. Great article - this kind of "outside-the-normal-use-case" requires a very careful reading of the specifications/guarantees of the language.

IEEE-754 seems to say that NaN payloads are designed to contain "retrospective diagnostic information inherited from invalid or unavailable data and results". While NaN boxing in particular probably wasn't the intention, untouched payloads in general absolutely were.

It's especially useful since everything is 64 bits uniformly.

Like JavaScript. Which should immediately raise the question how it could possibly work on engines that employ it themselves. Turns out... it won't.

Are there any security implications of NaN-Boxing?

If I encode data into the exponent of these NaN values, propagate them around the internet, and decode them elsewhere.... is that a security risk? Or this just falls into the category of "weird encryption"

Define security risk. Obviously this data could come from untrusted sources. Another consideration is that this data may not serialize correctly: most text serialization protocols will not distinguish different NaN values. It's possible for there to be some data confusion in your pipeline as well, if you don't control all the code that touches those bytes.

I'd be surprised. It's surprisingly difficult to setialize NaN values. Can't do it on JSON, for example.

Lots of formats just put the IEEE-754 bytes on the wire, as-is. For example, Protocol Buffers: https://protobuf.dev/programming-guides/encoding/

This doesn't work on Firefox, as it normalizes NaNs as they're extracted from ArrayBuffers. Presumably because SpiderMonkey uses NaN-boxing itself, and thus just doesn't have any way to represent actual non-canonical NaN floats.

Dammit Mozilla, first no WebGPU, now this?! /s

The spec mandates normalization of NaNs in ArrayBuffers. If other engines do not normalize, I believe it's a bug in those engines!

Chromium & Node (i.e. V8) do seem to just not normalize:

    arr = new Float64Array([0]);
    arr[0] = new Float64Array(new BigUint64Array([-123n]).buffer)[0];
    [...new Uint8Array(arr.buffer)] // [133, 255, 255, 255, 255, 255, 255, 255]

Running the following snippets:

    f = new Float64Array(1)
    dv = new DataView(f.buffer)
    dv.setBigInt64(0, -123n)
    console.log([...new Uint8Array(f.buffer)])

    f = new Float64Array(1)
    new BigUint64Array(f.buffer)[0] = -123n
    console.log([...new Uint8Array(f.buffer)])

    f = new Float64Array(1)
    f[0] = new Float64Array(new BigUint64Array([-123n]).buffer)[0]
    console.log([...new Uint8Array(f.buffer)])

    f = new Float64Array([NaN])
    console.log([...new Uint8Array(f.buffer)])

I get on Chrome:

    [255, 255, 255, 255, 255, 255, 255, 133]
    [133, 255, 255, 255, 255, 255, 255, 255]
    [133, 255, 255, 255, 255, 255, 255, 255]
    [0, 0, 0, 0, 0, 0, 248, 127]

And on Firefox:

    [ 255, 255, 255, 255, 255, 255, 255, 133 ]
    [ 133, 255, 255, 255, 255, 255, 255, 255 ]
    [ 0, 0, 0, 0, 0, 0, 248, 127 ]
    [ 0, 0, 0, 0, 0, 0, 248, 127 ]

It looks like both implementations are buggy, Since both the DataView and buffer versions should be normalized.

https://bugzilla.mozilla.org/show_bug.cgi?id=1393085

Note that there are a lot of exciting new float-related functions in C23, many related to NaN handling, signed zeros, or precision in edge cases. Some have been in glibc for years; others not yet.

The API for `getpayload`/`setpayload`/`setpayloadsig` looks a little funny but it's easy enough to wrap (just consider the edge cases; in particular remember that whether 0 is valid for quiet or signaling NaNs is platform-dependent).

Finally we have a reliable `roundeven`, and the convenience of directly calling `nextup`/`nextdown` (but note that you'll still only visit one of the zeros).

The new `fmaximum` family is confusing, but I think I have it clear:

  without 'imum' (legacy): prefer non-NaN
  with 'imum': zeros distinguished (-0 < +0)
  with '_num': prefer a non-NaN, also signal if applicable
  with '_mag': compare as if fabs first

`totalorder` has been often-desired; the other new comparisons not so much.

`rootn` and `compoundn` are surprisingly tricky to implement yourself. I still have one testcase I'm not sure why I have to hand-patch, and I'm not sure which implementation choice keeps the best precision (to say nothing of correct rounding mode).

> but note that you'll still only visit one of the zeros

Out of curiosity, isn't this what you'd pretty much universally want? Or maybe I misunderstand the intent here?

I find `nextup/`nextdown` useful for when you want to calculate `{f(nextdown(x)), f(x), f(nextup(x))}` and see if some property holds (or to what degree it holds) for both `x` and its surrounding values. It's annoying that one such surrounding value gets skipped.

That said, quite often you need to handle signed zero specially already, and if you don't the property you're testing might sufficiently differ in the interesting way for the smallest-magnitude subnormals.

I made a garlic nan: https://www.godbolt.org/z/enjv1c7Tf

I love it, how did I not think about this!

Since the first time I had Indian food sometime in 1987 I have always called naan “not a number bread” and no one has ever laughed. I feel like i may have found my people.

This may appeal: https://doubleyoudoubledoubleewe.www.dash.deeohhtee.dash-das...

I guess I just don't get it because the before & after cases don't seem to be showing remotely comparable use cases.

In the "before" use-cases, the programmer has accidentally written a bug and gets back a single NaN from a logical operation they performed as a result.

In the "after" cases, the programmer already has some data and explicitly decides to convert it to a NaN encoding. But instead of actually getting back a NaN that is secretly carrying their data, they actually get a whole array of NaN's, which duck type differently, and thus are likely to disappear into another NaN or an undefined if they are propagated through an API.

Like.. I get that the whole thing is supposed to be humorously absurd but... It just doesn't land unless there's something technical I'm missing to connect up the pieces.

It sounds like you might be interested in the Enterprise Edition

I'm curious why we have not-a-number, but not not-a-string, not-a-boolean, not-an-enum, and not-a-mycustomtype.

Because representing infinity is not possible outside of symbolic logic and isn’t encodable in floats. I think it is a simple numerical reason and not a deeper computer reason.

Well, infinity is totally representable with IEEE 754 floats. For example 1.0/0.0 == +inf, -1.0/0.0 == -inf, but 0.0/0.0 == NaN.

A smart compiler should be able to figure out a better value for 0/0, depending on context.

For example:

    for i in range(0, 10):
        print(i/0.0)

In this case it should probably print +inf when i == 0.

But:

    for i in range(-10, 10):
        print(i/0.0)

Now it is not clear, but at least we know it's an infinity so perhaps we need a special value +-inf.

And:

    for i in range(-10, 10):
        print(i/i)

In this case, the value for 0/0 can be 1.

Well, it could, but that would be against the spec. The hardware implements IEEE 754, most languages guarantee IEEE 754, and transforming code so that 0.0/0.0 doesn't result in NaN would be invalid.

I'm incorrect. there's a spec discussed here

https://www.gnu.org/software/libc/manual/html_node/Infinity-...

Some common numeric operations can result in non-numbers(eg division by zero - Nan or infinity).

Are there any common string operations with similar behavior?

Out of range substring? Some languages throw an error, others return an empty string. You could return a propagating NaS instead. I don't know what you'd use it for.

Charset translation.

Unicode’s � is basically a symbol for not-a-char.

Because IEEE 754 creators wanted to signal non-trapping error conditions for mathematically undefined operations, and they had a plenty of bit patterns to spare. Apparently back in the 70s and 80s in many cases it was preferable for a computation to go through and produce NaNs rather than trapping instantly when executing an undefined operation. I'm not quite sure what the reasoning was exactly.

In early FP machines the floating point processor could not take a trap at a faulting instruction precisely: it could only go bad things. Furthermore for programmers and hardware it can be very expensive. Rather than go through a loop and filter NaN out of results it becomes trap every time and resume and is a pain.

It avoids traps which are really inconvenient.

Because NaNs come from a standardized hardware-supported type, whereas the rest of those are largely language-specific (and you could consider null/nil as a "not-a-*" type for those in applicable languages; and there are languages which disallow NaN floats too, which completes all combinations).

Itanium had a bit for "not a thing" for integers (and perhaps some older hardware from around the time floats started being a thing had similar things), so the idea of hardware support for not-a-* isn't exclusive to floats, but evidently this hasn't caught on; generally it's messy because it needs a bit pattern to yoink, but many types already use all possible ones (whereas floats already needed to chop out some for infinities).

You can encode not-a-bool, not-a-(utf-8)-string and not-an-enum using one of the invalid bit patterns – that's exactly what the Rust compiler can do with its "niche optimization": https://www.0xatticus.com/posts/understanding_rust_niche/

C++ has std::optional for exactly that purpose.

Nana basically means that floating point arithmetic is predicting that your mathematical expression is an "indeterminate form", as in the thing you learn in calculus.

Not-a-boolean would be something like the much maligned tri-state bool pattern: https://thedailywtf.com/articles/What_Is_Truth_0x3f_

You missed not-a-NaN.

Also GNU, since it's not-a-unix.

I learned about this when trying to decode data from Firefox IndexedDB. (I was extracting Tana data.) Their structured clone data format uses nan-boxing for serialization.

‘Stuff your nan’ is this intentional? From a UK perspective this sounds wild

Stuffed Na(a)N as in naan bread https://commons.m.wikimedia.org/wiki/File:Stuffed_Naan.JPG

That's curious! Does anyone know why the spec was designed to allow so many possible NaN bit patterns? Seems like just one would do!

As long as you want all bit patterns to be Some float, there's not really one bit pattern you can chop out of somewhere (or, three, rather - both infinities, and NaN).

Taking, say, the 3 smallest subnormal numbers, or the three largest numbers, or whatever, would be extremely bad for allowing optimizations/algorithms/correctness checkers to reason about operations in the abstract.

You can put diagnostic information about the cause of the NaN in the bits. IEEE754 doesn’t mandate any format though, leaving it up to the implementation. You can check section 6 of IEEE754:2019 (which also talks about the possibility to use it to extend the standard to wider ranges, more infinities or other stuff)

Reminds me of using the highest bit(s) of 64-bit ints to stuff auxiliary data into lockfree algorithms. So long as you’re aware of your OS environment you can enable some efficiencies you couldn’t otherwise.

That's why OCaml has 63 bit integers by default: the language itself uses the last bit to help with GC.

The nan bits were intended to help provide more informative float error diagnostics at the language implementation level for non crashing code. I wonder if I’ll ever get to exploring it myself.

Four NaNs? Four? That's insane.

https://m.youtube.com/watch?v=feJlRDLX0iQ

well i totally relate to calling naan not-a-number bread, it's been stuck in my head ever since i learned about NaNs tbh

It's a shame this won't work on VAX.

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