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BigNums: JavaScript is killing it [Node.js v24.0.1]

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  BigNums: JavaScript is killing it [Node.js v24.0.1] Mild Shock <janburse@fastmail.fm> - 2025-05-11 11:36 +1000
    Denoising Fixpoint Operator in Prolog (Was: BigNums: JavaScript is killing it [Node.js v24.0.1]) Mild Shock <janburse@fastmail.fm> - 2025-05-14 11:59 +1000

#14506 — BigNums: JavaScript is killing it [Node.js v24.0.1]

Hi,

Just noticed that Node.js v24.0.1 has mostlikely
faster BigNums. Here is some test:

/* Dogelog Player 1.3.3 for JavaScript */
?- time(_ is 7^(8^9)).
% Zeit 3813 ms, GC 0 ms, Lips 5, Uhr 11.05.2025 11:31
true.

Not bad , current bun.js cannot do it. And it is
almost like this here based on GMP:

/* SWI-Prolog 9.3.21 */
?- time(_ is 7^(8^9)).
% 0 inferences, 1.594 CPU in 1.677 seconds
true

Bye

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#14508 — Denoising Fixpoint Operator in Prolog (Was: BigNums: JavaScript is killing it [Node.js v24.0.1])

Prolog and logic programming has traditionally
payed a lot of attention to fix point theory. For
example one can defin the least herbrand model
of a definite program.

Anybody already experimented in pure Prolog code
with stable diffusion, aka a fixpoint operator that
is a denoising autoencoder and do the thing as a
kernel operator over a grid?

P.S.: Interesting fixpoint scenarios and
maybe even new hardware:

GENERATIVE PSEUDO-INVERSE MEMORY
https://openreview.net/pdf?id=Harn4_EZBw

Mild Shock schrieb:
> Hi,
> 
> Just noticed that Node.js v24.0.1 has mostlikely
> faster BigNums. Here is some test:
> 
> /* Dogelog Player 1.3.3 for JavaScript */
> ?- time(_ is 7^(8^9)).
> % Zeit 3813 ms, GC 0 ms, Lips 5, Uhr 11.05.2025 11:31
> true.
> 
> Not bad , current bun.js cannot do it. And it is
> almost like this here based on GMP:
> 
> /* SWI-Prolog 9.3.21 */
> ?- time(_ is 7^(8^9)).
> % 0 inferences, 1.594 CPU in 1.677 seconds
> true
> 
> Bye

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