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Comment by mikewarot | Hacker News Reader

Does this result mean that aerodynamic simulation can be made far less compute intensive, like I think it does?

This could be as useful as Feynman diagrams are to physics calculations.

I worked in that field doing numerical many-body simulations of electron dynamics interacting with their environment in solid state devices like quantum dots, graphene, photonic waveguides & cavities , etc.

You would start from a Lagrangian formulation of the classical interaction, let's say Light-Matter, that would yield for example the Schrodinger and Maxwell equations. Following a Legendre transformation (there a post on the HN front page the other day on that) you end up with a so-called Hamilton operator from which you can derive a (huge) set of coupled differential equations which you then solve.

Here, if you wanted to increase temporal accuracy, it typically leads simply to longer calculation times.

We also tried a different approach using Feynman's path integrals and boy did that explode numerically. We optimized our programs to the point where everything was reduced to work on bits, but to no avail it was numerically unstable and the memory consumption when through the roof the longer or more accurate you wanted to make the simulation.

So, I would argue that NO, Feynman does not make it easier per se.

However, other groups made it work somehow.

As a starting point you can check that paper and it's references from the introduction section.

https://doi.org/10.1002/pssb.201000842

Okay I gotta be honest, and maybe I'm a little ignorant, but when did we start saying compute instead of computation? I feel like I went away on vacation and missed out on an in-joke. Should I be saying compute instead?

'Compute' connotes hardware, 'computation' does not.

Thank you! I always just assumed the difference was verb/noun.

Rather, 'compute' is a verb, 'computation' is a noun, and 'computationally' is an adverb (which is the most appropriate choice in the context of GGP's statement). All of these words refer to the same concept and may involve hardware computers (a more modern use of these words) or people-as-computers (the older, but still valid, use of the words).

Digging more into other internet discussions, a lot of people disagree about the usage. Many believe it's fine to use compute as a noun since it's a truncation of compute resources or compute nodes. Seems like an industry shibboleth like how data/stats people say "data" as a countable plural.

"Compute" as used upthread is in fact a noun. That's the point, it's a new word. And sort of a dumb one, but new nonetheless.

I think Compute is a gerund (a noun derived from a verb, like “swimming” as in the activity.)

It's been commonly used as a noun in the HPC / scientific computing space for a long time (relevant to this thread) typically talking about "compute bound" and "memory bound" algorithms. It's spilled over everywhere now that number crunching is hip for machine learning.

People favor shorter words for common concepts. We've started needing something equivalent to the 4-syllable "computation" frequently lately, so we nouned the verb "compute."

In the short-term, I think both words are fine. If it matters, use whichever one will best help you achieve your goals (e.g., if you're talking to a person who frequently uses n>>1 devices to perform computationally intensive workloads, you'll probably sound very mildly out-of-place nowadays if you don't choose "compute," which may or may not be the image you want to portray of yourself).

Slightly longer term, I expect this will be one of those cases where dictionaries and pedants try to settle the matter, nobody complies, and we have a "gray" vs "grey" scenario indefinitely. Beyond the next year or two I'm hesitant to place bets on the multitude of possible outcomes.

Way off-topic, patterns of speech like that might be a fun way to fingerprint the training data used for an LLM.

Compute as a noun may be a newer usage, but a noun sharing the same form as the verb is common in English, so it at least conforms to the patterns of the language.

For example dispute/disputation or repute/reputation ("a person of ill repute").

"compute" is used by the same people who call a collection of things a "stack".

I think of "compute" as referring to the resources for computations, rather than the computations themselves. For instance "compute-intensive" for an algorithm means that it is expensive in terms of computation resources, i.e. CPU cycles, as opposed to say I/O or network usage or something. Sometimes it refers to the actual physical hardware, sometimes to the theoretical resource of CPU time.

This exact topic came up in another thread a.few months ago, and I did some digging:

I believe the term "compute node" was first used in the context of the Intel ASCI Red supercomputer that was installed at Sandia in 1997. This later led to the Cray XT3, XT4, XT5 families of machines that used the same terminology.

But I believe the term was not in generic usage outside of those specific supercomputers until around 2005-2010.

And it is more recently that the term has been extended beyond referring to hardware.

It looks like the general trend of truncating nouns down to the verb they're based on instead of requiring the noun-ified form. You may have seen these:

1) an invitation to the party -> an invite to the party

2) I like that quotation. -> I like that quote.

3) I gave him a consultation. -> I gave him a consult.

You could even count:

4) What's the request? -> What's the ask?

Also, broken English seen on receptacle in China:

5) "The environment needs your conserve." (instead of "conservation")

What makes you think so? I quickly skimmed through and found nothing of the sort.

Edit: My take home message was that there is an equivalent higher order formulation which allows more structure and might be theoretically interesting. Usually higher order formulations are numerically more challenging.

Do Feynman diagrams reduce computation? my understanding is that Feynman diagrams are a clever simple way to document particle interaction. That is, more for human consumption than machine. My gut tells me it is the same as saying "we were able to reduce the computational complexity of our simulation because we had a good flowchart", by which I mean, It may help, but the flowchart is not the code(yes, uml, I am looking at you)

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