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submitted 2 months ago by [email protected] to c/[email protected]

cross-posted from: https://lemmy.world/post/31184706

C is one of the top languages in terms of speed, memory and energy

https://www.threads.com/@engineerscodex/post/C9_R-uhvGbv?hl=en

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[-] [email protected] 35 points 2 months ago

For those who don't want to open threads, it's a link to a paper on energy efficiency of programming languages.

[-] [email protected] 40 points 2 months ago
[-] [email protected] 13 points 2 months ago

Also the difference between TS and JS doesn't make sense at first glance. 🤷‍♂️ I guess I need to read the research.

[-] [email protected] 6 points 2 months ago

My first thought is perhaps the TS is not targeting ESNext so they're getting hit with polyfills or something

[-] [email protected] 1 points 2 months ago* (last edited 2 months ago)

It does, the "compiler" adds a bunch of extra garbage for extra safety that really does have an impact.

[-] [email protected] 4 points 2 months ago

I thought the idea of TS is that it strongly types everything so that the JS interpreter doesn't waste all of its time trying to figure out the best way to store a variable in RAM.

[-] [email protected] 9 points 2 months ago

TS is compiled to JS, so the JS interpreter isn't privy to the type information. TS is basically a robust static analysis tool

[-] [email protected] 5 points 2 months ago

The code is ultimately ran in a JS interpreter. AFAIK TS transpiles into JS, there's no TS specific interpreter. But such a huge difference is unexpected to me.

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[-] [email protected] 1 points 2 months ago
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[-] [email protected] 1 points 2 months ago

Only if you choose a lower language level as the target. Given these results I suspect the researchers had it output JS for something like ES5, meaning a bunch of polyfills for old browsers that they didn't include in the JS-native implementation..

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[-] [email protected] 7 points 2 months ago

I guess we can take the overhead of rust considering all the advantages. Go however... can't even.

[-] [email protected] 3 points 2 months ago

Even Haskell is higher on the list than Go, which surprises me a lot

[-] [email protected] 2 points 2 months ago

But Go has go faster stripes in the logo! Google wouldn't make false advertising, would they?

[-] [email protected] 2 points 2 months ago

Now we just need a language with flames in the logq

[-] [email protected] 6 points 2 months ago* (last edited 2 months ago)

For Lua I think it's just for the interpreted version, I've heard that LuaJIT is amazingly fast (comparable to C++ code), and that's what for example Löve (game engine) uses, and probably many other projects as well.

[-] [email protected] 5 points 2 months ago

I would be interested in how things like MATLAB and octave compare to R and python. But I guess it doesn't matter as much because the relative time of those being run in a data analysis or research context is probably relatively low compared to production code.

[-] [email protected] 7 points 2 months ago

Is there a lot of computation-intensive code being written in pure Python? My impression was that the numpy/pandas/polars etc kind of stuff was powered by languages like fortran, rust and c++.

[-] [email protected] 1 points 2 months ago

The popular well crafted ones are, but not all are well crafted.

[-] [email protected] 5 points 2 months ago

WASM would be interesting as well, because lots of stuff can be compiled to it to run on the web

[-] [email protected] 2 points 2 months ago* (last edited 2 months ago)

Indeed, here's an example - my climate-system model web-app, written in scala running (mainly) in wasm
(note: that was compiled with scala-js 1.17, they say latest 1.19 does wasm faster, I didn't yet compare).
[ Edit: note wasm variant only works with most recent browsers, maybe with experimental options set - if not try without ?wasm ]

[-] [email protected] 5 points 2 months ago

I have no clue what I am looking at but it is absolutely mesmerizing.

[-] [email protected] 2 points 2 months ago

Oh, it's designed for a big desktop screen, although it just happens to work on mobile devices too - their compute power is enough, but to understand the interactions of complex systems, we need space.

[-] [email protected] 4 points 2 months ago

Looking at the Energy/Time ratios (lower is better) on page 15 is also interesting, it gives an idea of how "power hungry per CPU cycle" each language might be. Python's very high

[-] [email protected] 3 points 2 months ago

Every time I get surprised by the efficiency of Lisp! I guess they mean Common Lisp there, not Clojure or any modern dialect.

[-] [email protected] 2 points 2 months ago

For Haskell to land that low on the list tells me they either couldn't find a good Haskell programmer and/or weren't using GHC.

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[-] [email protected] 1 points 2 months ago

Does the paper take into account the energy required to compile the code, the complexity of debugging and thus the required re-compilations after making small changes? Because IMHO that should all be part of the equation.

[-] [email protected] 11 points 2 months ago

It's a good question, but I think the amount of time spent compiling a language is going to be pretty tiny compared to the amount of time the application is running.

Still - "energy efficiency" may be the worst metric to use when choosing a language.

[-] [email protected] 5 points 2 months ago

Energy efficiency strongly correlates to datacentre costs.

[-] [email protected] 5 points 2 months ago

And battery costs, including charging time, for a lot of devices. Users generally aren't happy with devices that run out of juice all the time.

[-] [email protected] 5 points 2 months ago

They compile each benchmark solution as needed, following the CLBG guidelines, but they do not measure or report the energy consumed during the compilation step.

Time to write our own paper with regex and compiler flags.

this post was submitted on 11 Jun 2025
87 points (86.6% liked)

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