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
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
For those who don’t want to open threads, it’s a link to a paper on energy efficiency of programming languages.
Results
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.
Wonder what they used for the JS state since it’s dependent on the runtime.
Also the difference between TS and JS doesn’t make sense at first glance. 🤷♂️ I guess I need to read the research.
My first thought is perhaps the TS is not targeting ESNext so they’re getting hit with polyfills or something
It does, the “compiler” adds a bunch of extra garbage for extra safety that really does have an impact.
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.
TS is compiled to JS, so the JS interpreter isn’t privy to the type information. TS is basically a robust static analysis tool
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.
Its really not, have you noticed how an enum is transpiled? you end up with a function… a lot of other things follow the same pattern.
No they don’t. Enums are actually unique in being the only Typescript feature that requires code gen, and they consider that to have been a mistake.
In any case that’s not the cause of the difference here.
This isn’t true, there are other features that “emit code”, that includes: namespaces, decorators and some cases even async / await (when targeting ES5 or ES6).
Nope, have not noticed because I hate JavaScript with a passion. Thanks for educating me.
Just FYI the example that person gave would absolutely not explain a huge performance difference. I don’t think they understand what they’re looking at.
fair enough :D but it does happen and there are reasons for that: https://stackoverflow.com/questions/47363996/why-does-an-enum-transpile-into-a-function
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…
Not really, because this stuff also happens: https://stackoverflow.com/questions/20278095/enums-in-typescript-what-is-the-javascript-code-doing a function call always has an inpact.
Yeah sure, you found the one notorious TypeScript feature that actually emits code, but a) this feature is recommended against and not used much to my knowledge and, more importantly, b) you cannot tell me that you genuinely believe the use of TypeScript enums – which generate extra function calls for a very limited number of operations – will 5x the energy consumption of the entire program.
This isn’t true, there are other features that “emit code”, that includes: namespaces, decorators and some cases even async / await (when targeting ES5 or ES6).
Care to elaborate?
Here’s a good example: https://stackoverflow.com/questions/47363996/why-does-an-enum-transpile-into-a-function
That is not a good example. That is an immediate function call happening once when the program starts and certainly does not have a large impact like you are suggesting.
Every time I get surprised by the efficiency of Lisp! I guess they mean Common Lisp there, not Clojure or any modern dialect.
Yeah every time I see this chart I think “unless it’s performance critical, realtime, or embedded, why would I use anything else?” It’s very flexible, a joy to use, amazing interactive shell(s). Paren navigation is awesome. The build/tooling is not the best, but it is manageable.
That said, OCaml is nice too.
I guess we can take the overhead of rust considering all the advantages. Go however… can’t even.
Even Haskell is higher on the list than Go, which surprises me a lot
But Go has go faster stripes in the logo! Google wouldn’t make false advertising, would they?
Now we just need a language with flames in the logq
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.
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
WASM would be interesting as well, because lots of stuff can be compiled to it to run on the web
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 ]
I have no clue what I am looking at but it is absolutely mesmerizing.
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.
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.
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++.
The popular well crafted ones are, but not all are well crafted.
I have a hard time believing Java is that high up. I’d place it around c#.
Love the “I reject your empirical data and substitute my emotions” energy.
Why?
(A super slimmed down flavour of) Java runs on fucking simcards.
In theory Java is very similar to C#, an IL based JIT runtime with a GC, of course. So where is the difference coming from between the two? How is it better than pascal, a complied language? These are the questions I’m wondering about.
And it powers a lot of phones. People generally don’t like it when their phone needs to charge all the freaking time.
I ran Linux with KDE on my phone for a while and it for sure needed EVEN MORE charging all the time even though most of the system is C, with a sprinkle of C++ and QT.
But that is probably due to other inefficiencies and lack of optimization (which is fine, make it work first, optimize later)
Yeah, and Android has had some 16 years of “optimize later”. I have some very very limited experience with writing mobile apps and while I found it to be a PITA, there is clearly a lot of thought given to how to not eat all the battery and die in the ecosystem there. I would expect that kind of work to also be done at the JVM level.
If Windows Mobile had succeeded, C# likely would’ve been lower as well, just because there’d be more incentive to make a battery charge last longer.
C# has been very optimized since .NET Core (now .NET). Also jit compiler and everything around it.
Because usually they use the super fat flavor of Java. Jabba Fatt tier of lardiness Java.
I’m using the fattest of java (Kotlin) on the fattest of frameworks (Spring boot) and it is still decently fast on a 5 year old raspberry pi. I can hit precise 50 μs timings with it.
Imagine doing it in fat python (as opposed to micropython) like all the hip kids.
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Perl is disappointing too. I always considered it as an etalon shit-script.
That definitely raised an eyebrow for me. Admittedly I haven’t looked in a while but I thought I remembered perl being much more performant than ruby and python
I don’t see how that word makes sense in that phrase
English doesn’t have this word? Read it as a “standard unit”.
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.
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.
Energy efficiency strongly correlates to datacentre costs.
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.
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.