To run perhaps. But what about the same metrics for debugging? How many hours do we spend debugging c/c++ issues?
True but it's also a cock to write in
What if we make a new language that extends it and makes it fun to write? What if we call it c+=1?
This doesn't account for all the comfort food the programmer will have to consume in order to keep themselves sane
Machine energy, definitely not programmer energy ;)
I would argue that because C is so hard to program in, even the claim to machine efficiency is arguable. Yes, if you have infinite time for implementation, then C is among the most efficient, but then the same applies to C++, Rust and Zig too, because with infinite time any artificial hurdle can be cleared by the programmer.
In practice however, programmers have limited time. That means they need to use the tools of the language to save themselves time. Languages with higher levels of abstraction make it easier, not harder, to reach high performance, assuming the abstractions don’t provide too much overhead. C++, Rust and Zig all apply in this domain.
An example is the situation where you need a hash map or B-Tree map to implement efficient lookups. The languages with higher abstraction give you reusable, high performance options. The C programmer will need to either roll his own, which may not be an option if time Is limited, or choose a lower-performance alternative.
I understand your point but come on, basic stuff has been implemented in a thousand libraries. There you go, a macro implementation
And how testable is that solution? Sure macros are helpful but testing and debugging them is a mess
Ah this ancient nonsense. Typescript and JavaScript get different results!
It's all based on
https://en.wikipedia.org/wiki/The_Computer_Language_Benchmarks_Game
Microbenchmarks which are heavily gamed. Though in fairness the overall results are fairly reasonable.
Still I don't think this "energy efficiency" result is worth talking about. Faster languages are more energy efficient. Who new?
Edit: this also has some hilarious visualisation WTFs - using dendograms for performance figures (figures 4-6)! Why on earth do figures 7-12 include line graphs?
Microbenchmarks which are heavily gamed
Which benchmarks aren't?
Private or obscure ones I guess.
Real-world (macro) benchmarks are at least harder to game, e.g. how long does it take to launch chrome and open Gmail? That's actually a useful task so if you speed it up, great!
Also these benchmarks are particularly easy to game because it's the actual benchmark itself that gets gamed (i.e. the code for each language); not the thing you are trying to measure with the benchmark (the compilers). Usually the benchmark is fixed and it's the targets that contort themselves to it, which is at least a little harder.
For example some of the benchmarks for language X literally just call into C libraries to do the work.
Private or obscure ones I guess.
Private and obscure benchmarks are very often gamed by the benchmarkers. It's very difficult to design a fair benchmark (e.g chrome can be optimized to load Gmail for obvious reasons. maybe we should choose a more fair website when comparing browsers? but which? how can we know that neither browser has optimizations specific for page X?). Obscure benchmarks are useless because we don't know if they measure the same thing. Private benchmarks are definitely fun but only useful to the author.
If a benchmark is well established you can be sure everyone is trying to game it.
Typescript and JavaScript get different results!
It does make sense, if you skim through the research paper (page 11). They aren't using performance.now() or whatever the state-of-the-art in JS currently is. Their measurements include invocation of the interpreter. And parsing TS involves bigger overhead than parsing JS.
I assume (didn't read the whole paper, honestly DGAF) they don't do that with compiled languages, because there's no way the gap between compiling C and Rust or C++ is that small.
Their measurements include invocation of the interpreter. And parsing TS involves bigger overhead than parsing JS.
But TS is compiled to JS so it's the same interpreter in both cases. If they're including the time for tsc in their benchmark then that's an even bigger WTF.
For those who don't want to open threads, it's a link to a paper on energy efficiency of programming languages.
Results
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
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.
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
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.
and in most cases that's not good enough to justify choosing c
I wouldn't justify using any language based on this metric alone.
I just learned about Zig, an effort to make a better C compatible language. It's been really good so far, I definitely recommend checking it out! It's early stages for the community, but the core language is pretty developed and is a breath of fresh air compared to C.
For raw computation, yes. Most programs aren't raw computation. They run in and out of memory a lot, or are tapping their feet while waiting 2ms for the SSD to get back to them. When we do have raw computation, it tends to be passed off to a C library, anyway, or else something that runs on a GPU.
We're not going to significantly reduce datacenter energy use just by rewriting everything in C.
We're not going to significantly reduce datacenter energy use just by rewriting everything in C.
We would however introduce a lot of bugs in the critical systems
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