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Energy Efficiency in Programming Languages

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35 pointsingve22 comments

Previous discussion on HN, 3 days ago: https://news.ycombinator.com/item?id=15249289

I've always suspected using "like really productive" languages creates it's own scalability problem in production. Ruby/Python/Node/PHP consuming anywhere from 2x to 15x the amount of energy and time as a language like Java/C# comes as no surprise, which likely means you'll need a corresponding increase in servers for particular use cases.

What's not a surprise is C stomping everything with a lead boot. I am surprised that Fortran is a lower than it is (considering its role in HPC/research). It's no surprise to see Java leading the virtual machine pack on speed, I thought it'd take a larger hit on energy consumption due to JIT.

But Rust, WOW. Have we finally created the perfect language? Always something I've wanted to learn, now I think I have a good reason!

Here's the paper - http://greenlab.di.uminho.pt/wp-content/uploads/2017/09/pape...

On average, compiled languages consumed 120J to execute the solutions, while for virtual machine and interpreted languages this value was 576J and 2365J, respectively.

Does this mean for mobile devices like phones, tablets. watches, VR/AR headsets, etc, would should prefer compiled languages?

If your primary metric for good software is {speed,memory use,energy efficiency} then yes.

On a broad scale, yes. But it also proves that the efficiency of particular languages depends on the problem at hand. For example, if your problem is searching for a pattern in large strings, a simple Perl program using the builtin regex support will easily beat a C/C++ program that hand-rolls pattern matching, because Perl's regex engine has been optimized for over two decades.

On the topic of mobile devices, I recall the Nokia N900, which ran mostly C and C++ software. Its UI performance was comparable to contemporary smartphones even though it only had 256 MB RAM and a single-core 600 MHz CPU. (Of course, a major part of today's phones' slow UI is all the bullshit and spying that apps are doing in the background.)

Linux and Darwin is written with C. They are the OSs of Android and iOS.

But would be nice to have some mobile apps written with C.

Most Android apps use a handful of native code libraries which are bundled inside the apk. It's usual nowadays to only write the UI using Java and use C for the rest.

Linux is just the kernel for Android, the whole userspace is not written in C, and that is what matters in the end for performance and efficiency.

Lots of mobile apps are written in Objective-C, and Objective-C is C. A superset of C to be exact.

Since it's a single hybrid language, it's trivial to remove slower features fro, performance-intensive parts.

See my UIKonf talk https://www.youtube.com/watch?v=kHG_zw7%205SjE&feature=youtu...

Or my book: https://www.amazon.com/gp/product/0321842847/ref=as_li_tl?ie...

Before all of you go out taking these results as definite truth, remember that a language benchmark is only as good as the particular implementations. A $LANGUAGE fanboy can easily game the benchmark by overoptimizing the $LANGUAGE implementations into unmaintainable atrocities that perform extremely well, thus making people think that average $LANGUAGE programs will exhibit the same performance/efficiency/resource usage characteristics.

There's no easy way to guard against this problem when you're only a handful of researchers. If you have a large team with a background in a lot of languages, you can have them write and peer-review implementations that are idiomatic (i.e. representative of the language's practical usage).

And before you all go out taking the possibility of scepticism as an actual motivation to be sceptical, remember that conclusions do not need to be proven beyond all doubt to be reasonably believed.

It's nice to see that some newer languages like Rust and Swift are performing well!

Well, Rust and Go are performing very well. Swift performs worse than languages like Java, Haskell, OCaml, C# and Lisp.

-- Edit --

My bad, I only looked at the paper. The results (https://sites.google.com/view/energy-efficiency-languages/re...) show that Swift and Go are doing about as well as Java. (Which means they're right behind C, C++, Rust and Fortran).

The summary results for Swift do not reflect the individual tests. There is a single anomalous test, reflex-redux, where the Swift implementation sucks badly.

Anecdotally, Swift string handling makes it easy to do the right thing when handling Unicode strings, but also makes it easy to burn up several orders of magnitude too much CPU when you use those functions for simple tasks. I once saved three orders of magnitude clock time by dropping to POSIX IO and C run time library string handling for an application that needed to read a text file containing 10000 lines of 81 digits at launch and process them as single digits.

That's true. Given how young Swift is, though, I think it shows that its future is bright.

I don't intuitively understand why Go was so space efficient (#2 and ahead of C) but then so time+energy inefficient wrt C (3.23 and 2.83 vs 1.00 and 1.00).

Any clues?

My guess would be that Go's GC (which is supposedly pretty good) takes care of space but pushes up time and CPU usage anyway.

No, GC shouldn't take that much time.

I assume it just adds up in these kinds of "benchmark" tests.

I hope C/C++ programming picks up again.

Picks up? C/C++ never went anywhere(except you know web stuff).

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