Which begs the question - aside from macho bragging rights, exactly what good is this kind of information?
Assume I did have a specific problem case for which performance in terms of memory, time or LoC mattered. As a first step, I'd write a specific benchmarkable implementation of my own problem (or one very like it.) Then I'd need to profile and optimise that implementation in my chosen language(s), as well as stop and think laterally about ways I might be able to optimise around that specific problem.
This is all assuming I'm working on a greenfields project where I have absolute free choice of language & runtime environment. Which happens for my personal projects, but never yet for a professional one.
Not to mention that in all other cases apart from this hypothetical where performance matters, I would take the most human-readable program over the most fast, lean or concise one.
Long story short, at no point can I see myself stopping and saying to myself. "You know what I need now? I need to see which programming language can generate a Mandelbrot set bitmap with the smallest memory footprint, without using any 'unfair' optimisation techniques."
A while back, I wrote a program to solve a puzzle. The more complex the puzzle, the longer it took to solve. Today, I might come up with a better algorithm, but back then, all I could find was a brute-force approach. The most complex puzzle I had seen at the time was taking hours to run.
The program was written in VB6, and it was just wasn't mean for CPU-intensive programs like that. If I were to write that program again today, I'd be looking at optimizing the code for speed, starting with the language.
So yes, the question -does- matter. Sometimes.
I bet that you could come up with a better algorithm now, even in VB6 if you had to, to get the run time down. I've seen people take "optimised" C solutions that run in hours and make them run in minutes, just by rewriting the algorithm and rethinking basic assumptions.
> ... I would take the most human-readable program over the most fast, lean or concise one
And some people do look at the source code for 2 dozen languages.
However, this was still posted under the title "Which programming language is the fastest?" - so I think it's worth exploring in exactly what ways that is or isn't useful information. Just as their own reason #3 says - "To show how difficult it can be to make meaningful comparisons"
I'd also question exactly how useful reading toy benchmark solution code is to real problems. The code to the benchmark problems is often nicely written, but if I have a problem to solve then wouldn't I be better off looking for samples of readable code that solve problems related to my specific problem domain?
You have to optimise to your use case, not some arbitrary general use case like "render a Mandelbrot set" or "calculate pi". If I have a slow On^2 Erlang algorithm, then I'm a lot better off looking at ways to rewrite it as Olog(n) instead of scrapping Erlang and moving to Java because it had a better score on the programming language shootout.
Sure, but the benchmark has to fit the use case. If you're designing a large web application, find benchmarks for large web applications or write benchmark cases yourself that match the use cases you're going to see and think you need to optimise for.
Anyone have any details on why that happened? These destroyed my ability to link to the shootout as data for showing that languages don't matter as much as implementations do, a nuance many newbies miss :(
http://thread.gmane.org/gmane.comp.python.pypy/7303/focus=73...
The help page has your answer, anyway. "Because I want to do fewer chores not more!" http://shootout.alioth.debian.org/help.php
http://shootout.alioth.debian.org/u32/compare.php?lang=cint
But let's note that here CINT is only being used as a C interpreter but a CINT script can call compiled classes/functions and compiled code can make callbacks to CINT interpreted functions - which I'm sure you understand would make it a lot faster.
