A bit old but still interesting

  • FizzyOrange@programming.dev
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    2 days ago

    They chose an “optimized” set of algorithms from “The Computer Language Benchmarks Game” to produce results for well-optimized code in each language.

    Honestly that’s all you need to know to throw this paper away.

      • FizzyOrange@programming.dev
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        2 days ago

        It’s a very heavily gamed benchmark. The most frequent issues I’ve seen are:

        • Different uses of multi-threading - some submissions use it, some don’t.
        • Different algorithms for the same problem.
        • Calling into C libraries to do the actual work. Lots of the Python submissions do this.

        They’ve finally started labelling stupid submissions with “contentious” labels at least, but not when this study was done.

          • FizzyOrange@programming.dev
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            6 hours ago

            I agree, but if you take away the hard numbers from this (which you should) all you’re left with is what we all already knew from experience: fast languages are more energy efficient, C, Rust, Go, Java etc. are fast; Python, Ruby etc. are super slow.

            It doesn’t add anything at all.

            • atzanteol@sh.itjust.works
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              3 hours ago

              Well… No. You’re reading the title. Read the document.

              “We all know” is the gateway to ignorance. You need to test common knowledge to see if it’s really true. Just assuming it is isn’t knowledge, it’s guessing.

              Second - it’s not always true:

              for the fasta benchmark, Fortran is the second most energy efficient language, but falls off 6 positions down if ordered by execution time.

              Thirdly - they also did testing of memory usage to see if it was involved in energy usage.