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propensive's profile
Jon Pretty
Jon Pretty
Jon Pretty
@propensive

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Jon Pretty

@propensive

Supporting Scala through professional training and open-source software. Responsible for Magnolia, Fury, Scala World and Functional Africa.

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propensive.com
Joined July 2010

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    1. Grzegorz Kossakowski‏ @gkossakowski 9 May 2018

      How do you estimate the potential gain of the rare case of a software rewrite that makes sense? You want to differentiate between the two outcomes: - "this is one the best pieces of work I've ever done" - "we tried our best; I wished we knew better from the start"

      1 reply 1 retweet 18 likes
      Show this thread
    2. Grzegorz Kossakowski‏ @gkossakowski 9 May 2018

      I went through that exercise when software == compiler. A thread! Let me start off with admitting I'm cheating by narrowing down the gain to performance. Now that we got this out of the way, the answer is reasoning from first principles.

      1 reply 0 retweets 0 likes
      Show this thread
    3. Grzegorz Kossakowski‏ @gkossakowski 9 May 2018

      The question is: what's the gap between compiler's performance and the inherent complexity of the problem (e.g. language features) normalized by how quickly computers can compute?

      1 reply 0 retweets 0 likes
      Show this thread
    4. Grzegorz Kossakowski‏ @gkossakowski 9 May 2018

      The gap is the estimate of the bloat and excess, use of inefficient algorithms and datastructures in the implementation. I wondered about this for Scala compiler when I was trying to understand whether Scala has a design flaw. So I ran an experiment.

      1 reply 0 retweets 0 likes
      Show this thread
    5. Grzegorz Kossakowski‏ @gkossakowski 9 May 2018

      I generated Java and Scala code side-by-side whose compilation by either javac and scalac (and dottyc) requires the same amount of work. The result ispic.twitter.com/aQWFXOib7k

      1 reply 3 retweets 5 likes
      Show this thread
    6. Grzegorz Kossakowski‏ @gkossakowski 9 May 2018

      I gasped when I saw this chart for the first time. Dotc is a rewrite of Scala from scratch and it landed exactly at the same performance. For a rewrite of such scale, it's hard to believe no extraterrestrial forces were involved in shaping that chart.

      1 reply 1 retweet 4 likes
      Show this thread
    7. Grzegorz Kossakowski‏ @gkossakowski 9 May 2018

      I'm digressing, though. The gap is angular in this chart: you want to compare the relative slopes of the curves for javac and scalac. The comparison shows that scalac/dotc is 6x slower than javac for solving the task of the same complexity.

      1 reply 0 retweets 2 likes
      Show this thread
    8. Grzegorz Kossakowski‏ @gkossakowski 9 May 2018

      The lower limit of improving scalac/dotc performance is 6x for this task. I don't know if javac solves the compilation task optimally so this experiment sets just the lower limit.

      2 replies 0 retweets 0 likes
      Show this thread
    9. Jon Pretty‏ @propensive 9 May 2018
      Replying to @gkossakowski

      I think the comparison is a bit misleading, though... even if the input provided to Scala is the same complexity as Java, the fact that Scala *can* accept more complex input put a dynamic requirement (ie more work) on Scalac which Javac doesn't have.

      2 replies 0 retweets 0 likes
    10. Grzegorz Kossakowski‏ @gkossakowski 9 May 2018
      Replying to @propensive

      The comparison is to establish the performance gap relative to the difficulty of the task. The next question is how hard would it be to structure the compiler to scale up and down with the difficulty of an input. My hunch is that it's actually not that hard.

      1 reply 2 retweets 1 like
      Jon Pretty‏ @propensive 9 May 2018
      Replying to @gkossakowski

      My hunch is less optimistic, I think. ;)

      10:46 AM - 9 May 2018 from East Worldham, England
      1 reply 0 retweets 0 likes
        1. New conversation
        2. Grzegorz Kossakowski‏ @gkossakowski 9 May 2018
          Replying to @propensive

          If the gap was more narrow, there would be little value in trying to figure out how to scale the compiler up and down. But the potential win is big enough that you know upfront it's worth the effort.

          1 reply 1 retweet 3 likes
        3. Grzegorz Kossakowski‏ @gkossakowski 9 May 2018
          Replying to @gkossakowski @propensive

          And the key here is that it gives you a clear objective: you have a very simple setting and a large gap to close. You keep going until you closed the gap or you have a good story for why it can't be done. I find it better for morale than profiling which is shooting in the dark.

          0 replies 1 retweet 5 likes
        4. End of conversation

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