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pcwalton's profile
Patrick Walton
Patrick Walton
Patrick Walton
@pcwalton

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Patrick Walton

@pcwalton

Research engineer at Mozilla

San Francisco, CA
pcwalton.github.io
Joined November 2009

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    1. Biappi‏ @Biappi 7 Feb 2019
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      Biappi Retweeted Biappi

      For the other timezone, because I feel this is worth repeating.https://twitter.com/Biappi/status/1093282726512377857 …

      Biappi added,

      Biappi @Biappi
      is this a "problem" of the language, or a misunderstanding of floating point arithmetic?! (that they teach the second year of computer science undergrad, but we don't study it because we never invert a binary tree in our "everyday work") https://twitter.com/twostraws/status/1093087954212478976 …
      Show this thread
      1 reply 0 retweets 2 likes
    2. Steve Canon‏ @stephentyrone 7 Feb 2019
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      Replying to @Biappi

      Languages and tooling can help here: - we could warn that 0.1, 0.2, and 0.3 are not exactly representable, and report the value to which they have been rounded. - we could default decimal literals to a decimal floating-point type instead of Double.

      4 replies 3 retweets 16 likes
    3. Nate Cook‏ @nnnnnnnn 7 Feb 2019
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      Replying to @stephentyrone @Biappi

      The second one is the most interesting to me, since it's akin to what Swift did with strings. What you get in other languages when working with Unicode text feels a bit like these floating-point issues

      2 replies 0 retweets 3 likes
    4. Matthew Johnson‏ @anandabits 7 Feb 2019
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      Replying to @nnnnnnnn @stephentyrone @Biappi

      What would be the consequences of using decimal floating point? Can it be optimized as well as binary floating point? It’s pretty rare to care about the exact decimal value if you’re using floating point correctly, isn’t it?

      3 replies 0 retweets 0 likes
    5. Steve Canon‏ @stephentyrone 7 Feb 2019
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      Replying to @anandabits @nnnnnnnn @Biappi

      To your optimization question: yes, there is absolutely a performance tradeoff (roughly an order of magnitude for computations); the guidance really can't be "just always use double".

      1 reply 0 retweets 2 likes
    6. Steve Canon‏ @stephentyrone 7 Feb 2019
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      Replying to @stephentyrone @anandabits and

      But: (a) safer defaults with simple access to faster alternatives is generally accepted as a reasonable language design choice (b) broader SW use of decimal FP is the lever that gets us to better and faster HW support for decimal FP.

      2 replies 0 retweets 3 likes
    7. Joe Groff‏ @jckarter 7 Feb 2019
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      Replying to @stephentyrone @anandabits and

      I think it’s not obvious that decimal floats are a safer default. Going beyond 0.1+0.2==0.3, they’re still ultimately inexact, have even more weird representations than binary floats, and less ideal rounding error accumulation

      3 replies 0 retweets 14 likes
    8. Steve Canon‏ @stephentyrone 7 Feb 2019
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      Replying to @jckarter @anandabits and

      All true! It's not clear. But, there are really two overlapping use cases for floating-point: (a) algorithms that are resilient to changes in the scaling of their inputs. (b) algorithms that have known scaling, but need to represent non-integral values.

      1 reply 0 retweets 2 likes
    9. Steve Canon‏ @stephentyrone 7 Feb 2019
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      Replying to @stephentyrone @jckarter and

      One can argue that (b) would be better served by fixed-point types, which is almost true, except that if you're writing such code you usually end up calling some library functions, and *those* need to be resilient to scaling because they have multiple clients.

      2 replies 0 retweets 2 likes
      Patrick Walton‏ @pcwalton 7 Feb 2019
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      Replying to @stephentyrone @jckarter and

      Interesting way to look at it. I’m basically in camp (b) in vector graphics rendering. There’s no way to eliminate error because the whole problem is discretizing continuous functions, so I might as well use FP for better library/HW support.

      8:51 AM - 7 Feb 2019
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      • Steve Canon
      2 replies 0 retweets 1 like
        1. New conversation
        2. Steve Canon‏ @stephentyrone 7 Feb 2019
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          Replying to @pcwalton @jckarter and

          For graphics specifically, there's also the fact that floating point is just significantly faster on all current hardware, provided you can find enough parallel work to do.

          1 reply 0 retweets 2 likes
        3. Patrick Walton‏ @pcwalton 7 Feb 2019
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          Replying to @stephentyrone @jckarter and

          Yep. Though it’s interesting that the rasterizer converts to fixed point internally. (Also common to pack vertex data into fixed point for compression—I do this.)

          0 replies 0 retweets 0 likes
        4. End of conversation
        1. New conversation
        2. Rich Felker‏ @RichFelker 7 Feb 2019
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          Replying to @pcwalton @stephentyrone and

          The big question that *should* be deciding for float vs fixed is whether you care more about translation-invariance or scale-invariance of your geometry.

          1 reply 0 retweets 0 likes
        3. Steve Canon‏ @stephentyrone 7 Feb 2019
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          Replying to @RichFelker @pcwalton and

          That, and whether or not you can tolerate wrapping / undefined overflow.

          1 reply 0 retweets 1 like
        4. 2 more replies

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