[squeak-dev] Faster fibonacci

Nicolas Cellier nicolas.cellier.aka.nice at gmail.com
Tue Jan 28 06:52:27 UTC 2020


Hi Phil,
It is essential. Without it, it's very difficult to have correctly rounded
conversion float -> ascii decimal ->float.
Also, it may help to implement correctly rounded float functions.
GNU libc uses gmp.
Sometimes, you don't know the accuracy of a float calculus. There are
several possible easy strategies like changing the rounding direction, or
double the precision, and check the interval you obtain. It's far easier to
implement multi precision with integer than with float (though possible).
Chryptography heavily rely on large integer arithmetics.
Symbolic computer algebra also rely on it (the p-adic factorization of
polynomials may rapidly lead to huge integers).


Le mar. 28 janv. 2020 à 04:56, Eliot Miranda <eliot.miranda at gmail.com> a
écrit :

> Hi Phil,
>
> On Mon, Jan 27, 2020 at 6:07 PM Phil B <pbpublist at gmail.com> wrote:
>
>> That article was an interesting read.  One thing I've always been curious
>> about: what applications are people using the arbitrary precision stuff in
>> Squeak for?  (I generally make an effort to avoid straying into large
>> integers due to the performance implications, but the things I'm working on
>> don't require the precision they offer.)
>>
>
> One thing I used it for was in implementing 64-bit Spur VM above the
> 32-bit Spur implementation.
>
>
>>
>> On Mon, Jan 27, 2020 at 8:28 PM David T. Lewis <lewis at mail.msen.com>
>> wrote:
>>
>>> On Sun, Jan 26, 2020 at 01:59:21PM -0800, tim Rowledge wrote:
>>> > Remember the fun with we had calculating 4784969 fibonacci? There's an
>>> > interesting article in the Comm.ACM this month about the maybe-final
>>> > improvement in huge number multiplication;
>>> >
>>> https://cacm.acm.org/magazines/2020/1/241707-multiplication-hits-the-speed-limit/fulltext
>>> >
>>> > tim
>>> > --
>>> > tim Rowledge; tim at rowledge.org; http://www.rowledge.org/tim
>>> > Strange OpCodes: RIW: Re-Invent Wheel
>>> >
>>>
>>> Very interesting stuff. Probably not ready for a practical implementation
>>> in Squeak though. The performance benefits come into play only for very
>>> large numbers. The ACM article says:
>>>
>>>   The n(logn) bound means Harvey and van der Hoeven's algorithm is faster
>>>   than Schönhage and Strassen's algorithm, or Fürer's algorithm,
>>>   or any other known multiplication algorithm, provided n is sufficiently
>>>   large. For now, "sufficiently large" means almost unfathomably large:
>>>   Harvey and van der Hoeven's algorithm doesn't even kick in until the
>>>   number of bits in the two numbers being multiplied is greater than 2
>>>   raised to the 172912 power. (By comparison, the number of particles in
>>>   the observable Universe is commonly put at about 2270.)
>>>
>>> Checking the size of that boundary in Squeak:
>>>
>>>   (2 raisedTo: 172912) digitLength. ==> 21615
>>>   (2 raisedTo: 172912) asFloat. ==> Infinity
>>>
>>> I don't know nothin' about nothin' but even I know that 'Infinity' is
>>> a very big number ;-)
>>>
>>> But maybe that is missing the point. After all, we actually do a
>>> very good job of implementing large integer arithmetic in Squeak.
>>> Well OK, it is not exactly "we", Nicolas is the one who did most
>>> of it.
>>>
>>> Indeed, Squeak has no problem at all dealing with a rediculous
>>> expression such as this:
>>>
>>>   (((2 raisedTo: 172912)
>>>     cubed cubed cubed + 13 / (2 raisedTo: 172912)
>>>     * Float pi asScaledDecimal) asInteger) cubed cubed digitLength.
>>>
>>>      " ==> 5057678 "
>>>
>>> That's an integer with about 5 MB of internal representation. So maybe
>>> there is one more LargePositiveInteger>>digitMulXXXX method waiting
>>> to be created?
>>>
>>> Dave
>>>
>>>
>>>
>>
>
> --
> _,,,^..^,,,_
> best, Eliot
>
>
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