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Re^6: solve cubic equations (Java)

by no_slogan (Deacon)
on May 05, 2017 at 06:49 UTC ( #1189547=note: print w/replies, xml ) Need Help??

in reply to Re^5: solve cubic equations (Java)
in thread solve cubic equations

Now that I've had some time to kick it around, this is actually a great example. My Python program solves the sample problem in 1 second. In Perl, using Math::BigInt with the default backend, it takes 10 seconds. With the GMP backend, 5 seconds. With Math::GMP, 1 second, same as Python. By resorting to vile trickery, I was able to get the Perl to run in 0.5 seconds with no modules at all. Here's the kicker, though: the Python program runs in 0.1 second under PyPy (basically JIT compiled Python).

Replies are listed 'Best First'.
Re^7: solve cubic equations (Java)
by Anonymous Monk on May 05, 2017 at 08:29 UTC
Re^7: solve cubic equations (PyPy)
by LanX (Sage) on May 05, 2017 at 09:40 UTC
Re^7: solve cubic equations (JavaScript)
by LanX (Sage) on May 05, 2017 at 12:50 UTC
    Talking about JIT, maybe try benchmarking a JS version too. :)

    Cheers Rolf
    (addicted to the Perl Programming Language and ☆☆☆☆ :)
    Je suis Charlie!

Re^7: solve cubic equations (Java)
by vrk (Chaplain) on May 05, 2017 at 12:18 UTC

    That's intriguing. I admit I've never used Perl's bignum or bigint features for anything serious. Are you able to post short benchmark programs for this? It would be interesting to profile and figure out where the bottleneck is. Which version of Perl, by the way?

      Well, I hate to post a complete solution to one of their problems, so I've changed it around. The question is, given the first 10 outputs of this pseudo-random number generator:
      for (1..10) { $s = ($s*0x5deece66d + 0xb) % 2**48; say(($s>>17)%1000); }
      Find the initial value of the seed $s, which is a randomly-chosen number less than 2**17. Here are the comparisons of a brute-force search using several different modules:
      s/iter BigInt BigIntGMP GMP Perl BigInt 25.0 -- -42% -94% -100% BigIntGMP 14.4 73% -- -90% -99% GMP 1.47 1605% 885% -- -93% Perl 0.110 22701% 13070% 1238% --
      I'm running perl 5.24.1 on an aging MacBook. I could make the Perl faster, but it would require a 64-bit perl build. You could probably get good performance with Math::Int64, but I'll leave that as an exercise for the reader. Python is running in time comparable to the pure-Perl, and PyPy smokes them all at under a millisecond. Full code is below. You don't need to tell me that my benchmarking methodology is bad.

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