Challenge: optimizing isqrt

Christian Gollwitzer auriocus at gmx.de
Sat Nov 1 09:09:26 CET 2014


Addendum: If my method below works, you can also use it to speed up 
computations for n>2*1022, by splitting off an even power of two from 
the integer and computing the FP sqrt of the mantissa for the seed, i.e. 
doing the FP manually.

Am 01.11.14 09:02, schrieb Christian Gollwitzer:
> Hi Steven,
>
> let me start by answering from reverse:
>  > Q3: What is the largest value of n beyond which you can never use the
> float
>  > optimization?
>  >
>
> A3: There is no such value, besides the upper limit of floats (DBL_MAX~
> 10^308)
>
> P3: If you feed a perfect square into the floating point square root
> algorithm, with a mantissa of the root of length smaller than the
> bitwidth of your float, it will always come out perfectly. I.e.,
> computing sqrt(25) in FP math is no different from sqrt(25*2**200):
>
>  >>> 25*2**200
> 40173451106474756888549052308529065063055074844569820882534400L
>  >>> x=int(math.sqrt(25*2**200))
>  >>> x
> 6338253001141147007483516026880L
>  >>> x*x
> 40173451106474756888549052308529065063055074844569820882534400L
>  >>>
>
>
>
> Am 01.11.14 02:29, schrieb Steven D'Aprano:
>> There is an algorithm for calculating the integer square root of any
>> positive integer using only integer operations:
>>
>> def isqrt(n):
>>      if n < 0: raise ValueError
>>      if n == 0:
>>          return 0
>>      bits = n.bit_length()
>>      a, b = divmod(bits, 2)
>>      x = 2**(a+b)
>>      while True:
>>          y = (x + n//x)//2
>>          if y >= x:
>>              return x
>>          x = y
>
>> Q2: For values above M, is there a way of identifying which values of
>> n are
>> okay to use the optimized version?
>
> A2: Do it in a different way.
>
> Your above algorithm is obviously doing Heron- or Newton-Raphson
> iterations, so the same as with floating point math. The first line
> before the while loop computes some approximation to sqrt(n). Instead of
> doing bit shuffling, you could compute this by FP math and get closer to
> the desired result, unless the integer is too large to be represented by
> FP. Now, the terminating condition seems to rely on the fact that the
> initial estimate x>=sqrt(n), but I don't really understand it. My guess
> is that if you do x=int(sqrt(n)), then do the first iteration, then swap
> x and y such that x>y, then enter the loop, you would simply start with
> a better estimate in case that the significant bits can be represented
> by the float.
>
> So this is my try, but not thoroughly tested:
>
> def isqrt(n):
>      if n < 0: raise ValueError
>      if n == 0:
>          return 0
>      bits = n.bit_length()
>      # the highest exponent in 64bit IEEE is 1023
>      if n>2**1022:
>          a, b = divmod(bits, 2)
>          x = 2**(a+b)
>      else:
>          x=int(math.sqrt(n))
>          y=n//x
>          if x<y:
>              x,y = (y,x)
>
>      while True:
>          y = (x + n//x)//2
>          if y >= x:
>              return x
>          x = y
>
>
> Christian
>
>
>
>




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