| Karim Belabas on Thu, 10 Apr 2014 01:12:47 +0200 |
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| Re: index calculus vs pollard rho |
* Bill Allombert [2014-04-09 23:43]:
> On Thu, Apr 03, 2014 at 05:28:24PM +0200, Bill Allombert wrote:
> > On Thu, Apr 03, 2014 at 03:22:02PM +0200, Pascal Molin wrote:
> > > The following znlog uses index calculus on a 46 bits subgroup, but p itself
> > > is large,
> > > this is slow (and memory-demanding)
> > >
> > > *gp* > p=nextprime(2^120); znlog(Mod(3,p),Mod(2,p),p-1)
> > >
> > > time = 51,617 ms.
> > >
> > > %21 = 391862826185609110238504885400229618
> > >
> > > while the same is easier to compute with pollard
> >
> > The issue is that the threshold for Pohlig-Hellman algorithm is set to 27 bits
> > independently of the size of p.
>
> I join some benchmarks:
> [27,29]:4:8 means we are computing in (Z/lZ)* with l of 29 bits in a subgroup of
> order p of 27 bit. The number after the first colon is the time for
> Shanks/Pollard rho and the second for the linear sieve.
> (Remember that Pollard rho has probabilistic running time).
>
> The thresholds are about:
> p -> l
> 27 -> 29
[...]
> 50 ->115
A simple linear regression on your threshold data yields
log_2(l) ~ a * log_2(p) + b
for a = 3.88, b = -78.78 (max. error ~ 5.55). Switching to a linear sieve when
log_2(p) >= 27
and
log_2(l) <= a * log_2(p) + b
will recover something close to your thresholds.
In fact, assuming your linear sieve implementation follow the theoretical
model, the threshold should rather be determined by something resembling
sqrt(p) ~ exp(C*(log l log log l)^(1/2))
that would yield
log(p) ~ 2C * (log l log log l)^(1/2)
A linear regression between (log_2(p))^2 and log_2(l) yields
log_2(l) ~ A (log_2(p))^2 + B
for A = 0.05, B = -6
These two models yield the following thresholds:
? for(P = 27, 50, printf("%d -> %3d\n",P, floor(a*P+b)))
27 -> 26
28 -> 29
29 -> 33
30 -> 37
31 -> 41
32 -> 45
33 -> 49
34 -> 53
35 -> 57
36 -> 60
37 -> 64
38 -> 68
39 -> 72
40 -> 76
41 -> 80
42 -> 84
43 -> 88
44 -> 92
45 -> 95
46 -> 99
47 -> 103
48 -> 107
49 -> 111
50 -> 115
? for(P = 27, 50, printf("%d -> %3d\n",P, floor(A*P^2+B)))
27 -> 30
28 -> 33
29 -> 36
30 -> 39
31 -> 42
32 -> 45
33 -> 48
34 -> 51
35 -> 55
36 -> 58
37 -> 62
38 -> 66
39 -> 70
40 -> 74
41 -> 78
42 -> 82
43 -> 86
44 -> 91
45 -> 95
46 -> 100
47 -> 104
48 -> 109
49 -> 114
50 -> 119
Presumably, the second one will scale better :-)
Cheers,
K.B.
--
Karim Belabas, IMB (UMR 5251) Tel: (+33) (0)5 40 00 26 17
Universite Bordeaux 1 Fax: (+33) (0)5 40 00 69 50
351, cours de la Liberation http://www.math.u-bordeaux1.fr/~kbelabas/
F-33405 Talence (France) http://pari.math.u-bordeaux1.fr/ [PARI/GP]
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