A lower exp_E is (generally) better. So it pushes out polys with a higher exp_E (or in earlier commits, the lognorm, which seems related but I’m not sure).

[QUOTE=Dylan14;545624]A lower exp_E is (generally) better. So it pushes out polys with a higher exp_E (or in earlier commits, the lognorm, which seems related but I’m not sure).[/QUOTE]Thanks! Some other things make more sense now, as well.

What is the current thinking on the [I]ropteffort[/I] parameter? There is a wide range of values used throughout the [url=https://www.mersenneforum.org/showthread.php?t=24274]Improved params files for CADO[/url] thread, including some files which are missing it entirely.

At really low sizes, say under 115 digits, setting ropteffort higher doesn't have any effect- seems there isn't anything left to expend effort on. Also, trials are fast, so anyone can test themselves on e.g. 0.8 vs 1 vs 1.5 etc.

At high sizes, the time spent in root-opt is so small relative to the time spent on size-opt that I've been setting this quite high- like 30+. Again, at some point a higher setting doesn't produce any more effort, so I don't think it matters whether one sets this to 35 or 60.

It's the 115ish to 150ish area where I don't have a good answer; I played with it years ago, and ran into trials where higher settings cost more time but didn't produce any changes in polys. An open question?

[QUOTE=VBCurtis;545793]At really low sizes, say under 115 digits, setting ropteffort higher doesn't have any effect- seems there isn't anything left to expend effort on. Also, trials are fast, so anyone can test themselves on e.g. 0.8 vs 1 vs 1.5 etc.

At high sizes, the time spent in root-opt is so small relative to the time spent on size-opt that I've been setting this quite high- like 30+. Again, at some point a higher setting doesn't produce any more effort, so I don't think it matters whether one sets this to 35 or 60.

It's the 115ish to 150ish area where I don't have a good answer; I played with it years ago, and ran into trials where higher settings cost more time but didn't produce any changes in polys. An open question?[/QUOTE]

Thank you for summarizing the issue so well. I’m varying ropteffort and nrkeep with the c204 poly search just to get a feel for the resulting poly score and runtime.

I have been trying to study the randomness of "good" polynomials across a search region. I've even graphed exp_E values for a given region/parmeters. I'm sure someone's already explored this. Is there any documentation that I might be capable of understanding available on this?

Is there a way to backtrack a polynomial to any of its search criteria?


Edit: Extra question: How large is too large for admax?

The limit on admax is 1/(poly_degree+1) the size of the number to be factored. That's the extreme upper limit; Kleinjung's 2006 paper gives more sensible bounds on admax based on the largest and smallest skew that you can tolerate. The optimal skew goes down as a_d increases, taking the search space for the root optimization with it.

[QUOTE=EdH;546102]I have been trying to study the randomness of "good" polynomials across a search region. I've even graphed exp_E values for a given region/parmeters. I'm sure someone's already explored this. Is there any documentation that I might be capable of understanding available on this?
. . .[/QUOTE]I reran the range from 130M-132M at P=16M because P=2M found a cownoise MurphyE score of 2.203 for 130M-133M. The rerun only covered 130M-132M and only 130M to the below number was graphed. The cownoise MurphyE for the rerun was only 2.109. However, I don't know if the original best may have been within the last third of the original run. I may yet run that range to determine if anything better shows itself.

Here are some graphs of exp_E for a CADO-NFS run with the following parameters:
[code]
admin-admax: 130000000-131756940
incr: 210
P: 16000000
adrange: 1680
sopteffort: 1
[/code]Parameters not listed above were set to the default values in the CADO-NFS params.c200 file.

All of the below points represent the smallest raw exp_E score for a given search value. The first graph is of the entire set. The second is of the lowest value. The third is of the fifth lowest value, since CADO-NFS said the 4-th poly (starting at 0) after size optimization was chosen.

Edit: Rerunning the final third of the range (132M-133M) at P=16M netted only a MurphyE of 2.078 per cownoise. The new range is not reflected in the graphs.

Here is some data I have gathered, really started as a personal education on the effects of certain parameters on CADO performance. Nothing new here, but it does provide some actual results with respect to speed and the polys produced.

[code]
P (M) admin (M) admax (M) adrange (M) incr nq nrkeep ropteffort Size-opt time (wall clock minutes) Root-opt time (wall clock minutes) Total Time (wall clock minutes) Best poly score (cownoise) Best poly in n-th place after size opt
4 60 61 60060 30030 15625 50 35 110 175 285 1.44E-15 4
4 60 61 60060 30030 15625 200 35 110 675 785 1.45E-15 4
4 60 61 60060 30030 15625 50 10 110 90 200 1.44E-15 4
4 60 61 60060 30030 15625 200 10 110 330 440 1.44E-15 4
8 60 61 60060 30030 15625 50 35 215 180 395 1.88E-15 0
8 60 61 60060 30030 15625 200 35 215 620 835 1.88E-15 0
8 60 61 60060 30030 15625 50 10 220 100 320 1.88E-15 0
8 60 61 60060 30030 15625 200 10 220 335 555 1.88E-15 0
14 60 61 60060 30030 15625 50 35 370 175 545 1.72E-15 0
14 60 61 60060 30030 15625 200 35 365 670 1.72E-15 0
14 60 61 60060 30030 15625 50 10 485 85 570 1.66E-15 0
14 60 61 60060 30030 15625 200 10 365 330 695 1.66E-15 0
[/code]

All data was measured with -t 4 on a fully tasked i7-7705 with 32 Gb installed.

sopteffort was default (zero) in all cases. I chose these parameters for speed of testing, not optimizing a poly search. adrange and incr are too large for a 60-61M search. But the timings should be good.

Got another run grinding away on the same machine with incr = 9240 and nq = 4620. Much slower but the parameters are more realistic.