20200424, 13:11  #67 
"Ed Hall"
Dec 2009
Adirondack Mtns
2^{2}×7×11^{2} Posts 
I found and ran the poly for the 168 digit cofactor for 6+5,370 and got the following from cownoise:
Code:
4266086.58004 5.23508635e13 
20200424, 14:33  #68 
"Curtis"
Feb 2005
Riverside, CA
2×47^{2} Posts 
The records are kept in this thread, in the msieve forum:
https://mersenneforum.org/showthread...610#post539610 5.32 is the record for C168, so you were 2% shy. 
20200424, 14:37  #69  
"Curtis"
Feb 2005
Riverside, CA
1000101000010_{2} Posts 
Quote:
We are noting dup ratios by way of noting the number of unique relations, which is the only count that matters for filtering. I appreciate Charybdis noting his poly scores that may indeed explain the speed difference! However, if it's a tie the lower LP should be used to save storage space and potentially produce smaller matrices. Perhaps C180 params should be tested with 32/32, though. Sigh, so many options! 

20200424, 14:58  #70  
"Ed Hall"
Dec 2009
Adirondack Mtns
2^{2}·7·11^{2} Posts 
Quote:
Unfortunately, my compiled logs don't seem to have the actual polynomials, but they do list the Murphy_E scores as computed by CADONFS for the chosen poly's. What I don't understand is that my score for 5+2,415 is totally different from charybdis': Code:
5+2_415 177 (5721...) 1.440e13 Code:
Info:Polynomial Selection (root optimized): Finished, best polynomial has Murphy_E = 1.239e07 

20200424, 15:03  #71  
"Ed Hall"
Dec 2009
Adirondack Mtns
2^{2}×7×11^{2} Posts 
Quote:
2% shy  and I thought is was a poor poly. Didn't I have huge duplication for that one? Maybe it was the one before  darn memory  it's only great for some things. 

20200424, 16:02  #72 
"Curtis"
Feb 2005
Riverside, CA
2×47^{2} Posts 
The poly score evaluation has no way to know how many relations will be dups; so you had a strong score on that one, but it was unlucky in that it found lots of duplicate relations so it didn't perform as well as the score would indicate.
CADO uses a different scorecalculation method, one that they believe better forecasts poly performance, than the traditional Murphy Escore. cownoise finds the traditional score, which uses a fixed test area to determine score. CADO uses the actual lim's and sieve area (I or A value) and largeprimes to estimate performance, so the CADO score depends on your parameter choice while the traditional Murphy Escore does not. We use the traditional scores to compare for obvious reasons, but within a single factorization with preset params I think CADO is more accurately evaluating which poly will sieve best among those found during poly select. 
20200424, 23:51  #73  
"Curtis"
Feb 2005
Riverside, CA
1000101000010_{2} Posts 
Quote:
Run 6: mfb1 90, A=28. 220800 rels/hr, ETA 47 days 5 hr. Yield 3.45. So, yield is back to the original parameters on I=15, by using 3LP instead; ETA went from 14 July to 10 June, 12 weeks down to 7! (Not really, since the target relations is both too low and the same for all settings) Testing mfb1=92 next, then I'll mess with ncurves. Also, CADO default params switch which lim is bigger at this size, perhaps because 3LP works well with smaller lim, so I'll try that also. That requires a new run from scratch, since factor bases will change. 

20200424, 23:55  #74 
Jun 2012
101100111010_{2} Posts 
C182
By happy chance, a 182 dd composite just fell out of ECM of the kosta project after Yoyo@Home found a p67. Specifically C182_M19_k94:
Code:
26521232090195873108384905824300492852413283081683568418163219479089273132380406501680155963531361683795706304607082425988301635509432877463621844114521741860720947862338201013214619 Code:
# 524287 ^ 47 + 1 # MurphyE Score: 1.291e14 anorm: 1.169e49 rnorm: 9.577e52. (Since rnorm is larger, sieve with the "r" parameter.) # SNFS difficulty is 274.539 which is approximately equivalent to GNFS difficulty 183. (Since n has 182 digits, it's recommended to use either SNFS or GNFS.) # (some extra msieve library info) size: 4.922e14 alpha: 1.228 rroots: 0 n: 26521232090195873108384905824300492852413283081683568418163219479089273132380406501680155963531361683795706304607082425988301635509432877463621844114521741860720947862338201013214619 skew: 12.16597 type: snfs c6: 1 c5: 0 c4: 0 c3: 0 c2: 0 c1: 0 c0: 524287 Y1: 1 Y0: 5708903659119442793759136591282812149479505921 rlambda: 2.6 alambda: 2.6 lpbr: 31 lpba: 31 mfbr: 62 mfba: 62 alim: 134000000 rlim: 134000000 
20200425, 00:25  #75 
Apr 2020
6D_{16} Posts 
As promised, here's some data from my third c177 run, with I=15 and 31/32LP:
Code:
Fri Apr 24 23:34:21 2020 commencing relation filtering Fri Apr 24 23:34:21 2020 setting target matrix density to 110.0 Fri Apr 24 23:34:21 2020 estimated available RAM is 15845.4 MB Fri Apr 24 23:34:21 2020 commencing duplicate removal, pass 1 Sat Apr 25 00:03:27 2020 found 98515288 hash collisions in 295205985 relations Sat Apr 25 00:03:49 2020 commencing duplicate removal, pass 2 Sat Apr 25 00:09:33 2020 found 139833153 duplicates and 155372832 unique relations ... Sat Apr 25 01:08:08 2020 matrix is 11425351 x 11425576 (4878.0 MB) with weight 1295565782 (113.39/col) Sat Apr 25 01:08:08 2020 sparse part has weight 1164492361 (101.92/col) Sat Apr 25 01:08:08 2020 using block size 8192 and superblock size 884736 for processor cache size 9216 kB Sat Apr 25 01:08:39 2020 commencing Lanczos iteration (6 threads) Sat Apr 25 01:08:39 2020 memory use: 4605.1 MB Sat Apr 25 01:09:04 2020 linear algebra at 0.0%, ETA 50h16m Edit: Curtis, if I do a c178 next is there any parametertestingoverawholejob that you'd like me to do? Last fiddled with by charybdis on 20200425 at 00:30 
20200425, 04:34  #76  
"Curtis"
Feb 2005
Riverside, CA
2×47^{2} Posts 
Quote:
The record poly score for a C182 is 5 times bigger than this listed SNFS poly score; I imagine GNFS will be faster even accounting for the "deg 6 / SNFS scores don't translate perfectly to deg 5" issue. 

20200425, 04:40  #77  
"Curtis"
Feb 2005
Riverside, CA
2·47^{2} Posts 
Quote:
Let's try the 3LP settings for your C178: MFB1 = 90, ncurves1=13, A=28, rels_wanted=320M. EDIT: Ditch the lambda1 line entirely. I haven't yet tested new lim's; I'm using 100/140M for lim0 and lim1. I'm running mfb1=92 right now, with a limswap to 140/100 coming next. If you can wait a couple hours, I'll have a good idea if that should be faster. If I grasp 3LP correctly, sieving will be faster but the matrix will be bigger. Then again, 320M is a wild guess, and we can trade some sieve time for a smaller matrix. Last fiddled with by VBCurtis on 20200425 at 04:42 

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