20220914, 00:13  #12 
"Serge"
Mar 2008
Phi(4,2^7658614+1)/2
2×3×1,657 Posts 
Just in order to not fork another thread, some targets that could be a fallback from 2,1109+ (if it turns SNFSki) are, perhaps, 
Code:
214 7 419  354 0.604 219 11 334 + 347.8 0.629 219 5 523 + 365.5 0.599 222 3 718 + 342.5 0.648 224 3 823  392.6 0.57 (224 5 479 + 334.8 0.669) (225 2 1109 + 333.8 0.674) 
20220915, 09:14  #13 
"Vincent"
Apr 2010
Over the rainbow
2×1,429 Posts 
a slightly better (for me at least) poly
Code:
skew: 755192.453 c0: 44089320441977706345863258655893321664536110560 c1: 268491014998631707851828924312857969747572 c2: 168895151056819271392513808334804436 c3: 1095536629595790473291869141585 c4: 933378718901445252914593 c5: 850800448461467910 c6: 210163753800 Y0: 710135625395382122411596439629784935 Y1: 2600874528869472580495674989 # MurphyE (Bf=6.872e+10,Bg=3.436e+10,area=1.766e+18) = 1.850e09 
20220920, 09:08  #14 
"Vincent"
Apr 2010
Over the rainbow
2·1,429 Posts 
finally a decent one
Code:
skew: 724988.351 c0: 5864149138561428958664120082846303367267868400 c1: 64887105680355982672042016633688198554460 c2: 204393359764698159887054341192074888 c3: 184048900225366414544979923507 c4: 428493172390342410123193 c5: 161001307814852802 c6: 26851865040 Y0: 823051945817186779901623462260379129 Y1: 21719286194539104138651493 # MurphyE (Bf=6.872e+10,Bg=3.436e+10,area=1.766e+18) = 2.188e09 
20220920, 16:50  #15 
"Ed Hall"
Dec 2009
Adirondack Mtns
1001100110100_{2} Posts 

20220924, 12:53  #16 
Apr 2010
11101100_{2} Posts 
My current best:
Code:
# norm 3.812685e16 alpha 11.270627 e 2.186e16 rroots 4 skew: 27486666.79 c0: 21949786704915546043243424808434624720995532180576 c1: 41058006152954229159929753709281199565102884 c2: 2103952747130896180152288821190124349 c3: 96714753899249454119686484058 c4: 8749213175835406783325 c5: 356178171100692 c6: 604800 Y0: 3069461441978573391108054100447770150 Y1: 4741101382398693934919 # MurphyF (Bf=6.872e+10,Bg=3.436e+10,area=1.766e+18) = 2.394e09 
20221001, 15:35  #17  
"Bob Silverman"
Nov 2003
North of Boston
16472_{8} Posts 
Quote:
Typically one spends about 5% of the total effort on poly selection. Based on prior discussion it seems that nothing close to that amount of effort has been spent. 

20221001, 17:49  #18  
"Curtis"
Feb 2005
Riverside, CA
2^{4}×7^{3} Posts 
Quote:
More generally, how does one convert GPU time to a sense of effort when a GPU is 100+ times faster than a CPU for poly select? I think we (mostly Greg) have spent more than 1% of total effort on poly select, and we're not close to the SNFS score. While it's possible to catch the SNFS score, why spend the effort when beating the score is so doubtful? If the answer is "because GNFS225 is cool and new, while the SNFS job isn't", I am on board with that. 

20221001, 20:07  #19  
"Bob Silverman"
Nov 2003
North of Boston
2·3·29·43 Posts 
Quote:
I don't know the answer either. Quote:
Quote:
1st/2nd holes. It might be intersting as an SNFS job if only to see what the limits are for NFS@Home. And once more to show my ignorance: I don't know whether GNFS can beat SNFS for 2,1109+. My prior guess that it could has been shown to be doubtful. 

20221002, 02:30  #20 
"Curtis"
Feb 2005
Riverside, CA
2^{4}×7^{3} Posts 
I agree that a clear and accurate measure of "enough poly select effort" is difficult. So, rather than aim for a specific amount of effort, forum members who do team poly select efforts shoot for a particular Escore. We base our target scores on our list of record poly scores for each digit size, and the list of records provides us a rather accurate guess for an achievable score (that is. one on trend for other records of nearby or similar sizes).
Charybdis did such an interpolation in post #1, predicting 2e16 as an easy mark. Beating that by 10% is a reasonable goal, but the SNFS poly sieves about 20% better than our candidate "2e16" scoring GNFS. So, we need a 2.4 or 2.5 just to match, and I think that's as good as we can hope for. You can find the list of best poly Escores organized by degree and input size here: https://mersenneforum.org/showpost.p...&postcount=200 
20221002, 08:59  #21  
"Bob Silverman"
Nov 2003
North of Boston
2·3·29·43 Posts 
Quote:
(which could be very wrong) says that they are more likely to be shaped like a Gamma/ChiSquare distribution (i.e. with a long tail to the right). Has anyone ever looked at this? However they are distributed, you should probably aim for at least 2sigma above the mean. Mean should be a function of size. Do you have any idea how far above the mean your history of 'record' scores lie? Does anyone have histograms of past data, rather than just the record values? Did anyone keep the mean values in addition to the 'records'? It would be an interesting study. It might even be publishable. Note: When I say "distributed', I mean the distribution of values for each candidate and not the distribution of the 'record' values as a function of size. Last fiddled with by R.D. Silverman on 20221002 at 09:06 

20221002, 10:08  #22 
Jun 2012
3689_{10} Posts 
Kamada’s site has 20+ years of data, some displayed graphically but no escore histogram. He may have such data in his archives.
There is data in the NFS@Home log files for the various GNFS factorizations over the years but that would require a bit of data mining. I believe @VBCurtis did some digging into this a few years ago but the thread eludes me. Greg Childers may have such data as a matter of course (though I doubt it). But some data was likely never captured, e.g. hardware and SW used, processing time, discarded poly search results that “weren’t good enough”, and intangibles like user motivation  how much time does one really need to spend on a GNFS 155 search before going with a “good enough” result versus say a GNFS 210 where a few percent in escore represents LOT of sieving. Polynomial searches have evolved over the last decade  increased use of GPUs, better algorithms and search methodologies give better results in less time. Most of the records in the table are recent  virtually all of the old search results have been topped in the last 3years. But I love the idea of a study and I hope someone here takes the idea and runs with it. 
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