20220422, 02:30  #23  
"Ed Hall"
Dec 2009
Adirondack Mtns
1001111110111_{2} Posts 
Quote:
Also, do you need the full 175M relations? If Msieve successfully filters earlier than 175M, do you still want the rest? BTW, I found a c164 candidate. I think it has a 6 leading digit. The current c164 should be done tomorrow, so I can start the 3LP job after that. 

20220422, 03:07  #24  
"Curtis"
Feb 2005
Riverside, CA
1010110110110_{2} Posts 
Quote:
Ed Nothing else needs to be changed. mfb at 88 is the key setting that causes 3LP (any setting larger than 3 * log_2(lim) will do it). I don't mind if you don't get to 175M; whatever your scripts do is just fine with me all the better to compare to a previous run with your script. May wish to swap lim's per Charybdis' suggestion, though. 

20220422, 10:51  #25 
Apr 2020
5^{3}×7 Posts 
Haven't done any big GNFS jobs myself for a while, but larger lims on the 2LP side definitely sieve better for the big SNFS jobs I've been doing instead. I think we used larger lims on the 2LP side for 3,748+ too.

20220422, 12:42  #26 
"Ed Hall"
Dec 2009
Adirondack Mtns
1001111110111_{2} Posts 
Here's the first c164 (note: A=28 and adjust_strategy=2):
Code:
N = 345... <164 digits> tasks.lim0 = 50000000 tasks.lim1 = 70000000 tasks.lpb0 = 31 tasks.lpb1 = 31 tasks.qmin = 10000000 tasks.filter.target_density = 170.0 tasks.filter.purge.keep = 160 tasks.sieve.lambda0 = 2.07 tasks.sieve.lambda1 = 2.17 tasks.sieve.mfb0 = 58 tasks.sieve.mfb1 = 61 tasks.sieve.ncurves0 = 18 tasks.sieve.ncurves1 = 25 tasks.sieve.qrange = 5000 Polynomial Selection (size optimized): Total time: 529277 Polynomial Selection (root optimized): Total time: 31468 Lattice Sieving: Total time: 4.6221e+06s (all clients used 4 threads) Lattice Sieving: Total number of relations: 171561952 Found 149733097 unique, 40170110 duplicate, and 0 bad relations. cownoise Best MurphyE for polynomial is 8.37946014e13 Last fiddled with by EdH on 20220422 at 12:49 
20220422, 12:48  #27 
"Ed Hall"
Dec 2009
Adirondack Mtns
11767_{8} Posts 
One last question:
Should I have a tasks.sieve.lambda1 value? I currently have 2.17 (as can be seen above). Should I just keep that? Last fiddled with by EdH on 20220422 at 13:14 
20220422, 14:01  #28 
"Curtis"
Feb 2005
Riverside, CA
2·7·397 Posts 
No lambda if you did use one, it would have to be close to 3 for 3LP. Best leave it default.

20220422, 14:22  #29  
"Ed Hall"
Dec 2009
Adirondack Mtns
19×269 Posts 
Quote:
Code:
N = 685. . .<164 digits> tasks.I = 14 tasks.lim0 = 60000000 tasks.lim1 = 40000000 tasks.lpb0 = 31 tasks.lpb1 = 31 tasks.qmin = 10000000 tasks.sieve.lambda0 = 1.83 tasks.sieve.mfb0 = 58 tasks.sieve.mfb1 = 88 tasks.sieve.ncurves0 = 18 tasks.sieve.ncurves1 = 10 tasks.sieve.qrange = 5000 tasks.sieve.rels_wanted = 175000000 

20220423, 12:24  #30 
"Ed Hall"
Dec 2009
Adirondack Mtns
19·269 Posts 
Here is the latest c164:
Code:
N = 685... <164 digits> tasks.I = 14 tasks.lim0 = 60000000 tasks.lim1 = 40000000 tasks.lpb0 = 31 tasks.lpb1 = 31 tasks.qmin = 10000000 tasks.filter.target_density = 170.0 tasks.filter.purge.keep = 160 tasks.sieve.lambda0 = 1.83 tasks.sieve.mfb0 = 58 tasks.sieve.mfb1 = 88 tasks.sieve.ncurves0 = 18 tasks.sieve.ncurves1 = 10 tasks.sieve.qrange = 5000 Polynomial Selection (size optimized): Total time: 526394 Polynomial Selection (root optimized): Total time: 31614.9 Lattice Sieving: Total time: 4.67967e+06s (all clients used 4 threads) Lattice Sieving: Total number of relations: 175012772 Found 149733097 unique, 40170110 duplicate, and 0 bad relations. cownoise Best MurphyE for polynomial is 8.31589954e13 If you like, provide some changes and I'll put them in the params file for the next ~c165 composite. It may not be real soon, but maybe this upcoming week. 
20220423, 14:20  #31 
"Curtis"
Feb 2005
Riverside, CA
2·7·397 Posts 
Try with strategy2, please? I don't use that setting because it seems to trigger errors with CADO postprocessing, so I forgot to include it for you.
My guess is 4% faster from strat2? Your next data point will tell us. :) Was the resulting matrix notably bigger than your previous C164? 
20220423, 14:54  #32  
"Ed Hall"
Dec 2009
Adirondack Mtns
19×269 Posts 
Quote:
Code:
Thu Apr 21 08:30:37 2022 matrix is 9822977 x 9823172 (3015.8 MB) with weight 932199937 (94.90/col) Thu Apr 21 08:30:37 2022 sparse part has weight 672685141 (68.48/col) Thu Apr 21 08:32:25 2022 filtering completed in 2 passes Thu Apr 21 08:32:27 2022 matrix is 9792967 x 9793156 (3013.3 MB) with weight 931103496 (95.08/col) Thu Apr 21 08:32:27 2022 sparse part has weight 672400393 (68.66/col) Thu Apr 21 08:33:10 2022 matrix starts at (0, 0) Thu Apr 21 08:33:11 2022 matrix is 9792967 x 9793156 (3013.3 MB) with weight 931103496 (95.08/col) Thu Apr 21 08:33:11 2022 sparse part has weight 672400393 (68.66/col) Thu Apr 21 08:33:11 2022 saving the first 48 matrix rows for later Thu Apr 21 08:33:12 2022 matrix includes 64 packed rows Thu Apr 21 08:33:13 2022 matrix is 9792919 x 9793156 (2895.1 MB) with weight 745879127 (76.16/col) Code:
Sat Apr 23 07:29:12 2022 matrix is 10949079 x 10949259 (3349.2 MB) with weight 1042919866 (95.25/col) Sat Apr 23 07:29:12 2022 sparse part has weight 746571916 (68.18/col) Sat Apr 23 07:32:13 2022 filtering completed in 2 passes Sat Apr 23 07:32:17 2022 matrix is 10934410 x 10934588 (3348.1 MB) with weight 1042422445 (95.33/col) Sat Apr 23 07:32:17 2022 sparse part has weight 746467122 (68.27/col) Sat Apr 23 07:33:16 2022 matrix starts at (0, 0) Sat Apr 23 07:33:19 2022 matrix is 10934410 x 10934588 (3348.1 MB) with weight 1042422445 (95.33/col) Sat Apr 23 07:33:19 2022 sparse part has weight 746467122 (68.27/col) Sat Apr 23 07:33:19 2022 saving the first 48 matrix rows for later Sat Apr 23 07:33:21 2022 matrix includes 64 packed rows Sat Apr 23 07:33:23 2022 matrix is 10934362 x 10934588 (3228.6 MB) with weight 832280012 (76.11/col) * I'm guessing that's the only change you would like for the next ~c164 run (I don't have another c164 handy just yet), or do you want something else modified, too? 

20220423, 23:49  #33 
"Curtis"
Feb 2005
Riverside, CA
2×7×397 Posts 
Please try A=28 separately from strat 2. I'd like to know the speed gained from start 2 on I=14.
I expect A=28 would be slower than I=14 here, anyway; perhaps we can testsieve that rather than run a full job. 
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