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 2022-04-28, 21:17 #56 VBCurtis     "Curtis" Feb 2005 Riverside, CA 122378 Posts Not really; you'll have a slightly higher duplicate rate, meaning you may need an extra 1-3M raw relations to get the matrix size you expect. Sieve time will barely change.
 2022-04-29, 17:37 #57 EdH     "Ed Hall" Dec 2009 Adirondack Mtns 450710 Posts Here's the c165: Code: N = 309... <165 digits> tasks.I = 14 tasks.lim0 = 60000000 tasks.lim1 = 40000000 tasks.lpb0 = 31 tasks.lpb1 = 31 tasks.qmin = 7000000 tasks.sieve.adjust_strategy = 2 tasks.sieve.lambda0 = 1.83 tasks.sieve.mfb0 = 58 tasks.sieve.mfb1 = 89 tasks.sieve.ncurves0 = 18 tasks.sieve.ncurves1 = 10 tasks.sieve.qrange = 5000 Polynomial Selection (size optimized): Total time: 523377 Polynomial Selection (root optimized): Total time: 35527 Lattice Sieving: Total time: 4.96142e+06s (all clients used 4 threads) Lattice Sieving: Total number of relations: 175009615 Found 122644730 unique, 53361072 duplicate, and 0 bad relations. cownoise Best MurphyE for polynomial is 7.58493957e-13 Although I have another c165 available, I'm going to move back to working on the easier Aliquot sequences list for a little bit, since the number of sequences is diminishing and I want to try to make sure it doesn't get too low.
 2022-04-29, 20:50 #58 VBCurtis     "Curtis" Feb 2005 Riverside, CA 5,279 Posts If I've got the scaling of poly score vs sieve time, looks like 88 is quicker.
2022-04-29, 21:08   #59
EdH

"Ed Hall"
Dec 2009

4,507 Posts

Quote:
 Originally Posted by VBCurtis If I've got the scaling of poly score vs sieve time, looks like 88 is quicker.
Not at all empirical, but I had the feeling this was more difficult. I encountered a CADO-NFS filtering crash (possibly the strategy 2 trouble you mentioned?) and Msieve LA came back with over 32.5 hours ETA with 40 threads. I should probably save a copy of the Msieve log just for later perusal. (I wonder if I should see if a Colab instance would give me a good GPU and what it might show for ETA. . .)

ETA: I'm planning to try the Colab session, but the compression and upload times, as well as Colab inialization, are going to take quite a while, so I'm not sure there's an advantage.

ETA2: After nearly an hour and nowhere near completion, I gave up on my msieve.dat.mat.tbz upload to Google Drive for a Colab test. It had already taken over a half-hour to copy and compress it.

Last fiddled with by EdH on 2022-04-29 at 22:25 Reason: why do I keep writing startegey?. . .

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