CADO-NFS Data Harvesting

[EdH]

Originally Posted by VBCurtis

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 test-sieve that rather than run a full job.

OK. I have a c164 (685...) candidate and I should be able to start it running tomorrow. I'll run I=14 with adjust_strategy=2.

(For some reason, I had it in the back of my head that strategy=2 wouldn't work with I=14.)

[charybdis]

Originally Posted by VBCurtis

I expect A=28 would be slower than I=14 here, anyway; perhaps we can test-sieve that rather than run a full job.

Unfortunately I don't think that's something you can figure out by test-sieving, because A=28 should have a lower duplication rate. The crossover point for "time to find rels_wanted raw relations" is probably a few digits higher than the true crossover.

@EdH: I think you might need to take a look at your script, as all your summaries seem to include

Found 149733097 unique, 40170110 duplicate, and 0 bad relations.

[EdH]

Originally Posted by charybdis

. . .
@EdH: I think you might need to take a look at your script, as all your summaries seem to include

Found 149733097 unique, 40170110 duplicate, and 0 bad relations.

Indeed! I can't find where the report gets written in any of my scripts, but I do have a file with those values from sometime, that I harvest for each run. Thanks for catching that. I will definitely have to work on it. I might have to skip remdups4 and let Msieve report duplication and harvest the values from there.

[EdH]

OK, I'm losing it! The new candidate is the one I just factored. It got mixed into the list because it wasn't finished yet. I need to do some more work before I get to the next candidate.

[EdH]

I have a c164 underway:

N = 712...<164 digits>
tasks.I = 14
tasks.lim0 = 60000000
tasks.lim1 = 40000000
tasks.lpb0 = 31
tasks.lpb1 = 31
tasks.qmin = 10000000
tasks.sieve.adjust_strategy = 2
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

[EdH]

Here's the next c164 (I=14 and adjust_strategy=2):

N = 712... <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.adjust_strategy = 2
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: 524425
Polynomial Selection (root optimized): Total time: 30333.8
Lattice Sieving: Total time: 4.46548e+06s (all clients used 4 threads)
Lattice Sieving: Total number of relations: 175001545
Found 122488916 unique, 45564734 duplicate, and 0 bad relations.
cownoise Best MurphyE for polynomial is 8.11818879e-13

[VBCurtis]

Poly score 2.5% worse, but sieve time roughly 5% better. Nice!

The next settings to test are A=28 and mfb1 = 89. A=28 is more important a test (mfb should not change sieve time very much).

[EdH]

Originally Posted by VBCurtis

. . .
The next settings to test are A=28 and mfb1 = 89. A=28 is more important a test (mfb should not change sieve time very much).

Are you saying I should only change to A=28 first, or go ahead and change both, and with or without strategy=2?

[VBCurtis]

I think / hope each change should be independent- that is, you have determined strat 2 is faster (really, Charybdis determined this over a year ago), now it's the default. Next, try A = 28; once we know the best setting there, try mfb's.

One change at a time with A/B comparisons give us "clear" evidence for what to use; once the big settings like A and lp are set, the little settings (mfb, starting Q, lambda, target rels) can be dialed in hopes of finding a few more % of speed.

[EdH]

Originally Posted by VBCurtis

I think / hope each change should be independent- that is, you have determined strat 2 is faster (really, Charybdis determined this over a year ago), now it's the default. Next, try A = 28; once we know the best setting there, try mfb's.

One change at a time with A/B comparisons give us "clear" evidence for what to use; once the big settings like A and lp are set, the little settings (mfb, starting Q, lambda, target rels) can be dialed in hopes of finding a few more % of speed.

I just wanted to make sure I'm on the same page. The only thing I'll change for next time is A=28.

Again, I'm out of c164 candidates, I may have some lower c165s.

[charybdis]

Originally Posted by EdH

I just wanted to make sure I'm on the same page. The only thing I'll change for next time is A=28.

A=28 should probably have a slightly lower qmin - maybe 7M? - as you'll be sieving a smaller range of Q. We'll see what Curtis says.