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Old 2020-09-01, 23:43   #119
Apr 2020

2×5×23 Posts

The c183 stats below aren't directly comparable to those for the c182 above, for a couple of reasons.
Firstly, I ran the c183 on a slightly different set of machines, giving about a 1% speedup in CPU-time.
Secondly, one machine had some strange connection problems. I won't bother with the details, but the lowdown is that the server cancelled all the WUs from this client without receiving any relations. This meant that the final Q was a bit larger than it should have been, but the factorization will only have been slowed down by a fraction of a percent.

Poly score 6.356e-14 (4.5% worse than c182 above).
Sieved Q from 20M to 195.9M, with about 1.7M missing due to the bad client.
100.5M CPU-seconds for 321M raw relations, 218M unique.
TD=110 produced an 18.3M matrix. This is a bit bigger than the c182 matrix, but the all the figures looked very similar to the c182 run in the early stages of filtering, so I'm going to chalk the difference in matrix size up to the peculiarities of the polynomial.

Putting all the figures together, lambda0 = 2.07 (= mfb0/lpb0 + 0.2) might be 1% faster than the default (mfb0/lpb0 + 0.3). It looks like changing lambda from the default is unlikely to produce big gains at this size.

Next up will be the bunch of c184s. Would I be right in thinking lpb 32/32 deserves some testing here?
charybdis is offline   Reply With Quote