20221024, 11:12  #144 
"Oliver"
Sep 2017
Porta Westfalica, DE
1327_{10} Posts 
QUEUED AS W861
861*2^{861}1 is a Woodall number that is ready to be sieved as SNFS on 15e: Code:
n: 188386046098466199536175452570229431563689849939659262401226219971317243525754666917537583167996559619029043912342710003045776630563860201451094450711950131189856666365670472827943792458379509903998351786742808639630866998718013603 # 861*2^8611, difficulty: 262.12, anorm: 1.05e+36, rnorm: 1.35e+50 # scaled difficulty: 264.94, suggest sieving rational side # size = 2.269e13, alpha = 2.805, combined = 4.016e14, rroots = 2 type: snfs size: 262 skew: 0.29586 c6: 6888 c0: 1 Y1: 1 Y0: 11150372599265311570767859136324180752990208 rlim: 134000000 alim: 266000000 lpbr: 32 lpba: 32 mfbr: 94 mfba: 64 lss: 1 rlambda: 3.9 alambda: 2.7 Code:
Q norm. yield 35M 2465 40M 2257 70M 2194 125M 2069 200M 1680 300M 1597 I would like to do the LA. Last fiddled with by swellman on 20221024 at 11:56 
20221024, 12:18  #145 
Jun 2012
3×1,283 Posts 
QUEUED AS 5m4_865M
54,865M from the HCN project is a SNFS 241 (quartic) job to be run on 15e. It is ready for sieving. Code:
n: 202555903472921376017494458914423311746291773012577711177576348293001774379027222845952446030626352906737399177339738094628434247569226642258535081891097353893608325736988247777126991974546074562669981652275786573190793761 skew: 0.4472 type: snfs size: 241 c4: 25 c3: 25 c2: 15 c1: 5 c0: 1 Y1: 11972621413014756705924586149611790497021399392059392 Y0: 1292469707114105741986576081359316958696581423282623291015625 rlim: 134000000 alim: 266000000 lpbr: 33 lpba: 32 mfbr: 96 mfba: 64 rlambda: 3.7 alambda: 2.4 Code:
MQ Norm_yield 35 1837 50 2261 75 2453 100 2560 150 2447 200 2320 250 2274 300 2187 350 2122 Last fiddled with by swellman on 20221024 at 14:57 
20221103, 13:11  #146 
Jun 2012
3·1,283 Posts 
QUEUED AS 8m7_341
87,341 is a SNFS 280 job from the HCN project now ready for sieving on 15e. Code:
n: 1257831877902465284401904732297195473572308017725568799120893001756116420424745947122036616596445694485123521851527252735379003753111652033442861028407880668528720791431272129213829740292842857152587040353849000045033642110230877933436752399007747939 # 8^3417^341, difficulty: 279.96, skewness: 1.00, alpha: 2.22 # cost: 7.57243e+19, est. time: 36059.20 GHz days (not accurate yet!) skew: 1.000 c5: 1 c4: 1 c3: 4 c2: 3 c1: 3 c0: 1 Y1: 1562531701075863192779448904272185314811647640213651456 Y0: 98104607686593128479834996959304746360186153111467503313 rlim: 134000000 alim: 266000000 lpbr: 33 lpba: 33 mfbr: 96 mfba: 66 rlambda: 3.65 alambda: 2.45 Code:
MQ Norm_yield 35 1881 50 1940 75 2127 100 2101 150 2085 200 1789 250 1829 300 1666 350 1588 400 1489 450 1553 500 1377 550 1355 600 1276 I will park this job here until more jobs from other projects get posted. Last fiddled with by swellman on 20221107 at 13:31 
20221107, 10:53  #147 
"Oliver"
Sep 2017
Porta Westfalica, DE
1,327 Posts 
QUEUED AS 145!1
This C185 is a cofactor of the factorial minus 1 number 145!1 that is ready to be sieved as GNFS on 15e: Code:
n: 61961544527388294841688073882914854435388027897679210391156264443557149767638767403360578514778014603475277763521601393153149828278695416036164441248566103608937469068435239190125514623 type: gnfs skew: 23388742 c5: 28963296 c4: 468307738325310 c3: 49748528932542980322741 c2: 314034469329584823868962434378 c1: 10234603583895446847339037580343693197 c0: 4983288639261044534250632896338765636096980 Y1: 4473326874907429 Y0: 335939328349166369840151777825025122 rlim: 266000000 alim: 134000000 lpbr: 32 lpba: 32 mfbr: 64 mfba: 94 lss: 0 rlambda: 2.7 alambda: 3.9 Code:
Q norm. yield 35M 3344 40M 3227 70M 2997 125M 2634 200M 2283 300M 1970 400M 1675 I would like to do the LA. Last fiddled with by swellman on 20221107 at 12:30 
20221111, 01:29  #148 
Sep 2008
Kansas
7340_{8} Posts 
C278 from the MWRB file with OPN 11673.
I compromised on the alambda. Increasing it any more generated a few more rels at the cost of time per rels, so I stopped at 2.6. rlambda at 3.6 was much better than 3.5. I remember several years ago one could change the skew a bit to get better yield. I didn’t modify the skew value. The formulaic generation of parameters seems to be pretty good but test sieving is always beneficial, along with other's advice. Please hold for a day or two before queuing to allow feedback and/or modifications. Code:
n: 10929875925037315024994112350260780199767161975518955535270167413583164858504212664897476377692335059939499260248762932645204102682318951183447267479739483769724008717453251826937850228654862574004845245478825442381443215504635534927206893532265948445909765759873218837942895601 # 7043^731, difficulty: 280.89, skewness: 0.23, alpha: 0.00 # cost: 8.09051e+19, est. time: 38526.25 GHz days (not accurate yet!) skew: 0.228 c6: 7043 c0: 1 Y1: 1 Y0: 14896775084042115440192394458997575421235964401 type: snfs rlim: 134000000 alim: 268000000 lpbr: 33 lpba: 32 mfbr: 96 mfba: 64 rlambda: 3.6 alambda: 2.6 Code:
Q Yield NYld 35M 4173 4576 40M 4523 4251 70M 3876 4011 100M 3808 3759 200M 3008 2914 300M 2541 2528 400M 2075 2277 485M 1949 2119 
20221111, 13:30  #149  
Jun 2012
3849_{10} Posts 
Quote:
I believe the lambda should be mfb/log2(lim) + 0.05 which for the algebraic side is closer to 2.33 or 2.35 if you prefer. For 15e, rlim + alim is limited to 400M per Greg. alim must be changed to 266M. I’m not sure about your comment on skew. You’ve used the standard skew = c0/c6^(1/6). Cownoise recommends shifting skew to a value of 0.29722 but you should confirm this skew value with cownoise and whether if it improves things via test sieving. (I doubt it will help.) Max had a method of spinning things to lower skew with holding escore (nearly) constant but he’s not been around for awhile now. No one else has his recipe for this technique to my knowledge. Lastly, you could invert the roots of the polynomial to get a better skew value as suggested for this past job, with @charybdis’s recommendation. The job as posted should run just fine, but you may want to investigate some of the above ideas. Perhaps others will add deeper insights. 

20221111, 13:36  #150 
"Oliver"
Sep 2017
Porta Westfalica, DE
1,327 Posts 

20221111, 16:24  #151  
"Curtis"
Feb 2005
Riverside, CA
2^{3}·3·5·47 Posts 
Quote:
More generally, I think too much focus in testsieving is on improving yield, rather than improving speed. Often both improve at the same time, but with lambda it's worth losing a few relations to find the others faster. I'd test mfba of 63 also; you'll need 45% fewer relations to finish the job (like 625M instead of 650M) by shrinking mfba, so if you lose less than 4% in sec/rel it's a net win. 

20221112, 02:12  #152 
Sep 2008
Kansas
EE0_{16} Posts 
The following was performed on a Sandy Bridge chip at Q=40M using 2K block.
I need to investigate this further and the other ideas in the coming days. Code:
rlambda=2.6  rlambda=2.5  rlambda=2.4 yield sec/relyield sec/relyield sec/rel 4251 0.519  4376 0.521  4371 0.520 
20221112, 16:07  #153 
"Oliver"
Sep 2017
Porta Westfalica, DE
1,327 Posts 
...and IIUC, enlarging lambda's more than this 0.05 is theoretically useful when the Q range is largely below the corresponding lim? (This would need test sieving over the whole Q range.)
Regarding not optimising for rel/s, I plead guilty. 
20221113, 02:19  #154 
"Curtis"
Feb 2005
Riverside, CA
1608_{16} Posts 
Enlarging the lambda *on the sieve side* beyond this 0.05 "extra" is indeed useful, because GGNFS reduces the lim on the sieve side to {start of Q range 1}. So, if you have sieveside lim of 60M and sieve from 20M80M, Your lim is actually 19,999,999 for the first sieve range (and 29,999,999 when sieving a range starting at Q=30M, etc) and thus benefits from a larger lambda. This is part of the explanation for why folks who use fartoobig lambdas have testsieve results with really fast results at small Q (lambda nearly ideal and lower Q are faster anyway) but sec/rel falls off really fast as Q rises (larger Q suffering from lots of wasted cofactorsplitting work due to large lambda).
On the nonsieve side, none of this happens / is relevant, so lambda should be simply what theory indicates for lim/MFB choice, with a few hundredths / a tenth added to compensate for the estimation errors that occur in the step where lambda is used. Last fiddled with by VBCurtis on 20221113 at 02:20 
Thread Tools  
Similar Threads  
Thread  Thread Starter  Forum  Replies  Last Post 
Queue management for 14e queue  VBCurtis  NFS@Home  170  20230102 15:27 
2022  queue management for 15e_small  swellman  NFS@Home  186  20221229 17:58 
Queue management for 16e queue  VBCurtis  NFS@Home  154  20221223 21:35 
Queue management for e_small and 15e queues  VBCurtis  NFS@Home  254  20220102 01:59 
Improving the queue management.  debrouxl  NFS@Home  10  20180506 21:05 