I think a forum-organized NFS project is overdue, so I'm willing to help both with poly select and some sieving.

[QUOTE=VBCurtis;386650]I think a forum-organized NFS project is overdue, so I'm willing to help both with poly select and some sieving.[/QUOTE]
[URL]http://mersenneforum.org/showthread.php?t=19711[/URL] is already one forum-organized NFS project in progress.

[QUOTE=swellman;386646]
I normally use Yafu, but I believe the .dat files are perfectly compatible with pure Msieve results.
[/QUOTE]

Neither Yafu nor Msieve are capable of sieving.*

They each delegate to external sievers, in the typical forum case the gnfs-lasieve collection. Since it's the same siever, the results format is of course the same.

As a bonus, Yafu isn't even capable of post-processing -- it just uses Msieve's code (which is why Msieve is a compile time dependency for NFS).**

[QUOTE=Batalov;386659][URL]http://mersenneforum.org/showthread.php?t=19711[/URL] is already one forum-organized NFS project in progress.[/QUOTE]

Not that it's getting anywhere :razz:



[SIZE="1"]
* Msieve technically has a line siever, but its use in place of an optimized lattice siever like gnfs-lasieve is morbidly inefficient and a waste of resources.

** Yafu's SIQS code has a copy-and-pasted older form of Msieve's post-processing as part of its own source, which is why Msieve isn't a dependency for without-NFS builds.[/SIZE]

Batalov-
Except that nobody has decided upon parameters for M991, nor begun sieving. I tried- I posted a baseline parameter set for feedback, but nobody with experience on that size posted improvements. I don't think any consensus was reached for M991 on whether 33-bit LPs were enough, and thus whether the Win64 siever is sufficient for M991.

Is there a 64-bit siever binary available with the 33-bit limit removed? I know NFS@Home uses one in a Boinc wrapper, but I have not found the freestanding binary.

Yes, I know. I am only trying to say that two concurrent projects will have a worse fate than one.

[QUOTE=VBCurtis;386661]

Is there a 64-bit siever binary available with the 33-bit limit removed? I know NFS@Home uses one in a Boinc wrapper, but I have not found the freestanding binary.[/QUOTE]

Do you want to try the file in the attachment? It is the 64-bit binary from NFS@Home. Please let me know if it works.

Carlos-
Thanks for trying. This binary produces a file "stderr" that has a series of error outputs, such as "can't open init data file - running in standalone mode"
Followed by "boinc initialized work files resolved, now working"
followed by "Cannot open input_data for input of nfs polynomials: no such file or directory"

I called the binary by renaming it to my usual 16e siever and running the python script for 2,991-. The script did work, producing the usual .fb file and job files, etc.

So, it appears this binary is the one modified to work with NFS@ home's BOINC wrapper.

I'm going to send an email to Greg to see if he can share the original one.

Edit: Just checked my email and I have the linux binaries.
[url]https://cld.pt/dl/download/bc833ab0-e354-464e-83d0-a1305e5402dc/lasieve5.tar.gz[/url]

Final Counts
 

7186 @ 26e7 - no factor
222 @ 85e7 - no factor

I see yoyo is passing through 21K @ 26e7.

I'll put this on hold until the M991 project completes.

A C186 GNFS task is far above the reach of 14e, so Greg is the one to convince for queuing to NFS@Home :smile:

C186 @ i5232
 

I did a little preliminary work on poly selection and found the following:

I ran three intervals of leading coefficients. None of which produced the expected results. (i.e., not worth posting the poly.)

Baseline: expecting poly E from 3.55e-14 to > 4.09e-14

Leading coefficient & scores.
[CODE]1.2-1.3e6
skew 103308316.47, size 2.479e-18, alpha -7.147, combined = 2.977e-14 rroots = 5

2.7-2.8e6
skew 106652921.92, size 2.353e-18, alpha -8.691, combined = 2.825e-14 rroots = 3

3.6-3.8e6
skew 21384286.59, size 2.157e-18, alpha -7.678, combined = 2.677e-14 rroots = 3[/CODE]

It seems to get worse as the lead coefficient increases. I wonder if it would be better to search below 1M?