[CODE]
.
LL test successfully completes double-check of M26177689
LL test successfully completes double-check of M26128457[/CODE]So, version 1.64 is VERY close to what means a good and stable version :D

Reporting results
 

Sorry for this dumb question.
I´m running Cudalucas for the first time: everything fine, smooth and all, but... what will be the correct way to report the result? I mean, does Cudalucas write the result to some text file that can then be uploaded through the server Manual Pages, or...
In any case I think the result will have to be manually uploaded, and no security code is in place to avoid faking results, isn´t it?

[QUOTE=lycorn;292187] does Cudalucas write the result to some text file that can then be uploaded through the server Manual Pages, or...
In any case I think the result will have to be manually uploaded, and no security code is in place to avoid faking results, isn´t it?[/QUOTE]
Older versions used to create/update a file called mersarch.txt. With the newer versions you should look for a plain text result.txt. Every time an expo is finished, the last residue is appended to the file. You can edit the file (I always do, to add some info like date found etc). The new lines added by CudaLucas you have to copy and paste into mersenne.org report form. Be careful to be logged in, otherwise your results will end reported as anonymous and you won't be credited.

Thanks a bunch.

CUDALucas1.58.cuda4.0.sm_20.WIN64.29198173.log
[code]
Iteration 8160000 M( 29198173 )C, 0xd3d8e5229c0ef595, n = 1572864, CUDALucas v1.58 (1:06 real, 6.6116 ms/iter, ETA 38:37:22)
Iteration 8170000 M( 29198173 )C, 0x191e1edf48d3246acontinuing work from a partial result
Iteration 8220000 M( 29198173 )C, 0x8b29efc1039a9f62, n = 1572864, CUDALucas v1.58 (1:50 real, 11.0380 ms/iter, ETA 64:17:47)
[/code]
CUDALucas1.63.cuda4.1.sm_20.WIN64.29198173.log
[code]
Iteration 8160000 M( 29198173 )C, 0xd3d8e5229c0ef595, n = 1572864, CUDALucas v1.63 (0:53 real, 5.2994 ms/iter, ETA 30:57:26)
Iteration 8170000 M( 29198173 )C, 0x191e1edf48d3246a, n = 1572864, CUDALucas v1.63 (0:53 real, 5.2998 ms/iter, ETA 30:56:41)
Iteration 8180000 M( 29198173 )C, 0x38a7e6a8dbc3b325, n = 1572864, CUDALucas v1.63 (0:53 real, 5.2994 ms/iter, ETA 30:55:41)
Iteration 8190000 M( 29198173 )C, 0x850cdcbc97f98d2a, n = 1572864, CUDALucas v1.63 (0:53 real, 5.2993 ms/iter, ETA 30:54:45)
Iteration 8200000 M( 29198173 )C, 0xe6cd792c103f8994, n = 1572864, CUDALucas v1.63 (0:53 real, 5.2995 ms/iter, ETA 30:53:56)
Iteration 8210000 M( 29198173 )C, 0xdd1b0a482e81a352, n = 1572864, CUDALucas v1.63 (0:53 real, 5.2992 ms/iter, ETA 30:52:57)
Iteration 8220000 M( 29198173 )C, 0x9652c73462421f58, n = 1572864, CUDALucas v1.63 (0:53 real, 5.2994 ms/iter, ETA 30:52:08)
[/code]
My Ver1.58
[code]
Iteration 8160000 M( 29198173 )C, 0xd3d8e5229c0ef595, n = 1572864, CUDALucas v1.58 (1:28 real, 8.7039 ms/iter, ETA 50:50:43)
Iteration 8170000 M( 29198173 )C, 0x191e1edf48d3246a, n = 1572864, CUDALucas v1.58 (1:27 real, 8.7058 ms/iter, ETA 50:49:55)
Iteration 8180000 M( 29198173 )C, 0x38a7e6a8dbc3b325, n = 1572864, CUDALucas v1.58 (1:27 real, 8.7038 ms/iter, ETA 50:47:47)
Iteration 8190000 M( 29198173 )C, 0x850cdcbc97f98d2a, n = 1572864, CUDALucas v1.58 (1:27 real, 8.7049 ms/iter, ETA 50:46:43)
Iteration 8200000 M( 29198173 )C, 0xe6cd792c103f8994, n = 1572864, CUDALucas v1.58 (1:27 real, 8.7074 ms/iter, ETA 50:46:08)
Iteration 8210000 M( 29198173 )C, 0xdd1b0a482e81a352, n = 1572864, CUDALucas v1.58 (1:27 real, 8.7073 ms/iter, ETA 50:44:40)
Iteration 8220000 M( 29198173 )C, 0x9652c73462421f58, n = 1572864, CUDALucas v1.58 (1:27 real, 8.7054 ms/iter, ETA 50:42:31)
[/code]
roundoff error check per 100 iterations.
can not find all round off error.

[QUOTE=msft;292278]CUDALucas1.58.cuda4.0.sm_20.WIN64.29198173.log
CUDALucas1.63.cuda4.1.sm_20.WIN64.29198173.log
My Ver1.58

roundoff error check per 100 iterations.
can not find all round off error.[/QUOTE]

Did you get a mismatch? Or is it still running?

Possibly not a round off error: I've found a few instances where CUDALucas uses cudaMalloc / malloc of a size larger than the data that is put there. You may need to call cudaMemset on g_x before copying x to it.

[CODE] v1.57 v1.64
size of cudaMalloc g_x 1.5*n + 2*STRIDE 1.25*n
size of memcpy x->g_x 1*n 1*n
[/CODE]I have not checked and of your other arrays to see if they have similar issues. They might need cudaMemset as well? I had a similar problem in gpuLucas, and am currently clearing all the arrays on initialization just to be safe.

[QUOTE=aaronhaviland;292330]I have not checked and of your other arrays to see if they have similar issues. They might need cudaMemset as well? I had a similar problem in gpuLucas, and am currently clearing all the arrays on initialization just to be safe.[/QUOTE]
Data initialization is no problem.
Roundoff error was HW issue.

[QUOTE=apsen;291992]I have rerun 29198173 with 1.63 and got another mismatch. BTW no err messages on 1.63 side and residues matched between 1.58 and 1.63 up to the point of the first 1.58 err message.

Running 29027371 with 1.63 now. ETA 33 hours. Will rerun 29198173 with older version once 29027371 completes.[/QUOTE]

Got mismatch for 29027371 with 1.63. :sad:

Got another match with 1.64.

[QUOTE=Batalov;292443]Got another match with 1.64.[/QUOTE]

Have you gotten enough matches to at least entertain the idea that 1.64 is well behaved?