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Old 2012-11-28, 03:15   #1
toorandom
 
Nov 2012

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Default Help with msieve CUDA (C1060)

Hello, i just downloaded msieve 1.50 and I have in my faculty a C1060

$ lspci | grep -i nv
01:00.0 3D controller: nVidia Corporation GT200 [Tesla C1060] (rev a1)

I just installed all the SDK and the problem is that when I compile it in this way

make x86_64 CUDA=1 NVCCFLAGS="-arch sm_13"

everything compiles fine and i can see that nvidia headers and libraries are being linked, in fact here are some relevant lines of the compilation

nvcc -m64 -arch sm_13 -ptx -o stage1_core.ptx \\ gnfs/poly/stage1/stage1_core_gpu/stage1_core.cu

gcc -D_FILE_OFFSET_BITS=64 -O3 -fomit-frame-pointer -DNDEBUG -D_LARGEFILE64_SOURCE -Wall -W -DMSIEVE_SVN_VERSION="\"exported\"" -I. -Iinclude -Ignfs -Ignfs/poly -Ignfs/poly/stage1 -I"/usr/local/cuda/include" -DHAVE_CUDA demo.c -o msieve \
libmsieve.a -lcuda -lz -lgmp -lm -lpthread



and the msieve binary ldd looks like

$ ldd msieve | grep -i cuda
libcuda.so.1 => /usr/lib64/libcuda.so.1 (0x00007fa1c2cfc000)


The big problem is that when I run it it doesnt use cuda, i have ran it with -g option and without , but when I run nvidia-smi -l it always says that
| No running compute processes found |


And if I run the nvidia samples, the process appears in the nvidia-smi command, here is how i run msieve and some output that shows that isnt using NVIDIA


$ ./msieve -g 0 -v 69986008711415694391421268580269058232048146719704518153244714221529713444447


Msieve v. 1.50 (SVN exported)
Tue Nov 27 21:17:09 2012
random seeds: 59e9351d e6fc711d
factoring 69986008711415694391421268580269058232048146719704518153244714221529713444447 (77 digits)
no P-1/P+1/ECM available, skipping
commencing quadratic sieve (77-digit input)
using multiplier of 1
using 32kb Intel Core sieve core
sieve interval: 12 blocks of size 32768
processing polynomials in batches of 17


Thanks
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Old 2012-11-28, 05:27   #2
LaurV
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Quote:
Originally Posted by toorandom View Post
Hello, i just downloaded msieve 1.50 and I have in my faculty a C1060
Man, say that is a Tesla C1060, you made my heart jump...
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Old 2012-11-28, 05:43   #3
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Only the NFS polynomial selection is CUDA-enabled. QS nor NFS sieving supports CUDA.
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Old 2012-11-28, 05:45   #4
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Quote:
Originally Posted by LaurV View Post
Man, say that is a Tesla C1060, you made my heart jump...
Don't get too excited. It's no faster than a GTX 460. Just has more memory.
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Old 2012-11-28, 06:13   #5
LaurV
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Quote:
Originally Posted by frmky View Post
Don't get too excited. It's no faster than a GTX 460. Just has more memory.
No, I thought he wanna factorize a composite C1060.
(edit: owned two C2070 by myself, see my former posts one year ago)

Last fiddled with by LaurV on 2012-11-28 at 06:16
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Old 2012-11-28, 08:43   #6
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Owned? What happened to them?
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Old 2012-11-28, 09:11   #7
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Quote:
Originally Posted by LaurV View Post
No, I thought he wanna factorize a composite C1060.
Here's a C1060. Completely factored, nothing to it, really.
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Old 2012-11-28, 17:37   #8
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frmky is correct, you are running the quadratic sieve and not the number field sieve. Use 'msieve -h' to get the complete list of command-line stuff you can use, but CUDA will only be useful for selecting NFS polynomials, and your current input is too small for the NFS code to handle (try an input larger than 85 digits, and specify an NFS task explicitly).
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