![]() |
![]() |
#1 | |
∂2ω=0
Sep 2002
República de California
5·2,351 Posts |
![]()
Our dear forum owner Xyzzy is kindly loaning me his old low-end (but still with extant DP-float support) GT 430 card, which should allow me to do most of the GPU code-dev I intend to do in the coming 6-12 months. He has warned me, however, that the tools-install is a real adventure, and to use the local-expertise around here as a resource. Here are some nuggets from our e-mail exchange:
Quote:
To the experts: So, just how much fun am I in for? Would downloading the cuda toolkit from the above debian.org link be a good thing to do while I await USPS delivery of the card? Re. the DVI connectors: I have a small LCD monitor I can unbox if needed, but not sure if it has such outputs. (But can easily check, if that helps). My normal way of talking with the Haswell box is via direct ethernet cable to my macbook - the minimalist in me would prefer to continue to do that with the GPU-augmented ATX-cased system, if possible. |
|
![]() |
![]() |
![]() |
#2 |
"/X\(‘-‘)/X\"
Jan 2013
310610 Posts |
![]()
I run two GT430s. I run them on Ubuntu 14.04. I simply enable the third party repository, and installing the nvidia-331 and nvidia-cuda-dev and nvidia-cuda-toolkit packages. That should give you CUDA 6 in the driver and CUDA 5.5 for development. Compiling mfaktc then works:
sudo apt-get install build-essential -y cd ~ wget http://www.mersenneforum.org/mfaktc/...tc-0.20.tar.gz tar xf mfaktc-0.20.tar.gz && cd mfaktc-0.20/src && make -j You'll then have it installed in mfaktc. For automatic fetching of work from GPU72, I recommend teknohog's mfloop.py script (which I've also contributed to) at https://github.com/teknohog/primetools . Installing that is as simple as sudo apt-get install git python -y git clone https://github.com/teknohog/primetools Run the script with the --help switch to look at the options. It can do almost everything. I'm working on more features at https://github.com/MarkRose/primetools . I use a crontab like this: Code:
@reboot cd $HOME/mfaktc-0.20 && screen -S mfaktc -d -m $HOME/mfaktc-0.20/mfaktc.exe -d 0 22 * * * * $HOME/primetools/mfloop.py -u lolomg -p drowssap -U lolomg -P drowssap -t 0 -w $HOME/mfaktc-0.20 -e 74 -g 60 -o let_gpu72_decide If you want to sick with Debian, I've found in the past that the NVidia packages don't put the new libraries under the cuda directory in the shared object path. Assuming CUDA 6, run something like: echo /usr/local/cuda-6.0/lib | sudo tee /etc/ld.so.conf/cuda.conf sudo ldconfig Then you'll need to edit mfaktc-0.20/src/Makefile change line 12 from NVCC = nvcc to NVCC = /usr/local/cuda-6.0/bin/nvcc before compiling. Last fiddled with by Mark Rose on 2014-07-01 at 04:15 |
![]() |
![]() |
![]() |
#3 |
Bamboozled!
"𒉺𒌌𒇷𒆷𒀭"
May 2003
Down not across
2·73·17 Posts |
![]()
FWIW, getting CUDA to run on my Gentoo systems was very nearly trivial. The downside, of course, is that Gentoo doesn't install very much by default and so you need to know what you want. For instance, Ernst's accunt has been re-vived on my system; he discovered gdb was missing so an "emerge gdb" is chuntering away as I type.
Last fiddled with by xilman on 2014-07-01 at 07:53 Reason: s/an an/so an/ |
![]() |
![]() |
![]() |
#4 |
"Kieren"
Jul 2011
In My Own Galaxy!
2·3·1,693 Posts |
![]() |
![]() |
![]() |
![]() |
#5 |
Sep 2009
22·607 Posts |
![]()
Look at the " ECM for CUDA GPUs in latest GMP-ECM ? " thread http://mersenneforum.org/showthread.php?t=16480&page=22 posts 209-234 for details of the fun I had installing it. The system I installed it on runs Linux Mint 15 which is descended from Debian.
Chris |
![]() |
![]() |
![]() |
#6 |
"Serge"
Mar 2008
Phi(4,2^7658614+1)/2
3·7·479 Posts |
![]()
I used CUDA on OpenSUSE for a couple years. Initial installation was very easy. However, after OpenSUSE update to the next major version, all the hell broke loose and X wouldn't start with some rather idiotic message (well, it actually would start with a black screen and a tiny, meaningless error dialog in the corner). It took many hours to fix (partly because there is almost no guide anywhere how to perform even the simplest tasks in a graphics-less system, from a tty). It was something very specific to SUSE, I don't remember now the full details and I really hope that you won't have any of these troubles.
In fact, when after the next OS upgrade/ nvidia dirver update the whole story repeated, for quite a while I didn't use X; just six tty's. It was all the same for me at the time because I was running a few LA (a few weeks each) that even benefited from having more available memory (because there was no X). |
![]() |
![]() |
![]() |
#7 |
Bamboozled!
"𒉺𒌌𒇷𒆷𒀭"
May 2003
Down not across
2·73·17 Posts |
![]() |
![]() |
![]() |
![]() |
#8 | |
Bamboozled!
"𒉺𒌌𒇷𒆷𒀭"
May 2003
Down not across
2D8E16 Posts |
![]() Quote:
Eventually NVidia solved the problem properly and I've not had any significant trouble with CUDA thereafter. To be fair, I tend to stick with the RedHat family (CentOS, Fedora, etc) or Gentoo so there may be a lesson there for SuSE and/or Debian and/or Ubuntu fans. |
|
![]() |
![]() |
![]() |
#9 |
"Serge"
Mar 2008
Phi(4,2^7658614+1)/2
100111010010112 Posts |
![]()
Yes, later there was some 1-click-update service at OpenSUSE (that tries to do all magic spells for you and actually does them well). But the first time (when OpenSUSE was still 12.1-pre, I think, upping from 11.x) was awful. The hard way.
|
![]() |
![]() |
![]() |
#10 |
∂2ω=0
Sep 2002
República de California
1175510 Posts |
![]()
Thanks for all the replies, now I need to spend some time triaging the various suggestions into some kind of "try this, this and this first" priority order.
Is that for the CUDA toolkit or mfaktc? If for CUDA, will that work across my hardcoded LAN setup? [My Haswell only talks to my macbook - no wireless, as I said this is a barebones system]. Yes, one must vagilently guard against such embarrassing faux pas at all times. |
![]() |
![]() |
![]() |
#11 |
Jan 2005
Caught in a sieve
39510 Posts |
![]()
I'm on Linux Mint Debian Edition, with a GT430 at the moment. I never had much trouble installing CUDA. It's similar to installing the binary Nvidia driver, which you should do first, except that you don't have to shut down the window manager to install CUDA. For me I think it was as simple as running the BLOB, downloaded from Nvidia's website, with sudo.
If you need to run apt-get and don't have direct Internet access, maybe you need to set up a proxy? This appears to be a SQUID proxy for Mac OS X. |
![]() |
![]() |
![]() |
Thread Tools | |
![]() |
||||
Thread | Thread Starter | Forum | Replies | Last Post |
How to install v25.9 on Linux? | Unregistered | Information & Answers | 10 | 2018-07-04 09:13 |
CUDA Install errors...HELP...never mind | petrw1 | GPU Computing | 2 | 2016-03-06 13:39 |
TF fetching/reporting toolkit for Linux | swl551 | PrimeNet | 20 | 2014-06-19 15:00 |
CUDA Toolkit for OpenSUSE 11.2--gcc 4.5 and up are not supported | patrik | GPU Computing | 9 | 2012-04-07 03:50 |
NVIDIA CUDA C toolkit for G80 GPU available | dsouza123 | Programming | 2 | 2007-02-18 12:50 |