CUDA on Linux

microchip
microchip
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Topic 195753

Hi,

Got a question here. I'm fairly new to CUDA and would like to add a CUDA capable GPU in my crunch system. I'm on Linux and my question is if I have to install anything special to make it work with BOINC and E@H? I mean do I need the proprietary driver from nVIDIA and do I need some specific CUDA kit for it to work?

Thanks :)

Michael Karlinsky
Michael Karlinsky
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CUDA on Linux

Hi,

you need to install the NVIDIA driver.

download

and

instructions

excerpt:

1) Kernel sources must be installed and configured. Usually this means
installing the 'kernel-source', 'make' and 'gcc' packages with YaST2. 

2) Run the following commands

echo "blacklist nouveau" > /etc/modprobe.d/nvidia.conf
# recreate initrd without KMS, if the use of KMS is enabled in initrd
if grep -q NO_KMS_IN_INITRD=\"no\" /etc/sysconfig/kernel; then
sed -i 's/NO_KMS_IN_INITRD.*/NO_KMS_IN_INITRD="yes"/g' /etc/sysconfig/kernel
mkinitrd
fi

3) Reboot your machine.

4) Use the nvidia installer for 260.19.36.

sh NVIDIA-Linux-x86_64-260.19.36.run -q

IMPORTANT: You need to recompile and install the nvidia kernel module
after each kernel update.

sh NVIDIA-Linux-x86_64-260.19.36.run -K

Michael

PS: instructions are for SUSE, but I guess they should work everywhere else.

microchip
microchip
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Thanks for the info. Yes, I

Thanks for the info. Yes, I know how to manually install the NV driver, but thanks anyways... So I don't need anything else for CUDA on linux? I saw on the NV site a CUDA kit but it's an SDK, not sure if I need that

Michael Karlinsky
Michael Karlinsky
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RE: I saw on the NV site a

Quote:
I saw on the NV site a CUDA kit but it's an SDK, not sure if I need that

This is for development only. All BOINC-project (should) provide the rest (there are some libs, which are necessary).

Michael

Jeroen
Jeroen
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Depending on which GPU you

Depending on which GPU you add to your system, you may be able to run multiple work units at once per GPU using an app_info.xml file. Specifically the 4xx and 5xx Fermi GPUs can run two or more work units at a time optimally provided there is enough GPU memory. Each work units requires around 300-350 MB of GPU memory.

microchip
microchip
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RE: Depending on which GPU

Quote:
Depending on which GPU you add to your system, you may be able to run multiple work units at once per GPU using an app_info.xml file. Specifically the 4xx and 5xx Fermi GPUs can run two or more work units at a time optimally provided there is enough GPU memory. Each work units requires around 300-350 MB of GPU memory.

Can you be more specific about the app_info.xml file? Where do I find it and what do I have to put in it?

Richard Haselgrove
Richard Haselgrove
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I'd recommend that you start

I'd recommend that you start with the driver stuff on it's own - you don't need an app_info.xml file for that.

Get it running, check some tasks through and make sure that they validate. The time for moving up to multiple copies is after you've got the plain vanilla version running OK.

microchip
microchip
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Guys, a final

Guys, a final question...

Do I need a specific driver version or can I grab the 280.13 one?

I'm asking because on http://developer.nvidia.com/cuda-toolkit-40 I see there's an older driver version (270.41.19) while the normal driver download page of nVIDIA offers version 280.13... so which one should I get ?

Thanks

Richard Haselgrove
Richard Haselgrove
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You certainly don't need a

You certainly don't need a developer toolkit. Just the ordinary 280.13 should do it, though we have been having some problems with downclocking with the newer *windows* drivers. If you seem to have any problems like that, look for a menu item for "Beta and Archived Drivers" on the general - not developer - download page, and you should be able to find what you need there.

microchip
microchip
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OK... thanks Richard for your

OK... thanks Richard for your help :)

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