[slurm-users] How to use Autodetect=nvml in gres.conf

Stephan Roth stephan.roth at ee.ethz.ch
Fri Feb 7 16:57:34 UTC 2020


gpu_nvml.so links to libnvidia-ml.so:

$ ldd lib/slurm/gpu_nvml.so
	...
	libnvidia-ml.so.1 => /usr/lib/x86_64-linux-gnu/libnvidia-ml.so.1 
(0x00007f2d2bac8000)
	...

When you run configure you'll see something along these lines:


On 07.02.20 17:03, dean.w.schulze at gmail.com wrote:
> I just checked the .deb package that I build from source and there is nothing in it that has nv or cuda in its name.
> 
> Are you sure that slurm distributes nvidia binaries?
> 
> -----Original Message-----
> From: slurm-users <slurm-users-bounces at lists.schedmd.com> On Behalf Of Stephan Roth
> Sent: Friday, February 7, 2020 2:23 AM
> To: slurm-users at lists.schedmd.com
> Subject: Re: [slurm-users] How to use Autodetect=nvml in gres.conf
> 
> On 05.02.20 21:06, Dean Schulze wrote:
>   > I need to dynamically configure gpus on my nodes.  The gres.conf doc
>   > says to use
>   >
>   > Autodetect=nvml
> 
> That's all you need in gres.conf provided you don't configure any
> Gres=... entries for your nodes in your slurm.conf.
> If you do, make sure the string matches what NVML discovers, i.e.
> lowercase and underscores instead of spaces or dashes.
> 
> The upside of configuring everything is you will be informed in case the
> automatically detected GPUs in a node don't match what you configured.
> 
>   > in gres.conf instead of adding configuration details to each gpu in
>   > gres.conf.  The docs aren't really clear about this because they show an
>   > example with the details for each gpu:
>   >
>   > AutoDetect=nvml
>   > Name=gpu Type=gp100  File=/dev/nvidia0 Cores=0,1
>   > Name=gpu Type=gp100  File=/dev/nvidia1 Cores=0,1
>   > Name=gpu Type=p6000  File=/dev/nvidia2 Cores=2,3
>   > Name=gpu Type=p6000  File=/dev/nvidia3 Cores=2,3
>   > Name=mps Count=200  File=/dev/nvidia0
>   > Name=mps Count=200  File=/dev/nvidia1
>   > Name=mps Count=100  File=/dev/nvidia2
>   > Name=mps Count=100  File=/dev/nvidia3
>   > Name=bandwidth Type=lustre Count=4G
>   >
>   > First Question:  If I use Autodetect=nvml do I also need to specify
>   > File= and Cores= for each gpu in gres.conf?  I'm hoping that with
>   > Autodetect=nvml that all I need is the Name= and Type= for each gpu.
>   > Otherwise it's not clear what the purpose of setting Autodetect=nvml
>   > would be.
>   >
>   > Second Question:  I installed the CUDA tools from the binary
>   > cuda_10.2.89_440.33.01_linux.run.  When I restart slurmd with
>   > Autodetect=nvml in gres.conf I get this error:
>   >
>   > fatal: We were configured to autodetect nvml functionality, but we
>   > weren't able to find that lib when Slurm was configured.
>   >
>   > Is there something else I need to configure to tell slurmd how to use
> nvml?
> 
> I guess the version of slurm you're using was linked against a version
> of NVML which has been overwritten by your installation of Cuda 10.2
> 
> If that's the case there are various ways to solve that problem, but
> that depends on your reason to install Cuda 10.2.
> 
> My recommendation is to use the Cuda version of your system matching
> your system's slurm package and to install Cuda 10.2 in a non-default
> location, provided you need to make it available on a cluster node.
> 
> If people using your cluster ask for Cuda 10.2 they have the option of
> using a virtual conda environment and install Cuda 10.2 there.
> 
> 
> Cheers,
> Stephan
> 
> 
> 


-------------------------------------------------------------------
Stephan Roth | ISG.EE D-ITET ETH Zurich | http://www.isg.ee.ethz.ch
+4144 632 30 59  |  ETF D 104  |  Sternwartstrasse 7  | 8092 Zurich
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