Hello,

@Russel - good catch.  No, I'm not actually missing the square bracket.  It
got lost during the copy/paste.  I'll restate it below for clarity :
2. grep NodeName slurm.conf
root@h01:# grep NodeName slurm.conf
NodeName=dgx[01,02] RealMemory=2063937 Boards=1 SocketsPerBoard=2
CoresPerSocket=56 ThreadsPerCore=2 MemSpecLimit=30017 Gres=gpu:1g.20gb:32
Feature=location=local
NodeName=dgx*[*03-10] RealMemory=2063937 Boards=1 SocketsPerBoard=2
CoresPerSocket=56 ThreadsPerCore=2 MemSpecLimit=30017 Gres=gpu:H100:8
Feature=location=local

@Keshav : It still doesn't work
user@l01:~$ srun --reservation=g09_test --nodelist=dgx09 --gres=gpu:h100:2
--pty bash
srun: error: Unable to create step for job 107044: Invalid generic resource
(gres) specification

Best,
Lee


On Tue, Nov 25, 2025 at 12:49 PM Russell Jones via slurm-users <
[email protected]> wrote:

> > NodeName=dgx03-10] RealMemory=2063937 Boards=1 SocketsPerBoard=2
> CoresPerSocket=56 ThreadsPerCore=2 MemSpecLimit=30017 Gres=gpu:H100:8
> Feature=location=local
>
> Just in case, that line shows you are missing a bracket in the node name.
> Are you *actually* missing the bracket?
>
>
> On Tue, Nov 25, 2025 at 9:11 AM Lee via slurm-users <
> [email protected]> wrote:
>
>> Hello,
>>
>> Sorry for the delayed response, SC25 interfered with my schedule.
>>
>> *Answers* :
>> 1. Yes, dgx09 and all the others boot the same software images.
>>
>> 2. dgx09 and the other nodes mount a shared file system where Slurm is
>> installed, so /cm/shared/apps/slurm/23.02.6/lib64/slurm/gpu_nvml.so is
>> the same for every node.  I assume the library that is used for
>> autodetection lives there.  I also found a shared library 
>> /usr/lib/x86_64-linux-gnu/libnvml_injection.so.1.0
>> (within the software image).  I checked the md5sum and it is the same on
>> both dgx09 and a non-broken node.
>>
>> 3. `scontrol show config` is the same on dgx09 and a non-broken DGX.
>>
>> 4. The only meaningful difference between `scontrol show node` for dgx09
>> and dgx08 (a working node) is :
>>
>> <    Gres=gpu:*h100*:8(S:0-1)
>> ---
>> >    Gres=gpu:*H100*:8(S:0-1)
>>
>> 5. Yes, we've restarted slurmd and slurmctld several times, the behavior
>> persists.  Of note, when I run `scontrol reconfigure`, the phantom
>> allocated GPUs (see AllocTRES in original post) are cleared.
>>
>>
>> *Important Update :*
>> 1. We recently had another GPU tray replaced and now that DGX is
>> experiencing the same behavior as dgx09.  I am more convinced that there is
>> something subtle with how the hardware is being detected by Slurm.
>>
>> Best regards,
>> Lee
>>
>>
>> On Mon, Nov 17, 2025 at 4:06 PM Timony, Mick <
>> [email protected]> wrote:
>>
>>> Hi Lee,
>>>
>>> I manage a BCM cluster as well. Does DGX09 have the same disk image and
>>> libraries in place? Could the NVidia NVML library, used to auto-detect the
>>> GPU's, be a diff version and causing the case differences?
>>>
>>> If you compare the output of scontrol show node dgx09 and another DGX
>>> node, do they look the same? Does scontrol show config look different
>>> on DGX09 and other nodes?
>>>
>>> Have you restarted the Slurm controllers (slurmctld) and restarted
>>> slurmd on the compute nodes?
>>>
>>> Kind regards
>>>
>>> --
>>> Mick Timony
>>> Senior DevOps Engineer
>>> LASER, Longwood, & O2 Cluster Admin
>>> Harvard Medical School
>>> --
>>> ------------------------------
>>> *From:* Lee via slurm-users <[email protected]>
>>> *Sent:* Friday, November 14, 2025 7:17 AM
>>> *To:* John Hearns <[email protected]>
>>> *Cc:* [email protected] <[email protected]>
>>> *Subject:* [slurm-users] Re: Invalid generic resource (gres)
>>> specification after RMA
>>>
>>> Hello,
>>>
>>> Thank you for the suggestion.
>>>
>>> I ran lspci on dgx09 and a working DGX and the output was identical.
>>>
>>> nvidia-smi shows all 8 GPUs and looks the same as the output from a
>>> working DGX :
>>>
>>> root@dgx09:~# nvidia-smi
>>> Fri Nov 14 07:11:05 2025
>>>
>>> +---------------------------------------------------------------------------------------+
>>> | NVIDIA-SMI 535.129.03             Driver Version: 535.129.03   CUDA
>>> Version: 12.2     |
>>>
>>> |-----------------------------------------+----------------------+----------------------+
>>> | GPU  Name                 Persistence-M | Bus-Id        Disp.A |
>>> Volatile Uncorr. ECC |
>>> | Fan  Temp   Perf          Pwr:Usage/Cap |         Memory-Usage |
>>> GPU-Util  Compute M. |
>>> |                                         |                      |
>>>         MIG M. |
>>>
>>> |=========================================+======================+======================|
>>> |   0  NVIDIA H100 80GB HBM3          On  | 00000000:1B:00.0 Off |
>>>              0 |
>>> | N/A   29C    P0              69W / 700W |      4MiB / 81559MiB |
>>>  0%      Default |
>>> |                                         |                      |
>>>       Disabled |
>>>
>>> +-----------------------------------------+----------------------+----------------------+
>>> |   1  NVIDIA H100 80GB HBM3          On  | 00000000:43:00.0 Off |
>>>              0 |
>>> | N/A   30C    P0              71W / 700W |      4MiB / 81559MiB |
>>>  0%      Default |
>>> |                                         |                      |
>>>       Disabled |
>>>
>>> +-----------------------------------------+----------------------+----------------------+
>>> |   2  NVIDIA H100 80GB HBM3          On  | 00000000:52:00.0 Off |
>>>              0 |
>>> | N/A   33C    P0              71W / 700W |      4MiB / 81559MiB |
>>>  0%      Default |
>>> |                                         |                      |
>>>       Disabled |
>>>
>>> +-----------------------------------------+----------------------+----------------------+
>>> |   3  NVIDIA H100 80GB HBM3          On  | 00000000:61:00.0 Off |
>>>              0 |
>>> | N/A   31C    P0              73W / 700W |      4MiB / 81559MiB |
>>>  0%      Default |
>>> |                                         |                      |
>>>       Disabled |
>>>
>>> +-----------------------------------------+----------------------+----------------------+
>>> |   4  NVIDIA H100 80GB HBM3          On  | 00000000:9D:00.0 Off |
>>>              0 |
>>> | N/A   29C    P0              68W / 700W |      4MiB / 81559MiB |
>>>  0%      Default |
>>> |                                         |                      |
>>>       Disabled |
>>>
>>> +-----------------------------------------+----------------------+----------------------+
>>> |   5  NVIDIA H100 80GB HBM3          On  | 00000000:C3:00.0 Off |
>>>              0 |
>>> | N/A   28C    P0              69W / 700W |      4MiB / 81559MiB |
>>>  0%      Default |
>>> |                                         |                      |
>>>       Disabled |
>>>
>>> +-----------------------------------------+----------------------+----------------------+
>>> |   6  NVIDIA H100 80GB HBM3          On  | 00000000:D1:00.0 Off |
>>>              0 |
>>> | N/A   30C    P0              70W / 700W |      4MiB / 81559MiB |
>>>  0%      Default |
>>> |                                         |                      |
>>>       Disabled |
>>>
>>> +-----------------------------------------+----------------------+----------------------+
>>> |   7  NVIDIA H100 80GB HBM3          On  | 00000000:DF:00.0 Off |
>>>              0 |
>>> | N/A   32C    P0              69W / 700W |      4MiB / 81559MiB |
>>>  0%      Default |
>>> |                                         |                      |
>>>       Disabled |
>>>
>>> +-----------------------------------------+----------------------+----------------------+
>>>
>>>
>>> +---------------------------------------------------------------------------------------+
>>> | Processes:
>>>                |
>>> |  GPU   GI   CI        PID   Type   Process name
>>>      GPU Memory |
>>> |        ID   ID
>>>     Usage      |
>>>
>>> |=======================================================================================|
>>> |  No running processes found
>>>                 |
>>>
>>> +---------------------------------------------------------------------------------------+
>>>
>>>
>>> Best regards,
>>> Lee
>>>
>>> On Fri, Nov 14, 2025 at 3:53 AM John Hearns <[email protected]> wrote:
>>>
>>> I work for AMD...
>>> diagnostics I woud run are    lspci     nvidia-smi
>>>
>>> On Thu, 13 Nov 2025 at 19:18, Lee via slurm-users <
>>> [email protected]> wrote:
>>>
>>> Good afternoon,
>>>
>>> I have a cluster that is managed by Base Command Manager (v10) and it
>>> has several Nvidia DGXs.  dgx09 is a problem child.  The entire node was
>>> RMA'd and now it no longer behaves the same as my other DGXs.  I think the
>>> below symptoms are caused by a single underlying issue.
>>>
>>> *Symptoms : *
>>> 1. When I look at our 8 non-MIG DGXs, via `scontrol show node=dgxXY |
>>> grep Gres`, 7/8 DGXs report "Gres=gpu:*H100*:8(S:0-1)" while dgx09
>>> reports "Gres=gpu:*h100*:8(S:0-1)"
>>>
>>> 2. When I submit a job to this node, I get :
>>>
>>> $ srun --reservation=g09_test --gres=gpu:2 --pty bash
>>> srun: error: Unable to create step for job 105035: Invalid generic
>>> resource (gres) specification
>>>
>>> ### No job is running on the node, yet AllocTRES shows consumed
>>> resources...
>>> $ scontrol show node=dgx09 | grep -i AllocTRES
>>>    *AllocTRES=gres/gpu=2*
>>>
>>> ### dgx09 : /var/log/slurmd contains no information
>>> ### slurmctld shows :
>>> root@h01:# grep 105035 /var/log/slurmctld
>>> [2025-11-13T07:44:56.380] sched: _slurm_rpc_allocate_resources
>>> JobId=105035 NodeList=dgx09 usec=3420
>>> [2025-11-13T07:44:56.482] _job_complete: JobId=105035 WTERMSIG 1
>>> [2025-11-13T07:44:56.483] _job_complete: JobId=105035 done
>>>
>>>
>>> *Configuration : *
>>> 1. gres.conf :
>>> # This section of this file was automatically generated by cmd. Do not
>>> edit manually!
>>> # BEGIN AUTOGENERATED SECTION -- DO NOT REMOVE
>>> AutoDetect=NVML
>>> NodeName=dgx[01,02] Name=gpu Type=1g.20gb Count=32 AutoDetect=NVML
>>> NodeName=dgx[03-10] Name=gpu Type=h100 Count=8 AutoDetect=NVML
>>> # END AUTOGENERATED SECTION   -- DO NOT REMOVE
>>>
>>> 2. grep NodeName slurm.conf
>>> root@h01:# grep NodeName slurm.conf
>>> NodeName=dgx[01,02] RealMemory=2063937 Boards=1 SocketsPerBoard=2
>>> CoresPerSocket=56 ThreadsPerCore=2 MemSpecLimit=30017 Gres=gpu:1g.20gb:32
>>> Feature=location=local
>>> NodeName=dgx03-10] RealMemory=2063937 Boards=1 SocketsPerBoard=2
>>> CoresPerSocket=56 ThreadsPerCore=2 MemSpecLimit=30017 Gres=gpu:H100:8
>>> Feature=location=local
>>>
>>> 3. What slurmd detects on dgx09
>>>
>>> root@dgx09:~# slurmd -C
>>> NodeName=dgx09 CPUs=224 Boards=1 SocketsPerBoard=2 CoresPerSocket=56
>>> ThreadsPerCore=2 RealMemory=2063937
>>> UpTime=8-00:39:10
>>>
>>> root@dgx09:~# slurmd -G
>>> slurmd: gpu/nvml: _get_system_gpu_list_nvml: 8 GPU system device(s)
>>> detected
>>> slurmd: Gres Name=gpu Type=h100 Count=1 Index=0 ID=7696487
>>> File=/dev/nvidia0 Cores=0-55 CoreCnt=224 Links=-1,0,0,0,0,0,0,0
>>> Flags=HAS_FILE,HAS_TYPE,ENV_NVML
>>> slurmd: Gres Name=gpu Type=h100 Count=1 Index=1 ID=7696487
>>> File=/dev/nvidia1 Cores=0-55 CoreCnt=224 Links=0,-1,0,0,0,0,0,0
>>> Flags=HAS_FILE,HAS_TYPE,ENV_NVML
>>> slurmd: Gres Name=gpu Type=h100 Count=1 Index=2 ID=7696487
>>> File=/dev/nvidia2 Cores=0-55 CoreCnt=224 Links=0,0,-1,0,0,0,0,0
>>> Flags=HAS_FILE,HAS_TYPE,ENV_NVML
>>> slurmd: Gres Name=gpu Type=h100 Count=1 Index=3 ID=7696487
>>> File=/dev/nvidia3 Cores=0-55 CoreCnt=224 Links=0,0,0,-1,0,0,0,0
>>> Flags=HAS_FILE,HAS_TYPE,ENV_NVML
>>> slurmd: Gres Name=gpu Type=h100 Count=1 Index=4 ID=7696487
>>> File=/dev/nvidia4 Cores=56-111 CoreCnt=224 Links=0,0,0,0,-1,0,0,0
>>> Flags=HAS_FILE,HAS_TYPE,ENV_NVML
>>> slurmd: Gres Name=gpu Type=h100 Count=1 Index=5 ID=7696487
>>> File=/dev/nvidia5 Cores=56-111 CoreCnt=224 Links=0,0,0,0,0,-1,0,0
>>> Flags=HAS_FILE,HAS_TYPE,ENV_NVML
>>> slurmd: Gres Name=gpu Type=h100 Count=1 Index=6 ID=7696487
>>> File=/dev/nvidia6 Cores=56-111 CoreCnt=224 Links=0,0,0,0,0,0,-1,0
>>> Flags=HAS_FILE,HAS_TYPE,ENV_NVML
>>> slurmd: Gres Name=gpu Type=h100 Count=1 Index=7 ID=7696487
>>> File=/dev/nvidia7 Cores=56-111 CoreCnt=224 Links=0,0,0,0,0,0,0,-1
>>> Flags=HAS_FILE,HAS_TYPE,ENV_NVML
>>>
>>>
>>> *Questions : *
>>> 1. As far as I can tell, dgx09 is identical to all my non-MIG DGX nodes
>>> in terms of configuration and hardware.  Why does scontrol report it having
>>> 'h100' with a lower case 'h' unlike the other dgxs which report with an
>>> upper case 'H'?
>>>
>>> 2. Why is dgx09 not accepting GPU jobs and afterwards it artificially
>>> thinks that there are GPUs allocated even though no jobs are on the node?
>>>
>>> 3. Are there additional tests / configurations that I can do to probe
>>> the differences between dgx09 and all my other nodes?
>>>
>>> Best regards,
>>> Lee
>>>
>>> --
>>> slurm-users mailing list -- [email protected]
>>> To unsubscribe send an email to [email protected]
>>>
>>>
>> --
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>>
>
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