![]() To be able to do that, there are many Linux tools that can help you inspect how it is performing in real-time.īefore we proceed you can check your cpu details with the lscpu command. It will show a textual representation of GPU and GPU Memory utilization along with details of each process running on both the GPUs of the node.Time to time, while you administer servers in your day to day roles, you would wish to check how the CPU of your system is faring especially if you suspect that something might be consuming more than it is supposed to. # Load the cuda Environment ~]$ module load cuda/9.2 To check the utilization of GPU nodes, you can run nvidia-smi For more information about htop, see htop homepage It will show a graphical representation of CPU and Memory utilization along with details of each process. # RUN ON THE COMPUTE NODE (STANDARD NODES) To check the utilization of standard nodes, you can run htop Note that the hostname in the prompt ~]$ ssh ~]$ JOBID PARTITION NAME USER ST TIME NODES NODELIST(REASON) # Check Slurm job queue to find the allocated node ~]$ squeue -u $USER ![]() Now check the compute node name on which your Slurm job is running. # Copy the public key into list of authorized keysĬat ~/.ssh/id_ecdsa.pub > ~/.ssh/authorized_keys # This saves the key pair at the default location and doesn't set passphrase. # Press Enter 3 times for the prompts to accept the default values. You can do this only for the compute nodes on which your Slurm job is currently running.īefore using the SSH command on the login node, you should generate a new SSH key pair on the login node on Kay and add it to your authorized keys on Kay. ![]() To check the utilization of compute nodes, you can SSH to it from any login node and then run commands such as htop and nvidia-smi. You can check the utilization of the compute nodes to use Kay efficiently and to identify some common mistakes in the Slurm submission scripts.
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