slurm

问题 I’m trying to align 168 sequence files on our HPC using slurm version 14.03.0. I’m only allowed to use a maximum of 9 compute nodes at once to keep some nodes open for other people. I changed the file names so I could use the array function in sbatch. The sequence files look like this: Sequence1.fastq.gz, Sequence2.fastq.gz, … Sequence168.fastq.gz I can’t seem to figure out how to tell it to run all 168 files, 9 at a time. I can get it to run all 168 files, but it uses all the available nodes

问题 Background I need to run a blocks simulation. I've used OMEdit to create the system and I call omc to run the simulation using OMPython with zmq for messaging. The simulation works fine but now I need to move it to a server to simulate the system for long times. Since the server is shared among a team of people, it uses slurm to queue the jobs. The server has 32 cores but they asked me to use only 8 while I tune my script and then 24 when I want to run my final simulation. I've configured

问题 I am using Intel MPI and have encountered some confusing behavior when using mpirun in conjunction with slurm. If I run (in a login node) mpirun -n 2 python -c "from mpi4py import MPI; print(MPI.COMM_WORLD.Get_rank())" then I get as output the expected 0 and 1 printed out. If however I salloc --time=30 --nodes=1 and run the same mpirun from the interactive compute node, I get two 0s printed out instead of the expected 0 and 1. Then, if I change -n 2 to -n 3 (still in compute node), I get a

问题 Is there a way to oversubscribe GPUs on Slurm, i.e. run multiple jobs/job steps that share one GPU? We've only found ways to oversubscribe CPUs and memory, but not GPUs. We want to run multiple job steps on the same GPU in parallel and optionally specify the GPU memory used for each step. 回答1: The easiest way of doing that is to have the GPU defined as a feature rather than as a gres so Slurm will not manage the GPUs, just make sure that job that need one land on nodes that offer one. 来源：

问题 I want to parallelize an R script on a HPC with a Slurm scheduler. SLURM is configured with SelectType: CR_Core_Memory . Each compute node has 16 cores (32 threads). I pass the R script to SLURM with the following configuration using the clustermq as the interface to Slurm. #!/bin/sh #SBATCH --job-name={{ job_name }} #SBATCH --partition=normal #SBATCH --output={{ log_file | /dev/null }} # you can add .%a for array index #SBATCH --error={{ log_file | /dev/null }} #SBATCH --mem-per-cpu={{

问题 I have access to a cluster that's run by Slurm, in which each node has 4 GPUs. I have a code that needs 8 gpus. So the question is how can I request 8 gpus on a cluster that each node has only 4 gpus? So this is the job that I tried to submit via sbatch : #!/bin/bash #SBATCH --gres=gpu:8 #SBATCH --nodes=2 #SBATCH --mem=16000M #SBATCH --time=0-01:00 But then I get the following error: sbatch: error: Batch job submission failed: Requested node configuration is not available Then I changed my

问题 I have set up a small cluster (9 nodes) for computing in our lab. Currrently I am using one node as slurm controller, i.e. it is not being used for computing. I would like to use it too, but I do not want to allocate all the CPUs, I would like to keep 2 CPU free for scheduling and other master-node-related tasks. Is it possible to write something like that in slurm.conf : NodeName=master NodeHostname=master CPUs=10 RealMemory=192000 TmpDisk=200000 State=UNKNOWN NodeName=node0[1-8]

问题 sacct -n returns all job's name trimmed for example" QmefdYEri+ . [Q] How could I view the complete name of the job, instead of its trimmed version? -- $ sacct -n 1194 run.sh debug root 1 COMPLETED 0:0 1194.batch batch root 1 COMPLETED 0:0 1195 run_alper+ debug root 1 COMPLETED 0:0 1195.batch batch root 1 COMPLETED 0:0 1196 QmefdYEri+ debug root 1 COMPLETED 0:0 1196.batch batch root 1 COMPLETED 0:0 回答1: I use the scontrol command when I am interested in one particular jobid as shown below

问题 I have a front end and two compute nodes All have same slurm.conf file which ends with (for detail please see: https://gist.github.com/avatar-lavventura/46b56cd3a29120594773ae1c8bc4b72c): NodeName=ebloc2 NodeHostName=ebloc NodeAddr=54.227.62.43 CPUs=1 PartitionName=debug Nodes=ebloc2 Default=YES MaxTime=INFINITE State=UP NodeName=ebloc4 NodeHostName=ebloc NodeAddr=54.236.173.82 CPUs=1 PartitionName=debug Nodes=ebloc4 Default=YES MaxTime=INFINITE State=UP slurmctld : only checks first written

问题 I found some very similar questions which helped me arrive at a script which seems to work however I'm still unsure if I fully understand why, hence this question.. My problem (example): On 3 nodes, I want to run 12 tasks on each node (so 36 tasks in total). Also each task uses OpenMP and should use 2 CPUs. In my case a node has 24 CPUs and 64GB memory. My script would be: #SBATCH --nodes=3 #SBATCH --ntasks=36 #SBATCH --cpus-per-task=2 #SBATCH --mem-per-cpu=2000 export OMP_NUM_THREADS=2 for i