9/3/2023 0 Comments Satori importsline 12: -time=24:00:00 indicates the maximum run time you wish to allow.gres=gpu:4 and -nodes=2 = 4 x 2 = 8 GPU’s in total. Note: the total number of GPUS is the product of the -gres and the -nodes settings. a value of 1 means 1 node, a value of 2 means 2 nodes,Įtc. line 9: -nodes=1 here you put how many nodes you need.a value of 1 means you want onlyġ GPU on each node, a value of 4 means you want all GPUS’s on the node. line 7: -gres=gpu:4 here you can consider the no of GPUs you need per node e.g.Job output file and _err for the file with the related job errors line 2-4: with your desired job name, but remember to keep _out for the. Horovodrun -np $SLURM_NTASKS -H `cat $NODELIST ` python /data/ImageNet/pytorch_mnist.py export HOROVOD_GPU_ALLREDUCE =MPIĮcho " Running on multiple nodes/GPU devices" echo "" echo " Run started at:- " # Activate WMLCE virtual environment source $' | sed 's/,$//' > $NODELIST # Number of total processes echo " " echo " Nodelist:= " $SLURM_JOB_NODELIST echo " Number of nodes:= " $SLURM_JOB_NUM_NODES echo " GPUs per node:= " $SLURM_JOB_GPUS echo " Ntasks per node:= " $SLURM_NTASKS_PER_NODE # Use MPI for communication with Horovod - this can be hard-coded during installation as well. #!/bin/bash #SBATCH -J myjob_4GPUs #SBATCH -o myjob_4GPUs_%j.out #SBATCH -e myjob_4GPUs_%j.err #SBATCH #SBATCH -mail-type=ALL #SBATCH -gres=gpu:4 #SBATCH -gpus-per-node=4 #SBATCH -nodes=1 #SBATCH -ntasks-per-node=4 #SBATCH -mem=0 #SBATCH -time=24:00:00 #SBATCH -exclusive # User python environment HOME2 =/nobackup/users/ $(whoami ) PYTHON_VIRTUAL_ENVIRONMENT =wmlce-1.7.0 Shell) equivalent to the sample batch script above, you would use the For example, to request an interactive batch job (with bash as the Line are what makes the job “interactive batch”: -Is followed by a shell Via #SBATCH parameters in a batch script. Via the command line, which supports the same options that are passed System and, if necessary, wait until they are available. You must request the appropriate resources from the Possible to simply log into the system and begin running a parallel code Since all compute resources are managed/scheduled by SLURM, it is not Then work on other tasks however, it is sometimes preferable to run The system, since they permit you to hand off a job to the scheduler and Most users will find batch jobs to be the easiest way to interact with
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