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#!/bin/bash #PBS -N cuda #PBS -l walltime=100:00:00 #PBS -l select=1:ncpus=1:mem=15gb2gb:ngpus=1,walltime=01:00:00 #PBS -W group_list=gpu #PBS -q gpu gpuq2 cd $PBS_O_WORKDIR source $HOME/.bashrc module load cudaanaconda3/4.0.172022.10 source activate TorchA100 echo "Hello from $HOSTNAME: date = `date`" nvcc --version echo "Finished at `date`" |
sample 2
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#!/bin/bash -l #PBS -m abe #PBS -M emailaddress@griffith.edu.au #PBS -N CudaJob #PBS -q gpu #PBS -l select=21:ncpus=2:mem=2gb:ngpus=1 #PBS -W group_list=gpu cd $PBS_O_WORKDIR source $HOME/.bashrc module load NAMD/NAMD28b1 module load mpi/intel-4.0 echo "Starting job" mpirun -r ssh -n 2 namd2 +idlepoll /export/home/s2594054/pbs/namd/apoa1/namd/apoa1.namd > apoa1.namd.log echo "Done with job" |
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cudnn-10.0 ============ tar -zxvf cudnn-10.0-linux-x64-v7.6.5.32.tgz cuda/include/cudnn.h cuda/NVIDIA_SLA_cuDNN_Support.txt cuda/lib64/libcudnn.so cuda/lib64/libcudnn.so.7 cuda/lib64/libcudnn.so.7.6.5 cuda/lib64/libcudnn_static.a cp cuda/include/cudnn.h /usr/local/cuda-10.0/include/ cp cuda/lib64/libcudnn* /usr/local/cuda-10.0/lib64 chmod a+r /usr/local/cuda-10.0/include/cudnn.h /usr/local/cuda-10.0/lib64/libcudnn* cudnn-10.1 ========== cd /tmp; tar -zxvf cudnn-10.1-linux-x64-v7.6.5.32.tgz cp cuda/include/cudnn.h /usr/local/cuda-10.1/include/ cp cuda/lib64/libcudnn* /usr/local/cuda-10.1/lib64 chmod a+r /usr/local/cuda-10.1/include/cudnn.h /usr/local/cuda-10.1/lib64/libcudnn* cudnn-10.2 ========== tar -zxvf cudnn-10.2-linux-x64-v7.6.5.32.tgz cp cuda/include/cudnn.h /usr/local/cuda-10.2/include/ cp cuda/lib64/libcudnn* /usr/local/cuda-10.2/lib64 chmod a+r /usr/local/cuda-10.2/include/cudnn.h /usr/local/cuda-10.2/lib64/libcudnn* |
Sample pbs script to run on n061 - gpuq2
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#!/bin/bash
#PBS -m abe
#PBS -M emailaddress@griffith.edu.au
#PBS -N CudaJob
#PBS -q gpuq2
#PBS -l select=1:ncpus=1:mem=2gb:ngpus=1,walltime=01:00:00
cd $PBS_O_WORKDIR
source $HOME/.bashrc
module load anaconda3/2022.10
source activate TorchA100
echo "Starting job"
python isCuda
echo "Done with job"
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