CDS Teaching Cluster

The CDS Teaching cluster has 1 master nodes, and 1 compute node with 96 CPU cores and 2 GPUs.

First OpenMP program

  1. Download test-openmp.c, Makefile, sample-script. The script runs a simple OpenMP program on a single node.
  2. Login to the teaching cluster with your account.
  3. Create a directory called OpenMP. In another terminal, transfer the three downloaded files from your unix machine to the teaching cluster’s openmp_test directory using scp:
    >> scp test-openmp.c Makefile sample-script <your-account>@10.24.36.80:~/OpenMP
  4. Compile using
    >> make
  5. Submit to PBS using
    >> qsub sample-script
  6. Monitor your submitted job using
    >> qstat
  7. After your program finishes, you will see output of your program in “myjob<id>.o<num>” file. If your run produced error, you will see the error message in “myjob<id>.e<num>” file

Happy OpenMP!

First MPI program

  1. Download test-mpi.c, Makefile, sample-script. The script runs 32 MPI processes on 32 cores.
  2. Login to the teaching cluster with your account.
  3. Create a directory called MPI. In another terminal, transfer the three downloaded files from your unix machine to the turing cluster’s openmp_test directory using scp:
    >> scp scp test-mpi.c Makefile sample-script <your-account>@10.24.36.80:~/MPI
  4. Compile using
    >> make
  5. Submit to PBS using
    >> qsub sample-script
  6. Monitor your submitted job using
    >> qstat
  7. After your program finishes, you will see output of your program in “myjob<id>.o<num>” file. If your run produced error, you will see the error message in “myjob<id>.e<num>” file

Happy MPI!

First CUDA program

  1. Download test-cuda.cu, Makefile, sample-script
  2. Login to the teaching cluster with your account
  3. Create a directory called CUDA. In another terminal, transfer the three downloaded files from your Unix machine to the cluster’s CUDA directory using scp:
    • >> scp test-cuda.cu Makefile sample-script <your account>@10.24.36.80:~/CUDA
  4. Run the following to load CUDA
    • >> module load cuda
  5. Compile using
    >> make
  6. Submit to queue using
    >> sbatch sample-script
  7. Monitor your submitted job using
    >> squeue
  8. After your program finishes, you will see output of your program in “myjob<id>.o<num>” file. If your run produced error, you will see the error message in “myjob<id>.e<num>” file.

Happy CUDA!