@@ -133,6 +133,9 @@ http://127.0.0.1:9001/?token=...(your token is here)...
```
Copy that address and paste it into your browser, and you must successfuly access Jupyter's GUI.
### Apptainer TensorFlow batch job example
## Interactive jobs
### Starting an Interactive job
To start an interactive job, you use the srun command with specific parameters that define your job's resource requirements. Here's an example:
...
...
@@ -291,7 +294,7 @@ mpirun -n $NUM ./$OBJ
```
This script compiles the MPI program using `mpicc` and runs it with `mpirun`, and specifies the number of processes with `-n`.
Next, prepare a SLURM batch job script named `job-test-mpi.sh` to submit your MPI job. This script requests cluster resources and runs your MPI program through `mpi_hello_world.sh`:
Next, prepare a SLURM batch job script named `job-test-mpi.sbatch` to submit your MPI job. This script requests cluster resources and runs your MPI program through `mpi_hello_world.sh`:
```bash
#!/bin/bash
#SBATCH --job-name=mpi_job_test
...
...
@@ -300,13 +303,14 @@ Next, prepare a SLURM batch job script named `job-test-mpi.sh` to submit your MP
#SBATCH --nodelist=gpu1,gpu2,cn01
#SBATCH --time=10:00
#SBATCH --mem-per-cpu=1000
module load openmpi4
echo"run mpi program using parallel processes"
sh mpi_hello_world.sh $1
```
This script sets up a job with the name mpi_job_test, specifies output and error files, requests resources (All 3 nodes from the cluster), and loads the OpenMPI module. It then runs the `mpi_hello_world.sh` script and passes the number of processes as an argument.
In the end, submit your parallel MPI job to SLURM using the sbatch command, specifying the desired number of parallel processes with -n. For example, to run with 8 parallel processes:
In the end, submit your parallel MPI job to SLURM using the sbatch command`sbatch job-test-mpi.sbatch`, specifying the desired number of parallel processes with `-n`. For example, to run with 8 parallel processes:
