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Job Templates

Here you can find example job script templates for a variety of job types

  1. Single-threaded tasks
  2. Array jobs
  3. Multi-threaded tasks
  4. MPI tasks
  5. Hybrid MPI/OpenMP tasks
  6. GPU tasks
  7. MPI+GPU tasks

You can copy and paste the examples to use as a base - don't forget to edit the account and e-mail address as well as which software you want to use!

For all the possible things you can ask for see the official documentation at https://slurm.schedmd.com/sbatch.html

Single threaded tasks

Here we want to use a tool that cannot make use of more than one CPU at a time.

The important things to know are:

  • How long do I expect the job to run for?
  • How much memory do I think I need?
  • Do I want e-mail notifications?
  • What modules (or other software) do I need to load?
#!/bin/bash

#SBATCH --nodes 1
#SBATCH --ntasks 1
#SBATCH --cpus-per-task 1
#SBATCH --partition cpu
#SBATCH --mem 8G
#SBATCH --time 12:00:00

#SBATCH --mail-type END,FAIL 
#SBATCH --mail-user ursula.lambda@unil.ch

# Load the required software: e.g.
# module purge
# module load gcc

Array jobs

Here we want to run an array job where there are N almost identical jobs that differ only in the input parameters.

In this example we use 1 CPU per task but you can obviously use more (see the multi-threaded task example)

See our introductory course for more details

The important things to know are:

  • How long do I expect each individual job to run for?
  • How much memory do I think I need per individual job?
  • How many array elements do I have?
  • How am I going to prepare my inputs for the elements?
  • Do I want e-mail notifications?
  • What modules (or other software) do I need to load?
#!/bin/bash

#SBATCH --nodes 1
#SBATCH --ntasks 1
#SBATCH --cpus-per-task 1
#SBATCH --mem 8G
#SBATCH --partition cpu
#SBATCH --time 12:00:00
#SBATCH --array=1-100

#SBATCH --mail-type END,FAIL 
#SBATCH --mail-user ursula.lambda@unil.ch

# Extract the parameters from a file (one line per job array element)

INPUT=$(sed -n ${SLURM_ARRAY_TASK_ID}p in.list)

# Load the required software: e.g.
# module purge
# module load gcc

Multi-threaded tasks

Here we want to use a tool that makes use of more than one CPU at a time.

The important things to know are:

  • How long do I expect the job to run for?
  • How much memory do I think I need?
  • How many cores can the task use efficiently?
  • How do I tell the code how many cores/threads it should use?
  • Do I want e-mail notifications?
  • What modules (or other software) do I need to load?

Note that on the DCSR clusters the variable OMP_NUM_THREADS is set to the same value as cpus-per-task but here we set it explicitly as an example

#!/bin/bash

#SBATCH --nodes 1
#SBATCH --ntasks 1
#SBATCH --cpus-per-task 8
#SBATCH --mem 64G
#SBATCH --partition cpu
#SBATCH --time 12:00:00

#SBATCH --mail-type END,FAIL 
#SBATCH --mail-user ursula.lambda@unil.ch

# Set the number of threads for OpenMP codes

export OMP_NUM_THREADS=$SLURM_CPUS_PER_TASK

# Load the required software: e.g.
# module purge
# module load gcc

MPI tasks

Here we want to use code that uses MPI to allow for distributed memory parallel calculations.

The important things to know are:

  • How mank ranks (MPI tasks) do I want to run?
  • How does my code performance scale as I increase the number of ranks?
  • How much memory do I think I need per rank?
  • How long do I expect the job to run for?
  • Do I want e-mail notifications?
  • What modules (or other software) do I need to load?

Here we give the example of a code that we know runs efficiently with ~100 ranks so we choose 96 as this completely fills two compute nodes.

With MPI tasks always choose a number of tasks that entirely fills nodes: 48 / 96 / 144 / 192 etc - this is where the --ntasks-per-node directive is useful.

As we know that we are using the entire node it makes sense to ask for all the memory even if we don't need it.

#!/bin/bash

#SBATCH --nodes 2
#SBATCH --ntasks-per-node 48 
#SBATCH --cpus-per-task 1
#SBATCH --memory 500G
#SBATCH --partition cpu
#SBATCH --time 12:00:00

#SBATCH --mail-type END,FAIL 
#SBATCH --mail-user ursula.lambda@unil.ch

# Load the required software: e.g.
# module purge
# module load gcc mvapich2

# MPI codes must be launched with srun

srun mycode.x

Hybrid MPI/OpenMP tasks

Here we want to run a hybrid MPI/OpenMP code where each MPI rank uses OpenMP for shared memory parallelisation.

Based on the code and the CPU architecture we know that 12 threads per rank is efficient - always run tests to find the best ratio of threads per rank!

The important things to know are:

  • How mank ranks (MPI tasks) do I want to run?
  • How does my code performance scale as I increase the number of ranks and threads per rank?
  • How much memory do I think I need per rank (taking into account OpenMP?
  • How long do I expect the job to run for?
  • Do I want e-mail notifications?
  • What modules (or other software) do I need to load?
#!/bin/bash

#SBATCH --nodes 2
#SBATCH --ntasks-per-node 4 
#SBATCH --cpus-per-task 12
#SBATCH --memory 500G
#SBATCH --partition cpu
#SBATCH --time 12:00:00

#SBATCH --mail-type END,FAIL 
#SBATCH --mail-user ursula.lambda@unil.ch

# Load the required software: e.g.
# module purge
# module load gcc mvapich2

# Set the number of threads for the OpenMP tasks (12 in this case)

export OMP_NUM_THREADS=$SLURM_CPUS_PER_TASK

# MPI codes must be launched with srun

srun mycode.x

GPU tasks

Here we want to run a code that makes use of one GPU and one CPU core - some codes are able to use multiple GPUs and CPU cores but please check how the performance scales!

The important things to know are:

  • How mank GPUs do I need (1 or 2)
  • How does my code performance scale as I increase the number GPUs?
  • How much memory do I think I need for the CPU part of the job.
  • How long do I expect the job to run for?
  • Do I want e-mail notifications?
  • What modules (or other software) do I need to load?

Note the use of the --gres-flags enforce-binding directive to ensure that the CPU part of the code is on the same bus as the GPU used so as to maximise memory bandwidth.

#!/bin/bash

#SBATCH --nodes 1
#SBATCH --ntasks 1
#SBATCH --cpus-per-task 81
#SBATCH --mem 64G200G
#SBATCH --partition gpu
#SBATCH --time 12:00:00
#SBATCH --gres gpu:1
#SBATCH --gres-flags enforce-binding

#SBATCH --mail-type END,FAIL 
#SBATCH --mail-user ursula.lambda@unil.ch

MPI+GPU tasks

#!/bin/bash

#SBATCH
#SBATCH
#SBATCH
#SBATCH
#SBATCH
#SBATCH
#SBATCH
#SBATCH

#SBATCH --mail-type END,FAIL 
#SBATCH --mail-user ursula.lambda@unil.ch
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