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basic-examples

README.md

Basic SLURM Examples for ACCRE

START HERE if you're new to SLURM at ACCRE!

These examples use current ACCRE configuration and best practices. See https://help.accre.vanderbilt.edu/index.php?title=SLURM for more information.

Training Session Quick Start

If you're following along with ACCRE's SLURM training:

# 1. Clone this repo (if you haven't already)
git clone https://github.com/accre/slurm.git
cd slurm/basic-examples/

# 2. Find your account name
slurm_resources

# 3. Edit the interactive debug script
nano 00_interactive_debug.slurm
# Change "your_account_name_int" to your actual account (e.g., mygroup_int)

# 4. Submit your first job!
sbatch 00_interactive_debug.slurm

# 5. Check job status
squeue --me

Debug Examples (For Training & Testing)

These use the debug QoS - jobs start immediately! Use these for training and quick tests.

CPU Debug Job

File: 00_interactive_debug.slurm

Uses interactive partition + debug_int QoS.

# Edit to add your account name with _int suffix
sbatch 00_interactive_debug.slurm

Or run interactively:

srun --pty --partition=interactive --qos=debug_int \
     --account=your_account_int --cpus-per-task=2 --mem=2G --time=0:30:00 bash

GPU Debug Job

File: 00_gpu_debug.slurm

Uses interactive_gpu partition + debug_iacc QoS.

# Edit to add your account name with _iacc suffix
sbatch 00_gpu_debug.slurm

Or run interactively:

srun --pty --partition=interactive_gpu --qos=debug_iacc \
     --account=your_account_iacc --cpus-per-task=2 --mem=2G \
     --gres=gpu:1 --time=0:30:00 bash

Production Examples (For Real Work)

These use the batch partitions - jobs are scheduled based on fair-share.

1. Basic Batch Job (CPU)

File: 01_basic_batch.slurm

Simple CPU job for production work.

sbatch 01_basic_batch.slurm

Use this for: Data processing, statistical analysis, most Python/R workloads

2. GPU Batch Job

File: 02_basic_gpu.slurm

GPU-accelerated job for production work.

sbatch 02_basic_gpu.slurm

Use this for: Machine learning training, molecular dynamics, CUDA applications

Important: Must specify GPU type! Use slurm_resources to see available GPUs.

3. Job Array

File: 03_job_array.slurm

Run many similar jobs with one script.

sbatch 03_job_array.slurm

Use this for: Parameter sweeps, processing multiple files, ensemble runs

Account Suffixes - IMPORTANT!

Different partitions require different account suffixes:

Partition Account Suffix QoS (for debug) Example
batch (none) N/A --account=mygroup
interactive _int debug_int --account=mygroup_int
batch_gpu _acc N/A --account=mygroup_acc
interactive_gpu _iacc debug_iacc --account=mygroup_iacc

Find your accounts with: slurm_resources

Python Examples

  • hello_world.py - Basic test script, shows SLURM environment
  • matrix_multiply.py - CPU benchmark
  • gpu_check.py - GPU availability checker (requires PyTorch/TensorFlow)
  • array_task_example.py - Job array demo with parameter variation

Key ACCRE Requirements

CRITICAL: Software Stack

ALL scripts using modules MUST include setup_accre_software_stack first:

setup_accre_software_stack
module load gcc/12.3 python/3.11.5

Without setup_accre_software_stack, modules will NOT work!

Resource Limits

  • Default time: 30 minutes
  • Max time: 14 days
  • Default memory: 1 GB/core
  • Max memory: 20 GB/core (jobs requesting more get extra cores automatically)

Important: At ACCRE, 1 CPU = 1 PHYSICAL CORE (not threads!)

Getting Help

Last Updated: January 2026