Slurm Batch system usage

This is introduction to T3 Slurm configuration - a modern job scheduler for Linux clusters.

Please use User Interface Nodes t3ui01-03 mostly for development and small quick tests.

For intensive computational work one should use Compute Nodes. There are two types of Compute Nodes in T3 Slurm - Worker Nodes for CPU usage and GPU machines. All new hardware is equipped with 256GB of RAM and 10GbE network:

Access to the Compute Nodes is controlled by Slurm.
Currently Maximum number of CPU jobs each user is allowed to run is 500 (it's about 40% of CPU resources).
There are four partitions implemented. Two for CPU and 2 for GPU usage:

• quick for CPU short jobs; default time is 30 min, max - 1 hour
• wn for CPU longer jobs
• qgpu for short GPU jobs; default time is 30 min, max - 1 hour and 1 GPU/user
• gpu for GPU resources; max 15 GPUs/user

To submit job to the wn partition issue: sbatch -p wn --account=t3 --mem=3000 job.py

One might create a shell script with a set of all directives starting with #SBATCH string like in the following examples.

GPU Example

CPU Example

CPU Example for using multiple processors (threads) on a single physical computer

Here is few useful commands to check Slurm jobs and nodes status and T3 Slurm Monitoring page.

One can check Slurm configuration (information about Nodes and Partitions, etc.) from /etc/slurm/slurm.conf

Slurm itself calculates priorities of jobs taking into account
- Age of Job: the job has been waiting in queue
- FairShare: past of the cluster usage by the user
- Job Size: resources request CPU, Memeory

So that it's useful to declare time resource in submission script (the less required the higher priority) with time option like --time=...