OMNI Cluster Job Submission Guide
Queue Information
| Settings | Queue Type | |||
|---|---|---|---|---|
| Short | Medium | Long | CAI | |
| Default Time Limit | 2 hr | 6 hr | 1 day | 1 day |
| Maximum Time Limit | 6 hr | 1 day | 3 days | 3 days |
| Max Job Submit per Group | 3 | 2 | 1 | 1 |
| Storage quota | 5 TB per Group | |||
| Max. CPU Cores | 10 | 16 | 20 | 32 |
| No. of available GPUs per job | 1 | 1 | 1 | 2 |
| Max. available RAM per job | 64 GB | 256 GB | 512 GB | 512 GB |
| Token Cost | 0.1 per job | 0.5 per job | 1 per job | 0.5 per job |
| Queue | Description |
|---|---|
| Short | MIG-enabled (8x 2= 16 GPUs @ 70 GB each) GPUs (DGX H200) |
| Medium | Dedicated GPUs (B200 =8 GPUs @ 180GB , hgxh200=8 GPUs @144 GB ) |
| Long | Dedicated GPUs (B2002= 8 GPUs @192 GB) |
| CAI | Dedicated GPUs (dgxA100= 8 GPUs @40 GB) - Currently Down |
1. Short Queue
srun -A GroupName -p short -q short --ntasks=1 --gres=gpu:3g.71gb:1 --mem=64G --pty nvidia-smi
2. Medium Queue
srun -A GroupName -p medium -q medium --ntasks=1 --gres=gpu:1 --nodelist=hgxh200 --mem=60G --pty nvidia-smi
srun -A GroupName -p medium -q medium --ntasks=1 --gres=gpu:1 --nodelist=B2001 --mem=60G --pty nvidia-smi
3. Long Queue
srun -A GroupName -p long -q long --gres=gpu:1 --nodelist=B2002 --mem=60G --pty nvidia-smi
4. CAI Queue
Only valid for CAI Faculty Member Groups.
srun -A GroupName -p cai -q cai --gres=gpu:1 --nodelist=dgxA100 --mem=60G --pty bash
Job script
#!/bin/bash #SBATCH --time=06:00:00 #SBATCH --job-name=Any_name #SBATCH --account=GroupName #SBATCH --partition=short #SBATCH --qos=short #SBATCH --ntasks=1 #SBATCH --gres=gpu:3g.71gb:1 #SBATCH --mem=64G nvidia-smi > nvidialog.txt
Save the script as jobscript.slurm and submit using:
sbatch jobscript.slurm
Transparency
GPU allocation, utilization and ownership are visible to all users. Only resource usage information is public. Your source code and data remain private.
Prohibited Activities
- Bypassing the GPU quota system.
- Obtaining unauthorized administrative privileges.
- Cryptocurrency mining.
- Commercial or non-academic workloads.
- Keeping GPUs idle intentionally.
- Sharing login credentials.
- Illegal or prohibited activities.
Monitoring and Enforcement
GPU jobs are logged, monitored and audited. Misuse may result in reduced quota, temporary suspension or permanent loss of access.
Support and Exceptions
- Additional GPU hours may be requested with Faculty approval.
- User tiers are managed by administrators.
- Contact: helpdesk@iiitd.ac.in
Agreement
By using the GPU Server you agree to comply with this policy.
By using the GPU Server you agree to comply with this policy.