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Running ollama on Pelle

Summary

  • Ollama needs to be installed in the project folder.
  • The location of the ollama models needs to be redirected in to a folder within the project export OLLAMA_MODELS=/proj/naiss-XXXXX/....
  • ollama serve must run on an allocated GPU or CPU node.
  • Interaction with your ollama serve could be done
    • on the allocated node itself
    • on the login node
    • on your own computer
  • Running non-interactive tasks

User installation of ollama

  1. Login to Pelle and select a folder under your project allocation 
    ssh userid@pelle.uppmax.uu.se
...
cd /proj/naiss-XXXXX/userid/nobackup

  2. Download ollama 

    wget https://ollama.com/download/ollama-linux-amd64.tar.zst

  3. Make folder where you will unpack 

    mkdir ollama && cd ollama
tar -xvf ../ollama-linux-amd64.tar.zst
    Your ollama binary is in /proj/naiss-XXXXX/userid/nobackup/bin/ollama

Running ollama on a compute node

  1. Start interactive node with GPU https://docs.uppmax.uu.se/cluster_guides/slurm_on_pelle/ 

    interactive -A nais-XXXXX -p gpu -t 1:00:00 --gpus=l40s:1

# or on the old haswell nodes
interactive -A naiss-XXXXX -p haswell -c 16 -t 1:00:00 --gpus=t4:1

    # exampe output from running the last command
salloc: Pending job allocation 4068884
salloc: job 4068884 queued and waiting for resources
salloc: job 4068884 has been allocated resources
salloc: Granted job allocation 4068884
salloc: Waiting for resource configuration
salloc: Nodes p2033 are ready for job
    Take a note of the JOBID 4068884 and the node address: p2033

  2. Start ollama serve in the interactive session 

    export OLLAMA_MODELS=/proj/nais-XXXXXX/user/nobackup/ollama_models
mkdir -p $OLLAMA_MODELS

# start ollama serve
unset CUDA_VISIBLE_DEVICES
/proj/naiss-XXXXXX/userid/nobackup/ollama/bin/ollama serve
  3. Look at the end that ollama dicovered the GPU 
    ...
time=2026-03-20T07:58:02.030+01:00 level=INFO source=types.go:42 msg="inference compute" id=GPU-92ada8a8-9cda-effe-830e-0bdfcd3e0a96 filter_id="" library=CUDA compute=7.5 name=CUDA0 description="Tesla T4" libdirs=ollama,cuda_v13 driver=13.1 pci_id=0000:81:00.0 type=discrete total="15.0 GiB" available="14.6 GiB"
time=2026-03-20T07:58:02.030+01:00 level=INFO source=routes.go:1832 msg="vram-based default context" total_vram="15.0 GiB" default_num_ctx=4096
  4. Find the JOBID of the reservation if you lost track 
    # Check the JOBID
squeue --me
             JOBID PARTITION     NAME     USER ST       TIME  NODES NODELIST(REASON)
           4068884   haswell interact   pmitev  R       0:06      1 p2034
  5. Get additional shell in the same allocation 
    srun --x11 --pty --overlap --jobid 4068884 bash
    This will start bash shell in the same job reservation.
  6. Test that you can communicate with the ollama service 
    /proj/naiss-XXXXXX/userid/nobackup/ollama/bin/ollama list
NAME                      ID              SIZE      MODIFIED     
qwen2.5-coder:14b         9ec8897f747e    9.0 GB    23 hours ago
gemma3:latest             a2af6cc3eb7f    3.3 GB    36 hours ago
mistral:latest            6577803aa9a0    4.4 GB    37 hours ago
llama3.2-vision:latest    6f2f9757ae97    7.8 GB    37 hours ago
llama4:latest             bf31604e25c2    67 GB     39 hours ago
llama3.2:latest           a80c4f17acd5    2.0 GB    39 hours ago
llama4:scout              bf31604e25c2    67 GB     40 hours ago

Expose ollama serve to Pelle login node or personal computer.

Warning: This approach exposes the ollama instance to everyone on Pelle - Use with caution.

  1. Start interactive node with GPU as before https://docs.uppmax.uu.se/cluster_guides/slurm_on_pelle/ 

    interactive -A nais-XXXXX -p gpu -t 1:00:00 --gpus=l40s:1

# or on the old haswell nodes
interactive -A naiss-XXXXX -p haswell -c 16 -t 1:00:00 --gpus=t4:1

  2. On the node start ollama serve with additional export OLLAMA_HOST=0.0.0.0 

    export OLLAMA_HOST=0.0.0.0
export OLLAMA_MODELS=/proj/nais-XXXXXX/user/nobackup/ollama_models
mkdir -p $OLLAMA_MODELS

# start ollama serve
unset CUDA_VISIBLE_DEVICES
/proj/naiss-XXXXXX/userid/nobackup/ollama/bin/ollama serve

  3. On the login node you can, check on which node you got allocation 

    squeue --me
             JOBID PARTITION     NAME     USER ST       TIME  NODES NODELIST(REASON)
           4068884   haswell interact   pmitev  R       0:06      1 p2034
  4. Run ollama client on Pelle login node 
    export OLLAMA_HOST=p2034 
# start ollama client
/proj/naiss-XXXXXX/userid/nobackup/ollama/bin/ollama

# check models 
/proj/naiss-XXXXXX/userid/nobackup/ollama/bin/ollama list
  5. Run on personal computer with ollama serve running on Pelle GPU node To expose ollama serve to you personal computer run in a shell 
    ssh -L 21434:p2034:11434 userid@pelle.uppmax.uu.se
    Note that in the example above we select port 21434 on the local computer, to avoid potential conflict with local ollama installations running on your computer. Make sure you change p2034 to the node with your ollama serve. On your computer, make sure you connect to localhost:21434 when running ollama. 
    export OLLAMA_HOST=localhost:21434
ollama list

    NAME                      ID              SIZE      MODIFIED     
qwen2.5-coder:14b         9ec8897f747e    9.0 GB    23 hours ago
gemma3:latest             a2af6cc3eb7f    3.3 GB    36 hours ago
mistral:latest            6577803aa9a0    4.4 GB    37 hours ago
llama3.2-vision:latest    6f2f9757ae97    7.8 GB    37 hours ago
llama4:latest             bf31604e25c2    67 GB     39 hours ago
llama3.2:latest           a80c4f17acd5    2.0 GB    39 hours ago
llama4:scout              bf31604e25c2    67 GB     40 hours ago

Running non-interactive jobs

Example sbatch submit.sh template

#!/bin/bash -l 
#SBATCH -A naiss-XXXX 
#SBATCH -p gpu --gpus=l40s:1
#SBATCH -t 10:00:00

# Get the first free port within a range
OPORT=$(comm -23 <(seq 21434 21444 | sort) <(ss -tan | awk '{print $4}' | cut -d':' -f2 | sort -u) | head -n 1)
export OLLAMA_HOST=localhost:$OPORT

# start the service
export OLLAMA_MODELS=/proj/nais-XXXXXX/user/nobackup/ollama_models
ollama serve &

# Wait a bit for the service to be ready
sleep 5

# Run! 
ollama list 
# or your python program
source venv/activate.sh
python myprogram.py
Submit the job. 
sbatch submit.sh