Lumi-supercomputer · marlon-tobaben · Apr 17, 2026 · Apr 17, 2026 · Apr 17, 2026 · Apr 17, 2026
diff --git a/02_Using_the_LUMI_web_interface/Clone_with_JupyterLab.md b/02_Using_the_LUMI_web_interface/Clone_with_JupyterLab.md
diff --git a/02_Using_the_LUMI_web_interface/GPT-neo-IMDB-introduction.ipynb b/02_Using_the_LUMI_web_interface/GPT-neo-IMDB-introduction.ipynb
@@ -39,7 +39,7 @@
    "outputs": [],
    "source": [
     "import os\n",
-    "os.environ[\"HF_HOME\"] = \"/flash/project_465002178/hf-cache\""
+    "os.environ[\"HF_HOME\"] = \"/flash/project_465002757/hf-cache\""
    ]
   },
   {

diff --git a/02_Using_the_LUMI_web_interface/README.md b/02_Using_the_LUMI_web_interface/README.md
@@ -7,28 +7,30 @@
     In this exercise you will gain first experience with using the LUMI web interface to navigate files and directories on the LUMI supercomputer. You will also set up your own copy of the exercise repository on the system, so that you can work on them without interfering with the other course participants.
 
    1. Log in to the LUMI web interface: https://www.lumi.csc.fi
-   2. Create your own subdirectory in `/project/project_465002178/` and `/scratch/project_465002178/`. Use your username for the directory name. You can either
+   2. Create your own subdirectory in `/project/project_465002757/` and `/scratch/project_465002757/`. Use your username for the directory name. You can either
         - Use the built-in file explorer ("Home Directory"), or
         - Use the login node shell app in the webinterface
-   3. Clone the [exercise repository](https://github.com/Lumi-supercomputer/Getting_Started_with_AI_workshop) to your folder in `/project/project_465002178/<username>`. You can either
-        - use the login node shell app in the webinterface, or
-        - start a Jupyter lab job and use the Jupyter lab UI for cloning Git repositories, see [Clone_with_JupyterLab.md](./Clone_with_JupyterLab.md) for an illustrated step-by-step guide for this.
+   3. Clone the [exercise repository](https://github.com/Lumi-supercomputer/Getting_Started_with_AI_workshop) to your folder in `/project/project_465002757/<username>`. You can use the login node shell app in the webinterface for that.
    4. Get familiar with the exercise repository layout.
 
 2. Start an interactive Jupyter lab job and run inference with GPT-neo.
 
     In this exercise you will learn how to reserve resources for and start an interactive job to run a Jupyter notebook via the LUMI web interface. The notebook itself introduces you to our running example of finetuning a language model using PyTorch and the training libraries provided by Huggingface. In this exercise you will not do any training, but familiarise yourself a bit with the software and the base model.
 
     1. Start an interactive Jupyter session: Open the Jupyter app (! not "Jupyter for Courses" !) in the LUMI webinterface and set the following settings before pressing `Launch`
-        - Project: `project_465002178 (LUST Training ...)`
+        - Project: `project_465002757 (LUST Training ...)`
         - Reservation: Use the course reservation `AI_workshop_Day1` (there should only be one available option)
         - Partition: `small-g`
         - Number of CPU cores: `7`
         - Memory (GB): `16`
         - Time: `0:30:00`
         - Working directory: `/project/$PROJECT`
-        - Python: `pytorch (Via CSC stack, limited support available)`
-        - Virtual environment path: leave empty
+        - Press Advanced
+        - Custom Python Type: `Container`
+        - Modules to load: `Local-LAIF lumi-aif-singularity-bindings`
+        - Path to container with Python: `/appl/local/laifs/containers/lumi-multitorch-u24r64f21m43t29-20260319_153422/lumi-multitorch-full-u24r64f21m43t29-20260319_153422.sif`
+        - Container arguments: leave empty
+        - Init script for container: leave empty
     2. Wait for the session to start, then press `Connect to Jupyter`
 
         > **Note**

diff --git a/02_Using_the_LUMI_web_interface/images/step0.png b/02_Using_the_LUMI_web_interface/images/step0.png
diff --git a/02_Using_the_LUMI_web_interface/images/step1.png b/02_Using_the_LUMI_web_interface/images/step1.png
diff --git a/02_Using_the_LUMI_web_interface/images/step2.png b/02_Using_the_LUMI_web_interface/images/step2.png
diff --git a/03_Your_first_AI_training_job_on_LUMI/reference_solution/resume_from_checkpoint/run.sh b/03_Your_first_AI_training_job_on_LUMI/reference_solution/resume_from_checkpoint/run.sh
@@ -1,5 +1,5 @@
 #!/bin/bash
-#SBATCH --account=project_465002178
+#SBATCH --account=project_465002757
 #SBATCH --reservation=AI_workshop_Day1   # comment this out if the reservation is no longer available
 #SBATCH --partition=small-g
 #SBATCH --gpus-per-node=1
@@ -10,14 +10,14 @@
 
 # Set up the software environment
 # NOTE: the loaded module makes relevant filesystem locations available inside the singularity container
-#   (/scratch, /project, etc) as well as mounts some important system libraries that are optimized for LUMI
+#   (/scratch, /project, etc)
 # If you are interested, you can check the exact paths being mounted from
-#   /appl/local/containers/ai-modules/singularity-AI-bindings/24.03.lua
+#   /appl/local/laifs/modules/lumi-aif-singularity-bindings/1.0.0.lua
 module purge
-module use /appl/local/containers/ai-modules
-module load singularity-AI-bindings
+module use /appl/local/laifs/modules
+module load lumi-aif-singularity-bindings
 
-CONTAINER=/appl/local/containers/sif-images/lumi-pytorch-rocm-6.2.4-python-3.12-pytorch-v2.6.0.sif
+CONTAINER=/appl/local/laifs/containers/lumi-multitorch-u24r64f21m43t29-20260319_153422/lumi-multitorch-full-u24r64f21m43t29-20260319_153422.sif
 
 # Some environment variables to set up cache directories
 SCRATCH="/scratch/${SLURM_JOB_ACCOUNT}"
@@ -35,7 +35,7 @@ export OUTPUT_DIR=$SCRATCH/$USER/data/
 export LOGGING_DIR=$SCRATCH/$USER/runs/
 
 set -xv # print the command so that we can verify setting arguments correctly from the logs
-srun singularity exec $CONTAINER \
+srun singularity run $CONTAINER \
     python GPT-neo-IMDB-finetuning.py \
         --model-name gpt-imdb-model \
         --output-path $OUTPUT_DIR \

diff --git a/03_Your_first_AI_training_job_on_LUMI/reference_solution/run.sh b/03_Your_first_AI_training_job_on_LUMI/reference_solution/run.sh
@@ -1,5 +1,5 @@
 #!/bin/bash
-#SBATCH --account=project_465002178
+#SBATCH --account=project_465002757
 #SBATCH --reservation=AI_workshop_Day1   # comment this out if the reservation is no longer available
 #SBATCH --partition=small-g
 #SBATCH --gpus-per-node=1
@@ -10,14 +10,14 @@
 
 # Set up the software environment
 # NOTE: the loaded module makes relevant filesystem locations available inside the singularity container
-#   (/scratch, /project, etc) as well as mounts some important system libraries that are optimized for LUMI
+#   (/scratch, /project, etc)
 # If you are interested, you can check the exact paths being mounted from
-#   /appl/local/containers/ai-modules/singularity-AI-bindings/24.03.lua
+#   /appl/local/laifs/modules/lumi-aif-singularity-bindings/1.0.0.lua
 module purge
-module use /appl/local/containers/ai-modules
-module load singularity-AI-bindings
+module use /appl/local/laifs/modules
+module load lumi-aif-singularity-bindings
 
-CONTAINER=/appl/local/containers/sif-images/lumi-pytorch-rocm-6.2.4-python-3.12-pytorch-v2.6.0.sif
+CONTAINER=/appl/local/laifs/containers/lumi-multitorch-u24r64f21m43t29-20260319_153422/lumi-multitorch-full-u24r64f21m43t29-20260319_153422.sif
 
 # Some environment variables to set up cache directories
 SCRATCH="/scratch/${SLURM_JOB_ACCOUNT}"
@@ -35,7 +35,7 @@ export OUTPUT_DIR=$SCRATCH/$USER/data/
 export LOGGING_DIR=$SCRATCH/$USER/runs/
 
 set -xv # print the command so that we can verify setting arguments correctly from the logs
-srun singularity exec $CONTAINER \
+srun singularity run $CONTAINER \
     python GPT-neo-IMDB-finetuning.py \
         --model-name gpt-imdb-model \
         --output-path $OUTPUT_DIR \

diff --git a/03_Your_first_AI_training_job_on_LUMI/run.sh b/03_Your_first_AI_training_job_on_LUMI/run.sh
@@ -1,19 +1,19 @@
 #!/bin/bash
-#SBATCH --account=project_465002178
+#SBATCH --account=project_465002757
 #SBATCH --reservation=AI_workshop_Day1   # comment this out if the reservation is no longer available
 #SBATCH --partition=...
 ## <!!! ACTION REQUIRED: SPECIFY ADDITIONAL SLURM PARAMETERS HERE!!!>
 
 # Set up the software environment
 # NOTE: the loaded module makes relevant filesystem locations available inside the singularity container
-#   (/scratch, /project, etc) as well as mounts some important system libraries that are optimized for LUMI
+#   (/scratch, /project, etc)
 # If you are interested, you can check the exact paths being mounted from
-#   /appl/local/containers/ai-modules/singularity-AI-bindings/24.03.lua
+#   /appl/local/laifs/modules/lumi-aif-singularity-bindings/1.0.0.lua
 module purge
-module use /appl/local/containers/ai-modules
-module load singularity-AI-bindings
+module use /appl/local/laifs/modules
+module load lumi-aif-singularity-bindings
 
-CONTAINER=/appl/local/containers/sif-images/lumi-pytorch-rocm-6.2.4-python-3.12-pytorch-v2.6.0.sif
+CONTAINER=/appl/local/laifs/containers/lumi-multitorch-u24r64f21m43t29-20260319_153422/lumi-multitorch-full-u24r64f21m43t29-20260319_153422.sif
 
 # Some environment variables to set up cache directories
 SCRATCH="/scratch/${SLURM_JOB_ACCOUNT}"

diff --git a/...ng_to_multiple_GPUs/reference_solution/prints_only_from_single_process/run_no_torchrun.sh b/...ng_to_multiple_GPUs/reference_solution/prints_only_from_single_process/run_no_torchrun.sh
@@ -1,5 +1,5 @@
 #!/bin/bash
-#SBATCH --account=project_465002178
+#SBATCH --account=project_465002757
 #SBATCH --reservation=AI_workshop_Day2   # comment this out if the reservation is no longer available
 #SBATCH --partition=standard-g
 #SBATCH --nodes=1
@@ -11,14 +11,14 @@
 
 # Set up the software environment
 # NOTE: the loaded module makes relevant filesystem locations available inside the singularity container
-#   (/scratch, /project, etc) as well as mounts some important system libraries that are optimized for LUMI
+#   (/scratch, /project, etc)
 # If you are interested, you can check the exact paths being mounted from
-#   /appl/local/containers/ai-modules/singularity-AI-bindings/24.03.lua
+#   /appl/local/laifs/modules/lumi-aif-singularity-bindings/1.0.0.lua
 module purge
-module use /appl/local/containers/ai-modules
-module load singularity-AI-bindings
+module use /appl/local/laifs/modules
+module load lumi-aif-singularity-bindings
 
-CONTAINER=/appl/local/containers/sif-images/lumi-pytorch-rocm-6.2.4-python-3.12-pytorch-v2.6.0.sif
+CONTAINER=/appl/local/laifs/containers/lumi-multitorch-u24r64f21m43t29-20260319_153422/lumi-multitorch-full-u24r64f21m43t29-20260319_153422.sif
 
 # Some environment variables to set up cache directories
 SCRATCH="/scratch/${SLURM_JOB_ACCOUNT}"
@@ -46,7 +46,7 @@ export LOCAL_WORLD_SIZE=$SLURM_GPUS_PER_NODE
 
 # As opposed to the example in `run_torchrun.sh`, we can set the CPU binds directly via the slurm command, since we have
 #  one task per GPU. In this case we do NOT need to set them from within the Python code itself.
-srun singularity exec $CONTAINER \
+srun singularity run $CONTAINER \
     bash -c "RANK=\$SLURM_PROCID \
              LOCAL_RANK=\$SLURM_LOCALID \
              python GPT-neo-IMDB-finetuning.py \

diff --git a/...aling_to_multiple_GPUs/reference_solution/prints_only_from_single_process/run_torchrun.sh b/...aling_to_multiple_GPUs/reference_solution/prints_only_from_single_process/run_torchrun.sh
@@ -1,5 +1,5 @@
 #!/bin/bash
-#SBATCH --account=project_465002178
+#SBATCH --account=project_465002757
 #SBATCH --reservation=AI_workshop_Day2   # comment this out if the reservation is no longer available
 #SBATCH --partition=standard-g
 #SBATCH --nodes=1
@@ -11,14 +11,14 @@
 
 # Set up the software environment
 # NOTE: the loaded module makes relevant filesystem locations available inside the singularity container
-#   (/scratch, /project, etc) as well as mounts some important system libraries that are optimized for LUMI
+#   (/scratch, /project, etc)
 # If you are interested, you can check the exact paths being mounted from
-#   /appl/local/containers/ai-modules/singularity-AI-bindings/24.03.lua
+#   /appl/local/laifs/modules/lumi-aif-singularity-bindings/1.0.0.lua
 module purge
-module use /appl/local/containers/ai-modules
-module load singularity-AI-bindings
+module use /appl/local/laifs/modules
+module load lumi-aif-singularity-bindings
 
-CONTAINER=/appl/local/containers/sif-images/lumi-pytorch-rocm-6.2.4-python-3.12-pytorch-v2.6.0.sif
+CONTAINER=/appl/local/laifs/containers/lumi-multitorch-u24r64f21m43t29-20260319_153422/lumi-multitorch-full-u24r64f21m43t29-20260319_153422.sif
 
 # Some environment variables to set up cache directories
 SCRATCH="/scratch/${SLURM_JOB_ACCOUNT}"
@@ -41,7 +41,7 @@ set -xv # print the command so that we can verify setting arguments correctly fr
 # Since we start only one task with slurm which then starts subprocesses, we cannot use slurm to configure CPU binds.
 # Therefore we need to set them up in the Python code itself.
 
-srun singularity exec $CONTAINER \
+srun singularity run $CONTAINER \
     torchrun --standalone \
              --nnodes=1 \
              --nproc-per-node=${SLURM_GPUS_PER_NODE} \

diff --git a/08_Scaling_to_multiple_GPUs/reference_solution/run_no_torchrun.sh b/08_Scaling_to_multiple_GPUs/reference_solution/run_no_torchrun.sh
@@ -1,5 +1,5 @@
 #!/bin/bash
-#SBATCH --account=project_465002178
+#SBATCH --account=project_465002757
 #SBATCH --reservation=AI_workshop_Day2   # comment this out if the reservation is no longer available
 #SBATCH --partition=standard-g
 #SBATCH --nodes=1
@@ -11,14 +11,14 @@
 
 # Set up the software environment
 # NOTE: the loaded module makes relevant filesystem locations available inside the singularity container
-#   (/scratch, /project, etc) as well as mounts some important system libraries that are optimized for LUMI
+#   (/scratch, /project, etc)
 # If you are interested, you can check the exact paths being mounted from
-#   /appl/local/containers/ai-modules/singularity-AI-bindings/24.03.lua
+#   /appl/local/laifs/modules/lumi-aif-singularity-bindings/1.0.0.lua
 module purge
-module use /appl/local/containers/ai-modules
-module load singularity-AI-bindings
+module use /appl/local/laifs/modules
+module load lumi-aif-singularity-bindings
 
-CONTAINER=/appl/local/containers/sif-images/lumi-pytorch-rocm-6.2.4-python-3.12-pytorch-v2.6.0.sif
+CONTAINER=/appl/local/laifs/containers/lumi-multitorch-u24r64f21m43t29-20260319_153422/lumi-multitorch-full-u24r64f21m43t29-20260319_153422.sif
 
 # Some environment variables to set up cache directories
 SCRATCH="/scratch/${SLURM_JOB_ACCOUNT}"
@@ -46,7 +46,7 @@ export LOCAL_WORLD_SIZE=$SLURM_GPUS_PER_NODE
 
 # As opposed to the example in `run_torchrun.sh`, we can set the CPU binds directly via the slurm command, since we have
 #  one task per GPU. In this case we do NOT need to set them from within the Python code itself.
-srun singularity exec $CONTAINER \
+srun singularity run $CONTAINER \
     bash -c "RANK=\$SLURM_PROCID \
              LOCAL_RANK=\$SLURM_LOCALID \
              python GPT-neo-IMDB-finetuning.py \

diff --git a/08_Scaling_to_multiple_GPUs/reference_solution/run_torchrun.sh b/08_Scaling_to_multiple_GPUs/reference_solution/run_torchrun.sh
@@ -1,5 +1,5 @@
 #!/bin/bash
-#SBATCH --account=project_465002178
+#SBATCH --account=project_465002757
 #SBATCH --reservation=AI_workshop_Day2   # comment this out if the reservation is no longer available
 #SBATCH --partition=standard-g
 #SBATCH --nodes=1
@@ -11,14 +11,14 @@
 
 # Set up the software environment
 # NOTE: the loaded module makes relevant filesystem locations available inside the singularity container
-#   (/scratch, /project, etc) as well as mounts some important system libraries that are optimized for LUMI
+#   (/scratch, /project, etc)
 # If you are interested, you can check the exact paths being mounted from
-#   /appl/local/containers/ai-modules/singularity-AI-bindings/24.03.lua
+#   /appl/local/laifs/modules/lumi-aif-singularity-bindings/1.0.0.lua
 module purge
-module use /appl/local/containers/ai-modules
-module load singularity-AI-bindings
+module use /appl/local/laifs/modules
+module load lumi-aif-singularity-bindings
 
-CONTAINER=/appl/local/containers/sif-images/lumi-pytorch-rocm-6.2.4-python-3.12-pytorch-v2.6.0.sif
+CONTAINER=/appl/local/laifs/containers/lumi-multitorch-u24r64f21m43t29-20260319_153422/lumi-multitorch-full-u24r64f21m43t29-20260319_153422.sif
 
 # Some environment variables to set up cache directories
 SCRATCH="/scratch/${SLURM_JOB_ACCOUNT}"
@@ -41,7 +41,7 @@ set -xv # print the command so that we can verify setting arguments correctly fr
 # Since we start only one task with slurm which then starts subprocesses, we cannot use slurm to configure CPU binds.
 # Therefore we need to set them up in the Python code itself.
 
-srun singularity exec $CONTAINER \
+srun singularity run $CONTAINER \
     torchrun --standalone \
              --nnodes=1 \
              --nproc-per-node=${SLURM_GPUS_PER_NODE} \

diff --git a/08_Scaling_to_multiple_GPUs/reference_solution/with_cpu_bindings/run_no_torchrun.sh b/08_Scaling_to_multiple_GPUs/reference_solution/with_cpu_bindings/run_no_torchrun.sh
@@ -1,5 +1,5 @@
 #!/bin/bash
-#SBATCH --account=project_465002178
+#SBATCH --account=project_465002757
 #SBATCH --reservation=AI_workshop_Day2   # comment this out if the reservation is no longer available
 #SBATCH --partition=standard-g
 #SBATCH --nodes=1
@@ -11,14 +11,14 @@
 
 # Set up the software environment
 # NOTE: the loaded module makes relevant filesystem locations available inside the singularity container
-#   (/scratch, /project, etc) as well as mounts some important system libraries that are optimized for LUMI
+#   (/scratch, /project, etc)
 # If you are interested, you can check the exact paths being mounted from
-#   /appl/local/containers/ai-modules/singularity-AI-bindings/24.03.lua
+#   /appl/local/laifs/modules/lumi-aif-singularity-bindings/1.0.0.lua
 module purge
-module use /appl/local/containers/ai-modules
-module load singularity-AI-bindings
+module use /appl/local/laifs/modules
+module load lumi-aif-singularity-bindings
 
-CONTAINER=/appl/local/containers/sif-images/lumi-pytorch-rocm-6.2.4-python-3.12-pytorch-v2.6.0.sif
+CONTAINER=/appl/local/laifs/containers/lumi-multitorch-u24r64f21m43t29-20260319_153422/lumi-multitorch-full-u24r64f21m43t29-20260319_153422.sif
 
 # Some environment variables to set up cache directories
 SCRATCH="/scratch/${SLURM_JOB_ACCOUNT}"
@@ -52,7 +52,7 @@ CPU_BIND_MASKS="0x00fe000000000000,0xfe00000000000000,0x0000000000fe0000,0x00000
 
 # tell slurm to configure the cpu binds specified by the mask, additional option v prints to configuration to the logs
 srun --cpu-bind=v,mask_cpu=$CPU_BIND_MASKS \
-    singularity exec $CONTAINER \
+    singularity run $CONTAINER \
     bash -c "RANK=\$SLURM_PROCID \
              LOCAL_RANK=\$SLURM_LOCALID \
              python GPT-neo-IMDB-finetuning.py \

diff --git a/08_Scaling_to_multiple_GPUs/reference_solution/with_cpu_bindings/run_torchrun.sh b/08_Scaling_to_multiple_GPUs/reference_solution/with_cpu_bindings/run_torchrun.sh
@@ -1,5 +1,5 @@
 #!/bin/bash
-#SBATCH --account=project_465002178
+#SBATCH --account=project_465002757
 #SBATCH --reservation=AI_workshop_Day2   # comment this out if the reservation is no longer available
 #SBATCH --partition=standard-g
 #SBATCH --nodes=1
@@ -11,14 +11,14 @@
 
 # Set up the software environment
 # NOTE: the loaded module makes relevant filesystem locations available inside the singularity container
-#   (/scratch, /project, etc) as well as mounts some important system libraries that are optimized for LUMI
+#   (/scratch, /project, etc)
 # If you are interested, you can check the exact paths being mounted from
-#   /appl/local/containers/ai-modules/singularity-AI-bindings/24.03.lua
+#   /appl/local/laifs/modules/lumi-aif-singularity-bindings/1.0.0.lua
 module purge
-module use /appl/local/containers/ai-modules
-module load singularity-AI-bindings
+module use /appl/local/laifs/modules
+module load lumi-aif-singularity-bindings
 
-CONTAINER=/appl/local/containers/sif-images/lumi-pytorch-rocm-6.2.4-python-3.12-pytorch-v2.6.0.sif
+CONTAINER=/appl/local/laifs/containers/lumi-multitorch-u24r64f21m43t29-20260319_153422/lumi-multitorch-full-u24r64f21m43t29-20260319_153422.sif
 
 # Some environment variables to set up cache directories
 SCRATCH="/scratch/${SLURM_JOB_ACCOUNT}"
@@ -41,7 +41,7 @@ set -xv # print the command so that we can verify setting arguments correctly fr
 # Since we start only one task with slurm which then starts subprocesses, we cannot use slurm to configure CPU binds.
 # Therefore we need to set them up in the Python code itself.
 
-srun singularity exec $CONTAINER \
+srun singularity run $CONTAINER \
     torchrun --standalone \
              --nnodes=1 \
              --nproc-per-node=${SLURM_GPUS_PER_NODE} \