diff --git a/README.md b/README.md
index dfe3d4d..085f3d5 100644
--- a/README.md
+++ b/README.md
@@ -16,26 +16,6 @@ example command:
 uv run src/train.py --model_name my_model --epochs 50 --batch_size 32
 ```
 
-## HPC Integration
+## HPC
 
-To run training on the VSC HPC (Ghent Tier 2):
-
-### Setup
-
-Run the installation script once on a login node. This sets up a virtual environment in `$VSC_DATA` with the required system modules (JAX, Flax, WandB) and lightweight dependencies.
-
-```bash
-bash scripts/hpc_install.sh
-```
-
-### Smoke Test
-Verify everything runs on a compute node:
-```bash
-python src/train.py --config configs/hpc_smoke_test.yaml
-```
-
-### Submitting Jobs
-Submit long-running experiments via the provided Slurm script:
-```bash
-sbatch scripts/hpc_train.slurm
-```
+See **[docs/HPC.md](docs/HPC.md)** for the full guide, including environment setup, cluster selection, interactive debugging, and job submission.
diff --git a/docs/HPC.md b/docs/HPC.md
new file mode 100644
index 0000000..89d49bf
--- /dev/null
+++ b/docs/HPC.md
@@ -0,0 +1,129 @@
+# HPC Guide (Ghent University Tier-2)
+
+Full documentation: <https://docs.hpc.ugent.be/>
+
+## Cluster Selection
+
+Choose the appropriate cluster before submitting a job with `module swap cluster/<name>`. The default login cluster is **doduo**.
+
+| Cluster   | Type                    | Use case                                      |
+|-----------|-------------------------|-----------------------------------------------|
+| `donphan` | Interactive / debug GPU | First-time setup, interactive debugging       |
+| `doduo`   | CPU (default login)     | Rapid iteration, CPU-only smoke tests         |
+| `joltik`  | GPU (A100 ¼-slice)      | Standard training runs                        |
+| `accelgor`| GPU (A100 full)         | Large-scale / long experiments                |
+| `litleo`  | GPU                     | Alternative GPU option                        |
+
+> **Rule:** use at most **1 GPU per group at a time** on shared GPU clusters.  
+> Check the current queue load at <https://shieldon.ugent.be:8083/pbsmon-web-users/>.
+
+---
+
+## Initial Environment Setup
+
+Run **once** from a login node after cloning the repository:
+
+```bash
+# 1. Connect via the web portal → HPC Login → Interactive Apps > Shell (tmux)
+#    Set cluster to "donphan (interactive/debug)"
+
+# 2. Clone the project (if not done yet)
+git clone <repo-url>
+cd 2026SEL3-project-BrittleStar
+
+# 3. Run the install script
+bash scripts/hpc/install.sh
+```
+
+This uses the official [`vsc-venv`](https://docs.hpc.ugent.be/Linux/setting_up_python_virtual_environments/#vsc-venv-python-virtual-environment-wrapper-script) wrapper to:
+- Load the EasyBuild modules listed in `env/hpc/modules.txt` (JAX, Flax, WandB, …)
+- Create a per-cluster virtual environment in `$VSC_DATA`
+- Pip-install the remaining packages from `env/hpc/requirements.txt`
+- Register a Jupyter kernel named `sel3_<cluster>`
+
+> **Note:** virtual environments are cluster-specific. Re-run the script if you switch to a new cluster.
+
+---
+
+## Interactive Debugging on donphan
+
+The `donphan` cluster provides quick access to a fractional A100 GPU and is ideal for verifying your environment end-to-end before submitting batch jobs.
+
+### Option A — Interactive shell session
+
+```bash
+# Swap to the debug cluster (from the login node)
+module swap cluster/donphan
+
+# Request an interactive job (1 node, 4 cores)
+qsub -I -l nodes=1:ppn=4 -l walltime=1:00:00
+
+# Once inside the job, activate your environment
+cd "$PBS_O_WORKDIR"   # or cd to your project root if not set
+module load vsc-venv
+source vsc-venv --activate --modules env/hpc/modules.txt
+
+# Run the smoke test
+export MUJOCO_GL=egl
+python src/train.py --config configs/hpc_smoke_test.yaml
+```
+
+### Option B — JupyterLab session (HPC web portal)
+
+1. In the web portal go to **Interactive Apps → JupyterLab RHEL9**
+2. Set the following options:
+
+   | Option              | Value                           |
+   |---------------------|---------------------------------|
+   | Cluster             | `donphan (interactive/debug)`   |
+   | Number of nodes     | 1                               |
+   | Number of cores     | 4                               |
+   | JupyterLab version  | `4.2.5 GCCcore-13.3.0`          |
+   | Custom code         | *(leave blank — vsc-venv handles modules)* |
+
+3. Click **Launch**, wait for the session to start, then **Connect**.
+4. In JupyterLab, select the kernel **`SEL3 (<cluster>)`**.
+5. Verify GPU access:
+
+   ```python
+   import jax
+   print(jax.default_backend())  # expected: 'gpu'
+   print(jax.devices())          # expected: [CudaDevice(id=0)]
+   ```
+
+> **Warning:** JAX can only be loaded by one kernel at a time. Shut down other kernels before switching notebooks.
+
+---
+
+## Submitting Batch Training Jobs
+
+```bash
+# Default cluster (joltik — one A100 GPU slice)
+qsub scripts/hpc/train.pbs
+
+# Switch to a different GPU cluster first
+module swap cluster/accelgor
+qsub scripts/hpc/train.pbs
+```
+
+Monitor your jobs:
+
+```bash
+qstat          # list your jobs
+qstat -f <id>  # detailed info for a specific job
+qdel <id>      # cancel a job
+```
+
+Logs are written to `runs/pbs_<jobid>.out` and `runs/pbs_<jobid>.err`.
+
+---
+
+## Managing Dependencies
+
+`env/hpc/requirements.txt` is the **source of truth** for pip packages on the HPC. It is automatically regenerated by CI whenever `pyproject.toml` changes. To regenerate locally:
+
+```bash
+uv run scripts/export_hpc_requirements.py
+```
+
+Do **not** edit `env/hpc/requirements.txt` by hand — edit `pyproject.toml` instead.