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+# Docker NVIDIA Notes
+[Back to Index ../](../index.md)
+
+## Setting Up Docker Containers for NVIDIA GPUs
+
+To run Docker on NVIDIA GPUs, you need to install the NVIDIA Container Toolkit first.
+Follow the instructions [here](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html).
+
+Once the NVIDIA Container Toolkit has been installed, you can check access to the GPU by running the following image to run the `nvidia-smi` tool:
+
+```bash
+sudo docker run --rm --runtime=nvidia --gpus all ubuntu nvidia-smi
+```
+
+You will get an output similar to this:
+
+```bash
++-----------------------------------------------------------------------------------------+
+| NVIDIA-SMI 590.48.01              Driver Version: 590.48.01      CUDA Version: 13.1     |
++-----------------------------------------+------------------------+----------------------+
+| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
+| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
+|                                         |                        |               MIG M. |
+|=========================================+========================+======================|
+|   0  NVIDIA GeForce RTX 5060        Off |   00000000:01:00.0  On |                  N/A |
+|  0%   46C    P8             12W /  145W |     578MiB /   8151MiB |      0%      Default |
+|                                         |                        |                  N/A |
++-----------------------------------------+------------------------+----------------------+
+
++-----------------------------------------------------------------------------------------+
+| Processes:                                                                              |
+|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |
+|        ID   ID                                                               Usage      |
+|=========================================================================================|
+|  No running processes found                                                             |
++-----------------------------------------------------------------------------------------+
+```
+
+## DockerFile for HAT using NVIDIA SDK
+
+You can use the following `Dockerfile` for building a new docker container:
+
+```dockerfile
+FROM nvidia/cuda:13.0.1-devel-ubuntu24.04
+
+RUN apt-get update -q && apt install -qy \
+        build-essential git cmake vim maven curl bash unzip zip wget
+
+WORKDIR /opt/babylon/
+RUN wget https://download.java.net/java/early_access/jdk26/22/GPL/openjdk-26-ea+22_linux-x64_bin.tar.gz
+RUN tar xvzf openjdk-26-ea+22_linux-x64_bin.tar.gz
+ENV JAVA_HOME=/opt/babylon/jdk-26/
+ENV PATH=$JAVA_HOME/bin:$PATH
+RUN java --version
+
+## Configure Babylon/HAT from source
+RUN git clone https://github.com/openjdk/babylon.git
+WORKDIR /opt/babylon/babylon
+
+RUN apt-get update -y
+RUN apt-get install -y autoconf libfreetype6-dev
+RUN apt-get install -y file
+RUN apt-get install -y libasound2-dev
+RUN apt-get install -y libcups2-dev
+RUN apt-get install -y libfontconfig1-dev
+RUN apt-get install -y libx11-dev libxext-dev libxrender-dev libxrandr-dev libxtst-dev libxt-dev
+
+RUN bash configure --with-boot-jdk=${JAVA_HOME}
+RUN make clean
+RUN make images
+
+# Configure HAT
+WORKDIR /opt/babylon/babylon/hat
+RUN wget https://download.java.net/java/early_access/jextract/22/6/openjdk-22-jextract+6-47_linux-x64_bin.tar.gz
+RUN tar xvzf openjdk-22-jextract+6-47_linux-x64_bin.tar.gz > /dev/null
+ENV PATH=/opt/babylon/babylon/hat/jextract-22/bin:$PATH
+ENV PATH=/opt/babylon/babylon/build/linux-x86_64-server-release/jdk/bin/:$PATH
+ENV JAVA_HOME=/opt/babylon/babylon/build/linux-x86_64-server-release/jdk
+RUN /bin/bash -c "source env.bash"
+
+RUN apt-get install -y maven
+RUN mvn clean package
+
+## Expose a volume to pass files in the local directory
+WORKDIR /opt/babylon/babylon/hat/
+VOLUME ["/data"]
+```
+
+## Build Image
+
+Run the following command in the same directory of the `Dockerfile` with the previous configuration:
+
+```bash
+docker build . -t babylon
+```
+
+## Running Examples on the NVIDIA GPU
+
+Check `nvidia-smi` tool from NVIDIA with the new image, so we have connection to the GPU:
+
+```bash
+docker run -it --rm --runtime=nvidia --gpus all babylon nvidia-smi
+```
+
+All setup! Now you can run HAT on NVIDIA GPUs.
+
+Run matrix-multiply example:
+
+```bash
+docker run -it --rm --runtime=nvidia --gpus all babylon java @.ffi-cuda-examples matmul --size=1024 --kernel=2DREGISTERTILING_FP16
+```
+
+## Enable debug info
+
+```bash
+docker run -it --rm --runtime=nvidia --gpus all babylon java @.ffi-cuda-examples matmul -DHAT=INFO matmul --size=1024 --kernel=2DREGISTERTILING_FP16
+```
+
+Expected output:
+
+```bash
+[INFO] Input Size     : 1024x1024
+[INFO] Check Result:  : false
+[INFO] Num Iterations : 100
+[INFO] NDRangeConfiguration: 2DREGISTER_TILING_FP16
+
+[INFO] Using NVIDIA GPU: NVIDIA GeForce RTX 5060
+[INFO] Dispatching the CUDA kernel
+        \_ BlocksPerGrid   = [16,16,1]
+        \_ ThreadsPerBlock = [16,16,1]
+```