# Pytorch Benchmark ## 1. Install Docker ```bash sudo apt install curl ``` ## Uninstall docker ```bash sudo apt-get remove docker docker-engine docker.io containerd runc ``` ```bash # Add Docker's official GPG key: sudo apt-get update sudo apt-get install ca-certificates curl sudo install -m 0755 -d /etc/apt/keyrings sudo curl -fsSL https://download.docker.com/linux/ubuntu/gpg -o /etc/apt/keyrings/docker.asc sudo chmod a+r /etc/apt/keyrings/docker.asc # Add the repository to Apt sources: echo \ "deb [arch=$(dpkg --print-architecture) signed-by=/etc/apt/keyrings/docker.asc] https://download.docker.com/linux/ubuntu \ $(. /etc/os-release && echo "$VERSION_CODENAME") stable" | \ sudo tee /etc/apt/sources.list.d/docker.list > /dev/null sudo apt-get update sudo apt-get install docker-ce docker-ce-cli containerd.io docker-buildx-plugin docker-compose-plugin ``` ```bash curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg \ && curl -s -L https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list | \ sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | \ sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list \ && \ sudo apt-get update sudo apt-get install -y nvidia-container-toolkit ``` ```bash sudo nvidia-ctk runtime configure --runtime=docker sudo systemctl restart docker sudo nvidia-ctk runtime configure --runtime=containerd sudo systemctl restart containerd sudo nvidia-ctk runtime configure --runtime=crio sudo systemctl restart crio sudo systemctl enable docker.service sudo systemctl enable containerd.service ``` ```bash sudo docker run --rm --runtime=nvidia --gpus all nvidia/cuda:11.6.2-base-ubuntu20.04 nvidia-smi ``` ### Add permission user ```bash sudo chmod 666 /var/run/docker.sock sudo groupadd docker sudo usermod -aG docker $USER newgrp docker ``` ### Modify to compile dockers with Nvidia If you're going to be building containers, you need to set Docker's default-runtime to nvidia, so that the NVCC compiler and GPU are available during docker build operations. Add "default-runtime": "nvidia" to your /etc/docker/daemon.json configuration file before attempting to build the containers: ```bash { "runtimes": { "nvidia": { "path": "nvidia-container-runtime", "runtimeArgs": [] } }, "default-runtime": "nvidia" } ``` ## 1.2. Check with nvidia-smi ```bash docker run --rm --runtime=nvidia --gpus all nvidia/cuda:11.6.2-base-ubuntu20.04 nvidia-smi ``` ## 2. Run Pytorch benchmark ```bash mkdir Projects cd Projects git clone https://github.com/johnnynunez/pytorch_benchmark.git cd pytorch_benchmark ``` ### 2.1 Run ```bash chmod +x run_benchmark.sh bash run_benchmark.sh ```
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