key_word: reinforcement learning; query: Wafer Characterization review; filter_keys: wafer Characterization; language: cn;
- Title: Epitaxial Growth of 2D Layered Transition Metal Dichalcogenides(二维分层过渡金属二硫化物的外延生长)
# Get Airflow Docker Compose file | |
curl -LfO 'https://airflow.apache.org/docs/apache-airflow/2.2.3/docker-compose.yaml' | |
# Initialize the Airflow Database | |
docker-compose up airflow-init | |
# Run Airflow | |
docker-compose up | |
# Ensure that all services are running | |
docker ps | |
# Access the web interface | |
# Login:airflow,Password:airflow |
channels: | |
- https://public.dhe.ibm.com/ibmdl/export/pub/software/server/ibm-ai/conda-early-access/linux-ppc64le/ | |
- rocketce | |
- nvidia | |
- pytorch | |
- powerai | |
- conda-forge | |
- anaconda |
conda config --prepend channels https://public.dhe.ibm.com/ibmdl/export/pub/software/server/ibm-ai/conda-early-access/ -y | |
conda create -n ibm-ai -y | |
# conda activate ibm-ai -y | |
conda install -n base mamba -c conda-forge -y | |
mamba install pytorch torchvision cudatoolkit -c https://public.dhe.ibm.com/ibmdl/export/pub/software/server/ibm-ai/conda-early-access/ -y | |
mamba install opencv -y | |
export IBM_POWERAI_LICENSE_ACCEPT=yes | |
conda install powerai -y |
""" | |
Ubuntu 22 for arm | |
ubuntu 20 OSCN for PCC | |
ubuntu 20 for x86-64 | |
Instructions: | |
## brief | |
This profile creates a single node with/without latest cuda and conda installation | |
anaconda will use install version on date of 2023-01 |
# ssh -J lz@Jumpper lz@10.10.10.3 -vvv | |
OpenSSH_9.0p1, LibreSSL 3.3.6 | |
debug1: Reading configuration data /Users/lz/.ssh/config | |
debug1: /Users/lz/.ssh/config line 30: Applying options for * | |
debug1: Reading configuration data /etc/ssh/ssh_config | |
debug1: /etc/ssh/ssh_config line 21: include /etc/ssh/ssh_config.d/* matched no files | |
debug1: /etc/ssh/ssh_config line 54: Applying options for * | |
debug2: resolve_canonicalize: hostname 10.10.10.3 is address | |
debug1: Setting implicit ProxyCommand from ProxyJump: ssh -l lz -vvv -W '[%h]:%p' Jumpper | |
debug3: expanded UserKnownHostsFile '~/.ssh/known_hosts' -> '/Users/lz/.ssh/known_hosts' |
curl -L https://gist.githubusercontent.com/HernandoR/f1d2f0be041c99bf0f7c1d0a53ac1ada/raw/install-temianl-app.sh | |
curl -L https://gist.githubusercontent.com/HernandoR/f1d2f0be041c99bf0f7c1d0a53ac1ada/raw/install-desktop-app.sh | |
source ./install-temianl-app.sh | |
source ./install-desktop-app.sh | |
# Call the functions | |
detect_os | |
install_git | |
install_homebrew | |
install_build_essential |
curl -s -L https://nvidia.github.io/libnvidia-container/stable/rpm/nvidia-container-toolkit.repo | sudo tee /etc/yum.repos.d/nvidia-container-toolkit.repo | |
sudo yum install -y nvidia-container-toolkit | |
sudo nvidia-ctk cdi generate --output=/etc/cdi/nvidia.yaml | |
nvidia-ctk cdi list | |
sudo nvidia-ctk runtime configure --runtime=docker | |
# podman example | |
# podman run --rm --device nvidia.com/gpu=all --security-opt=label=disable ubuntu nvidia-smi -L | |
# docker example | |
# docker run --rm -ti --runtime=nvidia -e NVIDIA_VISIBLE_DEVICES=nvidia.com/gpu=all ubuntu nvidia-smi -L |