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)
| pixi-activate() { | |
| local name="$1" | |
| local base="$HOME/pixi-envs" | |
| local env="$base/$name" | |
| if [[ -d "$env" && -f "$env/pixi.toml" ]]; then | |
| eval "$(pixi shell-hook --manifest-path $env)" | |
| else | |
| echo "No pixi environment named '$name' found in $base" | |
| return 1 | |
| fi |
| 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 |
| 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 |
| # 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' |
| """ | |
| 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 |
| 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 |
| 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 |
| # 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 |