After none of the instructions on how to setup Tensorflow on Ubuntu 22.x worked for me I created the setup below. It is based on some instructions that I had created a few years ago for Ubuntu 18. (https://github.com/OliverMaerz/deep-learning-etc/blob/master/setup-fastai-pytorch-tensorflow-ubuntu-nvidia-gpu.md). So far it works really well for me. Remove Nvidia drivers and stuff If you have already installed some Nvidia drivers, CUDA etc. via then you remove them with: sudo apt –purge remove "*nvidia*" sudo apt –purge remove "*cublas*" "cuda*" "nsight*" sudo apt autoremove If you have them installed via some other method (e.g. download binary/installed) then follow the uninstall instrutions...
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Deploy a Samba (SMB) Fileserver on your K3s/Kubernetes Cluster
So, you have successfully setup your home K3s/Kubernetes cluster. And it is time to deploy some useful applications on the cluster? How about a file server for your home network? Chances are you already have a disk with lots of files that you want to migrate to your K3s cluster. So, in this scenario we will take a USB disk with it contents and attach it to one of the worker nodes (e.g. node ‘raspi3’). We will label this node (e.g. with ‘hdd2’) so the deployment can be configured to only be installed on the node with the external disk....
Continue reading...Setup K3s/Kubernetes Cluster with Ubuntu 20.04 on Raspberry Pi 4s
/## Install K3s Install the server version of Ubuntu on each Raspberry and assign a different hostname to each. In case you local router (wifi router etc.) does not resolve those hostnames add all to the /etc/hosts file on each Raspberry. Update system on all Raspberry Pis sudo apt-get update && sudo apt-get upgrade Install will fail with error "Failed to find memory cgroup, you may need to add "cgroup_memory=1 cgroup_enable=memory" to your linux cmdline (/boot/cmdline.txt on a Raspberry Pi)" if you do not add a line to each Raspberry’s cmdline.txt file and then reboot. So, run: sudo sed -i...
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