This guide will walk you through a factory reset and initial config as well as upgrade from OS8 to OS9 on the Dell Force10 S4810 switch

Step-by-Step Guide to install Nvidia Drivers, Nvidia CUDA Toolkit, & Container Toolkit on Red Hat Enterprise Linux 9

In this post we will walk through the process of upgrading the IOS image on a Cisco Catalyst WS-C4500X switch

Need to reset your Cisco Catalyst 4500X  back to the factory default settings. Follow this quick and easy guide

In this post we will install and configure dnsmasq with a webUI frontend to simplify manaing dns management

I recently got my hands on a couple of gigabyte servers. These machines came preinstalled with Ubuntu 20.04. Credentials for a OS local user account were on a sticker on the machines. However there was no indication of what the BMC credentials were. According to this document, there should be default credentials that we can … <a href="" class="more-link">Continue reading <span class="screen-reader-text"></span></a>

Prerequisites I have already installed Nvidia proprietary drivers and the Nvidia Cuda Toolkit. I documented the install of the Cuda toolkit in an older post which can be found here. Since I have Nvidia GPUs in my host system, and I intend to run some services in containers, I want to make sure that I … <a href="" class="more-link">Continue reading <span class="screen-reader-text"></span></a>

This guide details the installation process for Instructlab + VLLM on Ubuntu 22.04 with an Nvidia CUDA Support.

First determine what driver is installed. Below we can see that we are running the “nouveau” driver and not the Nvidia proprietary driver. Add rpm fusion repos. Dnf update. Install kernel-devel which provides kernel headers and makefiles required to build kernel modules. Install akmod-nividia, which checks if there are any missing kernel mods at boot … <a href="" class="more-link">Continue reading <span class="screen-reader-text"></span></a>

The NVIDIA CUDA Toolkit is essential for developing GPU-accelerated applications and includes various tools. Users must uninstall older versions from Ubuntu before installing the latest toolkit from NVIDIA’s website for better performance and compatibility. The summary highlights differences between installation methods regarding version availability, ease, and update management.

“The NVIDIA CUDA Toolkit is a software development kit that helps users create GPU-accelerated applications. It includes libraries, compilers, debuggers, and optimization tools”. Since we have an Nvidia GPU we will install it as shown below. Note: If you installed the nvidia-cuda-toolkit from default ubuntu noble repo, uninstall it first as that version is probably too old. … <a href="" class="more-link">Continue reading <span class="screen-reader-text"></span></a>

Introduction to RamaLama RamaLama is an open-source project developed to simplify AI model deployment and management using OCI (Open Container Initiative) containers. Ramalama enables seamless execution of AI workloads across different hardware configurations, supporting both GPU-accelerated and CPU-based environments. By leveraging container engines like Podman and Docker, RamaLama includes all necessary dependencies, eliminating complex installation … <a href="" class="more-link">Continue reading <span class="screen-reader-text"></span></a>