3 dépôts
Downloads and installs GPU drivers, compute stacks, and kernel modules for hardware-accelerated workloads.
Distinct from AMD Hardware Acceleration: Distinct from AMD Hardware Acceleration: focuses on the installation of drivers and kernel modules rather than the acceleration capability itself.
Explore 3 awesome GitHub repositories matching artificial intelligence & ml · Driver and Kernel Module Installations. Refine with filters or upvote what's useful.
This project provides a customized Linux kernel and driver suite designed to enable hardware compatibility for Surface devices. It focuses on building and patching the Linux kernel to provide driver support for proprietary hardware components that are missing from the upstream source. The system includes a secure boot kernel signing mechanism and a process for enrolling custom keys into the system firmware. This allows the execution of patched kernels while maintaining system security protections. The project covers peripheral driver support for touchscreens, styluses, and keyboards, as well
Enables the installation of specialized kernels containing critical drivers and firmware missing from the upstream source.
OpenWrt-Rpi is a firmware builder and embedded Linux build toolset designed to compile custom router operating system images for Raspberry Pi and NanoPi hardware. It utilizes a GitHub Actions CI pipeline to automate the generation of fresh firmware images from the latest source code via daily updates. The project maintains a custom package repository and local software sources for managing community plugins and kernel modules. This infrastructure is used to ensure version consistency and prevent dependency conflicts during the installation of network drivers and system extensions. The build
Maintains a dedicated software source for drivers to ensure version consistency and resolve dependency conflicts.
JimsGarage is a collection of shell scripts and automation tools designed to help individuals deploy and manage a wide range of self-hosted services on their own hardware. It provides a structured approach to setting up containerized applications, from media servers and document management systems to VPNs and monitoring stacks, all through automated Docker-based configurations. The project distinguishes itself by offering a comprehensive library of deployment recipes that cover the full lifecycle of a home server environment. This includes not just the services themselves, but also the suppor
Provides scripts to install AMD GPU drivers, ROCm stack, and kernel modules for GPU-accelerated workloads.