Awesome GitHub RepositoriesKernel Process Internals

xv6 is a Unix-like educational operating system designed for teaching kernel concepts. It is implemented as an instructional kernel for x86 and RISC-V architectures, featuring a virtual memory manager and support for symmetric multiprocessing. The system is designed to demonstrate core OS principles through a simplified re-implementation of Unix Version 6. It provides a controlled environment for studying system calls, trap handling, and process lifecycles. Its capability surface covers process management, including scheduling and context switching, and memory management via page tables for

CppGuide is a curated collection of educational resources and practical guides focused on C++ server development, Linux kernel internals, concurrent programming, network protocols, and security exploitation. It provides structured learning paths for backend developers, covering everything from interview preparation to building high-performance network servers and understanding operating system fundamentals. The guide distinguishes itself by offering in-depth, hands-on tutorials that walk through real-world implementations, including building a Redis-like server from scratch, designing custom

This is a collection of academic programming projects that accompany an operating systems textbook, designed to teach core OS concepts through hands-on implementation. The projects span the major subsystems of an operating system, including process scheduling, memory management, file systems, and concurrency, with students building components from scratch in a simulated environment. The projects are structured to cover the full range of OS internals, from low-level kernel development to user-space system programming. Students implement lottery-based CPU schedulers, dynamic heap memory allocat

TileLang is a Python-embedded domain-specific language compiler that JIT-compiles and autotunes GPU kernels. It uses a tile-based DSL, automatic software pipelining, and parallel autotuning to generate optimized GPU kernels at runtime. It supports tensor core operations with Pythonic syntax, automatic memory management, and thread mapping. The compiler searches over tile sizes, thread counts, and scheduling policies, compiling and benchmarking candidates in parallel to find the fastest kernel. It also caches compiled binaries and tuning results to disk for reuse across sessions. TileLang inc

This project is an educational framework and toolkit designed for developing and testing operating system kernels. It provides a structured environment for implementing fundamental system primitives, including virtual memory management, preemptive process scheduling, and filesystem organization, using Rust and C. The framework is specifically oriented toward RISC-V and x86 architectures, serving as a laboratory for learning how to build core system software from the ground up. The project distinguishes itself by supporting both bare-metal deployment and hardware emulation, allowing developers

This project is an educational operating system kernel designed to demonstrate the fundamental architectural principles of memory paging and process management. It is implemented as a minimal kernel that serves as a practical reference for building a functioning system from the ground up. The implementation features a preemptive multitasking kernel that switches execution contexts between threads to share a single CPU. It includes an x86 virtual memory manager that uses paging to map virtual addresses to physical memory and isolate processes. The system covers low-level hardware interfacing