Awesome GitHub RepositoriesShared Memory Management

AISystem is a comprehensive AI full-stack infrastructure project covering the entire pipeline from AI chip architecture to high-level training frameworks. It encompasses the development of AI compiler frameworks, inference engines, and distributed training orchestrators designed to coordinate workloads across a heterogeneous compute stack of CPUs, GPUs, and NPUs. The project focuses on the deep integration of software and hardware, employing software-hardware co-design to align tensor layouts with physical memory structures. It provides specialized capabilities for accelerating Transformer mo

MAME is a vintage hardware emulation platform designed to recreate the circuitry of arcade games, computers, and consoles to run original software on modern devices. It functions as a retro gaming preservation framework for managing, verifying, and archiving ROM sets and disk images to ensure long-term software accessibility. The project features a system debugging tool for inspecting emulated memory, CPU registers, and execution flow via breakpoints and disassembly. It also includes a Lua-based automation layer that exposes core system state and hardware controls for custom behavior and anal

This is an open-source, crowd-sourced wiki textbook that teaches Linux system programming in C. It covers the core operating system concepts of process management through the fork-exec-wait model, dynamic memory allocation using implicit free list heap allocators, inode-based file systems, inter-process communication via pipes and shared memory, POSIX threads with synchronization primitives, signal-based asynchronous notification, virtual memory with page table translation, and runtime diagnostics using Valgrind and GDB. The textbook distinguishes itself by providing practical, implementation

This repository provides a collection of reference implementations, toolkits, and orchestration tools for training and deploying large-scale AI models on Cloud TPU hardware. It serves as a framework for managing the lifecycle of accelerator clusters, including hardware orchestration and the provisioning of high-performance compute infrastructure for machine learning workloads. The project specifically enables the pre-training of foundation models, large language models, and complex reasoning architectures through distributed training toolkits and multi-host scaling recipes. It further provide

Acest proiect este o resursă educațională care oferă un tutorial de dezvoltare cuprinzător pentru scrierea și încărcarea programelor eBPF folosind C, Go și Rust în kernel-ul Linux. Servește drept ghid tehnic pentru dezvoltarea logicii personalizate care să fie executată direct în kernel. Materialele acoperă domenii specializate, inclusiv observabilitatea și trasarea kernel-ului, implementarea securității pentru detectarea intruziunilor și ingineria rețelelor de înaltă performanță pentru filtrarea pachetelor și echilibrarea sarcinii. Include, de asemenea, manuale dedicate pentru trasarea kernel-ului Linux și utilizarea kprobes, uprobes și tracepoints. Proiectul cuprinde o gamă largă de domenii de capabilități, cum ar fi instrumentarea kernel-ului, monitorizarea și observabilitatea sistemului, analiza rețelei și aplicarea securității. Se extinde în continuare la depanarea la nivel hardware pentru GPU-uri și drivere, precum și la manipularea sistemului de nivel scăzut și gestionarea resurselor.