2 repository-uri
Awesome GitHub RepositoriesKernel Resource Orchestrators
System-level orchestrators that manage hardware resources like GPU memory and CPU cores for isolated execution environments.
Distinct from Resource Orchestrators: None of the candidates capture the specific role of an OS-like kernel managing AI-specific hardware resources for agents.
Explore 2 awesome GitHub repositories matching operating systems & systems programming · Kernel Resource Orchestrators. Refine with filters or upvote what's useful.
Awesome Kernel Resource Orchestrators GitHub Repositories
Găsește cele mai bune repo-uri cu AI.Vom căuta cele mai potrivite repository-uri folosind AI.
- agiresearch/aios
agiresearch/AIOS
5,168Vezi pe GitHubAIOS is an LLM agent operating system and orchestration kernel designed to manage memory, resource scheduling, and tool execution for multiple autonomous AI agents. It serves as a comprehensive framework for developing and deploying agents, featuring a dedicated resource manager that coordinates model backends, GPU memory, and isolated kernel instances. The system distinguishes itself through a semantic memory engine that uses vector search and autonomous clustering for long-term knowledge management, and a semantic file system that allows users to control computer files and system operations
Coordinates model cores, memory, and storage through an abstraction layer to manage agent execution and lifecycle.
Python - zodiacon/windowsinternals
zodiacon/WindowsInternals
2,682Vezi pe GitHubWindowsInternals is a CPU stress testing tool and a research project designed to illustrate the underlying mechanisms of the Windows kernel and system architecture. It functions as an educational resource for studying how the Windows operating system manages internal processes and hardware resources. The project focuses on Windows OS research and system resource profiling. It provides a collection of source code and examples used to reveal the internal workings of the operating system and monitor how it handles high processing demands to identify stability issues and performance bottlenecks.
Manages CPU cores and system threads to simulate hardware resource contention.
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