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6 个仓库

Awesome GitHub RepositoriesGPU Workload Virtualization and Containerization

Manages hardware resources with a hypervisor and runs guest OSes or Docker containers for isolation and scalability.

Distinct from GPU Resource Virtualization: Distinct from GPU Resource Virtualization: combines virtualization with containerization for GPU workloads.

Explore 6 awesome GitHub repositories matching operating systems & systems programming · GPU Workload Virtualization and Containerization. Refine with filters or upvote what's useful.

Awesome GPU Workload Virtualization and Containerization GitHub Repositories

用 AI 发现最棒的仓库。我们将通过 AI 为您搜索最匹配的仓库。
  • loft-sh/vclusterloft-sh 的头像

    loft-sh/vcluster

    11,186在 GitHub 上查看↗

    vcluster is a Kubernetes virtual cluster platform that creates fully isolated Kubernetes environments with dedicated control planes, API servers, and RBAC on shared physical infrastructure. It virtualizes Kubernetes control planes by running them as pods inside a host cluster, as standalone binaries on bare metal or virtual machines, or within Docker containers, providing each tenant their own isolated Kubernetes environment without the overhead of managing separate physical clusters. The platform enables multi-tenant Kubernetes isolation through multiple tenancy models, from shared node pool

    Provides secure kernel-level isolation for workloads using seccomp, cgroups, and namespaces.

    Gocloud-nativehelmk3s
    在 GitHub 上查看↗11,186
  • wasmedge/wasmedgeWasmEdge 的头像

    WasmEdge/WasmEdge

    10,665在 GitHub 上查看↗

    WasmEdge is an extensible WebAssembly runtime that executes WebAssembly bytecode in a secure sandbox for cloud, edge, and embedded applications. It functions as a multi-language compiler, compiling applications written in Rust, JavaScript, Go, and Python into WebAssembly bytecode for sandboxed execution, and as a server-side JavaScript runtime that runs JavaScript programs with ES6 modules, NPM packages, and Node.js-compatible APIs. The runtime also serves as an AI inference runtime, executing AI models from JavaScript using WASI-NN plug-ins for inference tasks on personal devices and edge har

    Orchestrates large language model inference tasks on GPU hardware within a Kubernetes cluster.

    C++artificial-intelligencecloudcloud-native
    在 GitHub 上查看↗10,665
  • nvidia/isaac-gr00tNVIDIA 的头像

    NVIDIA/Isaac-GR00T

    6,222在 GitHub 上查看↗

    Provides virtualization and containerization for managing GPU workloads.

    Jupyter Notebook
    在 GitHub 上查看↗6,222
  • gpustack/gpustackgpustack 的头像

    gpustack/gpustack

    5,173在 GitHub 上查看↗

    gpustack 是一个 GPU 集群管理平台与 LLM 推理编排器。它作为一个集中式系统,用于汇聚并编排本地服务器与云环境中的图形处理器,充当针对多样化硬件与软件配置的异构计算管理器。 该系统提供了一个安全的 AI 模型部署网关,使用基于密钥的认证将模型作为可扩展服务提供。它包含一个 GPU 资源调度器,用于平衡加速器间的负载,并协调多个推理引擎,将特定 AI 模型映射到兼容的硬件上。 该平台涵盖了全面的集群编排,包括自动化故障恢复、实时资源监控与分布式推理扩展。它通过量化与投机解码整合了性能优化,以最大化吞吐量并降低延迟。 系统配置与集群状态通过外部关系型数据库状态持久化进行维护。

    Coordinates and deploys inference engines like vLLM and SGLang to serve AI models.

    Python
    在 GitHub 上查看↗5,173
  • jamesturland/jimsgarageJamesTurland 的头像

    JamesTurland/JimsGarage

    4,439在 GitHub 上查看↗

    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 create toolbox containers with GPU access for running compute workloads.

    Shell
    在 GitHub 上查看↗4,439
  • checkpoint-restore/criucheckpoint-restore 的头像

    checkpoint-restore/criu

    3,697在 GitHub 上查看↗

    CRIU is a Linux process checkpointing tool and state manager used to freeze running applications and save their memory and state to disk for later restoration. It functions as a container migration engine and an OCI checkpoint image converter, allowing the live state of running containers to be transferred between different hosts. The project distinguishes itself through its ability to persist network connectivity, acting as a TCP connection state persister that saves and reconstructs network socket states to maintain active communication after a restart. It further enables the distribution o

    Captures and restores the state of applications using GPU acceleration to enable failure recovery and workload migration.

    Cblcrcheckpointcontainer
    在 GitHub 上查看↗3,697
  1. Home
  2. Operating Systems & Systems Programming
  3. GPU Resource Virtualization
  4. GPU Workload Virtualization and Containerization

探索子标签

  • GPU Workload CheckpointingCapturing and restoring the execution state of GPU-accelerated applications for migration or recovery. **Distinct from GPU Workload Virtualization and Containerization:** Distinct from general GPU virtualization; focuses specifically on saving and restoring the runtime state (checkpointing).
  • Kernel-Level Hardware IsolationProvides secure isolation for hardware-accelerated workloads using kernel primitives to avoid hypervisor overhead. **Distinct from GPU Workload Virtualization and Containerization:** Focuses on using kernel-level security for high-performance direct hardware access, whereas general GPU Virtualization often involves hypervisors.
  • LLM Inference OrchestrationOrchestrating large language model inference tasks on GPU hardware within a Kubernetes cluster. **Distinct from GPU Workload Virtualization and Containerization:** Distinct from general GPU Workload Virtualization and Containerization: focuses specifically on orchestrating LLM inference tasks, not general GPU workload management.