[[["わかりやすい","easyToUnderstand","thumb-up"],["問題の解決に役立った","solvedMyProblem","thumb-up"],["その他","otherUp","thumb-up"]],[["わかりにくい","hardToUnderstand","thumb-down"],["情報またはサンプルコードが不正確","incorrectInformationOrSampleCode","thumb-down"],["必要な情報 / サンプルがない","missingTheInformationSamplesINeed","thumb-down"],["翻訳に関する問題","translationIssue","thumb-down"],["その他","otherDown","thumb-down"]],["最終更新日 2025-09-04 UTC。"],[],[],null,["# Cluster node machine types\n\nWhen you create a Kubernetes cluster in Google Distributed Cloud (GDC) air-gapped appliance, you\ncreate node pools that are responsible for running your container workloads in\nthe cluster. You provision nodes based on your container workload requirements,\nand can update them as your requirements evolve.\n\nGDC provides predefined machine types for your worker\nnodes that are selectable when you\n[add a node pool](/distributed-cloud/hosted/docs/latest/appliance/platform/pa-user/manage-node-pools#add-a-node-pool).\nThere are also multiple ways to partition separate GPU instances using the\nMulti-Instance GPU (MIG) feature.\n\nReference the following sections for available machine types and GPU support.\n\nAvailable machine types\n-----------------------\n\nGDC defines machine types with some parameters\nfor a Kubernetes cluster node, which include CPU, memory, and GPU.\nGDC has various machine types for different purposes.\nFor example, clusters use `n2-standard-4-gdc` for general purpose container\nworkloads. If you plan to run artificial intelligence (AI) and\nmachine learning (ML) notebooks, you must provision GPU machines, such as\n`a2-highgpu-1g-gdc`.\n\nThe following is a list of all GDC predefined machine\ntypes available for Kubernetes cluster worker nodes:\n\n| **Preview:** The following machine types are in Preview:\n|\n| - a3-highgpu-1g-gdc\n| - a3-highgpu-2g-gdc\n|\n| For more information on Preview features, see [Feature stages](/distributed-cloud/hosted/docs/latest/appliance/resources/feature-stages#preview).\n\nSupported MIG profiles\n----------------------\n\nThis section defines the supported partitioning schemes of MIG profiles on\nsupported GPUs. You can define a partitioning scheme for a node pool in your\n`Cluster` custom resource.\n| **Important:** A partitioning scheme gets applied to all GPUs in a node. For example, the `a3-highgpu-4g-gdc` machine can support four iterations of the `7x 1g.12gb` GPU slicing because there are four GPUs available to the machine type.\n\nFor more information on how to apply a GPU partitioning scheme, see\n[Add a node pool](/distributed-cloud/hosted/docs/latest/appliance/platform/pa-user/manage-node-pools#add-a-node-pool).\n\n### A100 40GB GPU\n\nThe following table defines the MIG profiles supported on the A100 40GB NVIDIA\nGPU:\n\n### A100 80GB GPU\n\nThe following table defines the MIG profiles supported on the A100 80GB NVIDIA\nGPU:\n\n### H100 94GB GPU\n\nThe following table defines the MIG profiles supported on the H100 94GB NVIDIA\nGPU:"]]
