Create groups of GPU VMs in bulk

gcloud

To create a group of VMs, use the gcloud compute instances bulk create command. For more information about the parameters and how to use this command, see Create VMs in bulk.

The following optional flags are shown in the example command:

• The --provisioning-model=SPOT is an optional flag that configures your VMs as Spot VMs. If your workload is fault-tolerant and can withstand possible VM preemption, consider using Spot VMs to reduce the cost of your VMs and the attached GPUs. For more information, see GPUs on Spot VMs. For Spot VMs, the automatic restart and host maintenance options flags are disabled.

• The --accelerator flag to specify a virtual workstation. NVIDIA RTX Virtual Workstations (vWS) are supported for only G2 VMs.

Example

This example creates two VMs that have attached GPUs by using the following specifications:

• VM names: my-test-vm-1, my-test-vm-2
• Each VM has two GPUs attached, specified by using the appropriate accelerator-optimized machine type

gcloud compute instances bulk create \
    --name-pattern="my-test-vm-#" \
    --region=REGION \
    --count=2 \
    --machine-type=MACHINE_TYPE \
    --boot-disk-size=200 \
    --image=IMAGE \
    --image-project=IMAGE_PROJECT \
    --on-host-maintenance=TERMINATE \
    [--provisioning-model=SPOT] \
    [--accelerator=type=nvidia-l4-vws,count=VWS_ACCELERATOR_COUNT]

Replace the following:

• REGION: the region for the VMs. This region must support your selected GPU model.

• MACHINE_TYPE: the machine type that you selected. Choose from one of the following:

  • An A3 machine type.
  • An A2 machine type.
  • A G2 machine type. G2 machine types also support custom memory. Memory must be a multiple of 1024 MB and within the supported memory range. For example, to create a VM with 4 vCPUs and 19 GB of memory specify --machine-type=g2-custom-4-19456.

• IMAGE: an operating system image that supports GPUs.

  If you want to use the latest image in an image family, replace the --image flag with the --image-family flag and set its value to an image family that supports GPUs. For example: --image-family=rocky-linux-8-optimized-gcp.

  You can also specify a custom image or Deep Learning VM Images.

• IMAGE_PROJECT: the Compute Engine image project that the OS image belongs to. If using a custom image or Deep Learning VM Images, specify the project that those images belong to.

• VWS_ACCELERATOR_COUNT: the number of virtual GPUs that you need.

If successful, the output is similar to the following:

NAME          ZONE
my-test-vm-1  us-central1-b
my-test-vm-2  us-central1-b
Bulk create request finished with status message: [VM instances created: 2, failed: 0.]

REST

Use the instances.bulkInsert method with the required parameters to create multiple VMs in a zone. For more information about the parameters and how to use this command, see Create VMs in bulk.

Example

This example creates two VMs that have attached GPUs by using the following specifications:

• VM names: my-test-vm-1, my-test-vm-2

• Each VM has two GPUs attached, specified by using the appropriate accelerator-optimized machine type

  POST https://compute.googleapis.com/compute/v1/projects/PROJECT_ID/regions/REGION/instances/bulkInsert
  {
  "namePattern":"my-test-vm-#",
  "count":"2",
  "instanceProperties": {
    "machineType":MACHINE_TYPE,
    "disks":[
      {
        "type":"PERSISTENT",
        "initializeParams":{
          "diskSizeGb":"200",
          "sourceImage":SOURCE_IMAGE_URI
        },
        "boot":true
      }
    ],
    "name": "default",
    "networkInterfaces":
    [
      {
        "network": "projects/PROJECT_ID/global/networks/default"
      }
    ],
    "scheduling":{
      "onHostMaintenance":"TERMINATE",
      ["automaticRestart":true]
    }
  }
  }
  

Replace the following:

• PROJECT_ID: your project ID
• REGION: the region for the VMs. This region must support your selected GPU model.

• MACHINE_TYPE: the machine type that you selected. Choose from one of the following:

  • An A2 machine type.
  • A G2 machine type. G2 machine types also support custom memory. Memory must be a multiple of 1024 MB and within the supported memory range. For example, to create a VM with 4 vCPUs and 19 GB of memory specify --machine-type=g2-custom-4-19456.

• SOURCE_IMAGE_URI: the URI for the specific image or image family that you want to use.

  For example:

  • Specific image: "sourceImage": "projects/rocky-linux-cloud/global/images/rocky-linux-8-optimized-gcp-v20220719"
  • Image family: "sourceImage": "projects/rocky-linux-cloud/global/images/family/rocky-linux-8-optimized-gcp".

  When you specify an image family, Compute Engine creates a VM from the most recent, non-deprecated OS image in that family. For more information about when to use image families, see Image family best practices.

Additional settings:

• If your workload is fault-tolerant and can withstand possible VM preemption, consider using Spot VMs to reduce the cost of your VMs and the attached GPUs. For more information, see GPUs on Spot VMs. To use a Spot VM, add the "provisioningModel": "SPOT option to your request. For Spot VMs, the automatic restart and host maintenance options flags are disabled.

  "scheduling":
    {
      "provisioningModel": "SPOT"
    }
  

• For G2 VMs, NVIDIA RTX Virtual Workstations (vWS) are supported. To specify a virtual workstation, add the guestAccelerators option to your request. Replace VWS_ACCELERATOR_COUNT with the number of virtual GPUs that you need.

  "guestAccelerators":
   [
     {
       "acceleratorCount": VWS_ACCELERATOR_COUNT,
       "acceleratorType": "projects/PROJECT_ID/zones/ZONEacceleratorTypes/nvidia-l4-vws"
     }
   ]
  

A3 Mega VMs

• You don't receive sustained use discounts and flexible committed use discounts for VMs that use an A3 Mega machine type.
• You can only use an A3 Mega machine type in certain regions and zones.
• You can't use regional persistent disks on a VM that use A3 Mega machine type.
• The A3 Mega machine type is only available on the Sapphire Rapids platform.
• If your VM uses an A3 Mega machine type, you can't change the machine type. If you need to change the machine type, you must create a new VM.
• You can't change the machine type of a VM to an A3 Mega machine type. If you need a VM that uses an A3 Mega machine type, you must create a new VM.
• A3 Mega machine types don't support sole-tenancy.
• You can't run Windows operating systems on an A3 Mega machine type.
• You can reserve A3 Mega machine types only through certain reservations.

A3 High VMs

• You don't receive sustained use discounts and flexible committed use discounts for VMs that use an A3 High machine type.
• You can only use an A3 High machine type in certain regions and zones.
• You can't use regional persistent disks on a VM that use A3 High machine type.
• The A3 High machine type is only available on the Sapphire Rapids platform.
• If your VM uses an A3 High machine type, you can't change the machine type. If you need to change the machine type, you must create a new VM.
• You can't change the machine type of a VM to an A3 High machine type. If you need a VM that uses an A3 High machine type, you must create a new VM.
• A3 High machine types don't support sole-tenancy.
• You can't run Windows operating systems on an A3 High machine type.
• You can reserve A3 High machine types only through certain reservations.
• For a3-highgpu-1g, a3-highgpu-2g, anda3-highgpu-4g machine types, the following limitations apply:
  • For these machine types, you must either use Spot VMs or a feature that uses the Dynamic Workload Scheduler (DWS) such as resize requests in a MIG. For detailed instructions on either of these options, review the following:
    • To create Spot VMs, see Create an accelerator-optimized VM and remember to set the provisiong model to SPOT
    • To create a resize request in a MIG, which uses Dynamic Workload Scheduler, see Create a MIG with GPU VMs.
  • You can't use Hyperdisk Balanced with these machine types.
  • You can't create reservations.
  If you try to create a VM by using standard provisioning or try to create a reservation for these machine types, you'll receive an error message.

A3 Edge VMs

• You don't receive sustained use discounts and flexible committed use discounts for VMs that use an A3 Edge machine type.
• You can only use an A3 Edge machine type in certain regions and zones.
• You can't use regional persistent disks on a VM that use A3 Edge machine type.
• The A3 Edge machine type is only available on the Sapphire Rapids platform.
• If your VM uses an A3 Edge machine type, you can't change the machine type. If you need to change the machine type, you must create a new VM.
• You can't change the machine type of a VM to an A3 Edge machine type. If you need a VM that uses an A3 Edge machine type, you must create a new VM.
• A3 Edge machine types don't support sole-tenancy.
• You can't run Windows operating systems on an A3 Edge machine type.
• You can reserve A3 Edge machine types only through certain reservations.

A2 Standard VMs

• You don't receive sustained use discounts and flexible committed use discounts for VMs that use an A2 Standard machine types.
• You can only use an A2 Standard machine types in certain regions and zones.
• You can't use regional persistent disks on a VM that use A2 Standard machine types.
• The A2 Standard machine type is only available on the Cascade Lake platform.
• If your VM uses an A2 Standard machine type, you can only switch from one A2 Standard machine type to another A2 Standard machine type. You can't change to any other machine type. For more information, see Modify accelerator-optmized VMs.
• You can't use the Windows operating system with A2 Standard machine types. When using Windows operating systems, choose a different A2 Standard machine type.
• You can't do a quick format of the attached Local SSDs on Windows VMs that use A2 Standard machine types. To format these Local SSDs, you must do a full format by using the diskpart utility and specifying format fs=ntfs label=tmpfs.
• A2 Standard machine types don't support sole-tenancy.

A2 Ultra VMs

• You don't receive sustained use discounts and flexible committed use discounts for VMs that use an A2 Ultra machine types.
• You can only use an A2 Ultra machine types in certain regions and zones.
• You can't use regional persistent disks on a VM that use A2 Ultra machine types.
• The A2 Ultra machine type is only available on the Cascade Lake platform.
• If your VM uses an A2 Ultra machine type, you can't change the machine type. If you need to use a different A2 Ultra machine type, or any other machine type, you must create a new VM.
• You can't change any other machine type to an A2 Ultra machine type. If you need a VM that uses an A2 Ultra machine type, you must create a new VM.
• You can't do a quick format of the attached Local SSDs on Windows VMs that use A2 Ultra machine types. To format these Local SSDs, you must do a full format by using the diskpart utility and specifying format fs=ntfs label=tmpfs.

G2 VMs

• You don't receive sustained use discounts and flexible committed use discounts for VMs that use an G2 machine types.
• You can only use an G2 machine types in certain regions and zones.
• You can't use regional persistent disks on a VM that use G2 machine types.
• The G2 machine type is only available on the Cascade Lake platform.
• Standard persistent disks (pd-standard) are not supported on VMs that use G2 standard machine types. For supported disk types, see Supported disk types for G2.
• You can't create Multi-Instance GPUs on G2 machine types.
• If you need to change the machine type of a G2 VM, review Modify accelerator-optmized VMs.
• You can't use Deep Learning VM Images as boot disks for your VMs that use G2 machine types.
• The current default driver for Container-Optimized OS doesn't support L4 GPUs running on G2 machine types. Container-Optimized OS also only support a select set of drivers. If you want to use Container-Optimized OS on G2 machine types, review the following notes:
  • Use a Container-Optimized OS version that supports the minimum recommended NVIDIA driver version 525.60.13 or later. For more information, review the Container-Optimized OS release notes.
  • When you install the driver, specify the latest available version that works for the L4 GPUs. For example, sudo cos-extensions install gpu -- -version=525.60.13.
• You must use the Google Cloud CLI or REST to create G2 VMs for the following scenarios:
  • You want to specify custom memory values.
  • You want to customize the number of visible CPU cores.

gcloud

To create a group of VMs, use the gcloud compute instances bulk create command. For more information about the parameters and how to use this command, see Create VMs in bulk.

Example

The following example creates two VMs with attached GPUs using the following specifications:

• VM names: my-test-vm-1, my-test-vm-2
• VMs created in any zone in us-central1 that supports GPUs
• Each VM has two T4 GPUs attached, specified by using the accelerator type and accelerator count flags
• Each VM has GPU drivers installed
• Each VM uses the Deep Learning VM image pytorch-latest-gpu-v20211028-debian-10

gcloud compute instances bulk create \
    --name-pattern="my-test-vm-#" \
    --count=2 \
    --region=us-central1 \
    --machine-type=n1-standard-2 \
    --accelerator type=nvidia-tesla-t4,count=2 \
    --boot-disk-size=200 \
    --metadata="install-nvidia-driver=True" \
    --scopes="https://www.googleapis.com/auth/cloud-platform" \
    --image=pytorch-latest-gpu-v20211028-debian-10 \
    --image-project=deeplearning-platform-release \
    --on-host-maintenance=TERMINATE --restart-on-failure

If successful, the output is similar to the following:

NAME          ZONE
my-test-vm-1  us-central1-b
my-test-vm-2  us-central1-b
Bulk create request finished with status message: [VM instances created: 2, failed: 0.]

REST

Use the instances.bulkInsert method with the required parameters to create multiple VMs in a zone. For more information about the parameters and how to use this command, see Create VMs in bulk.

Example

The following example creates two VMs with attached GPUs using the following specifications:

• VM names: my-test-vm-1, my-test-vm-2
• VMs created in any zone in us-central1 that supports GPUs
• Each VM has two T4 GPUs attached, specified by using the accelerator type and accelerator count flags
• Each VM has GPU drivers installed
• Each VM uses the Deep Learning VM image pytorch-latest-gpu-v20211028-debian-10

Replace PROJECT_ID with your project ID.

POST https://compute.googleapis.com/compute/v1/projects/PROJECT_ID/region/us-central1/instances/bulkInsert

{
    "namePattern":"my-test-vm-#",
    "count":"2",
    "instanceProperties": {
      "machineType":"n1-standard-2",
      "disks":[
        {
          "type":"PERSISTENT",
          "initializeParams":{
            "diskSizeGb":"200",
            "sourceImage":"projects/deeplearning-platform-release/global/images/pytorch-latest-gpu-v20211028-debian-10"
          },
          "boot":true
        }
      ],
      "name": "default",
      "networkInterfaces":
      [
        {
          "network": "projects/PROJECT_ID/global/networks/default"
        }
      ],
      "guestAccelerators":
      [
        {
          "acceleratorCount": 2,
          "acceleratorType": "nvidia-tesla-t4"
        }
      ],
      "scheduling":{
        "onHostMaintenance":"TERMINATE",
        "automaticRestart":true
      },
      "metadata":{
        "items":[
          {
            "key":"install-nvidia-driver",
            "value":"True"
          }
        ]
      }
  }
 }