NVIDIA Data Center GPU Manager (DCGM)

The NVIDIA Data Center GPU Manager integration collects key advanced GPU metrics from DCGM, including Streaming Multiprocessor (SM) block utilization, SM occupancy, SM pipe utilization, PCIe traffic rate, and NVLink traffic rate. For information about the purpose and interpretation of these metrics, see Profiling Metrics in the DCGM feature overview.

For more information about the NVIDIA Data Center GPU Manager, see the DCGM documentation. This integration is compatible with DCGM version 3.1 and later.

The Ops Agent collects DCGM metrics by using NVIDIA's client library go-dcgm.

These metrics are available for Linux systems only. Metrics are not collected from NVIDIA GPU models K80, P100, and P4.

Prerequisites

To collect DCGM metrics, you must do the following:

• Install DCGM.

• Install the Ops Agent. Only Ops Agent version 2.38.0 or versions 2.41.0 or newer are compatible with GPU monitoring. Do not install Ops Agent versions 2.39.0 and 2.40.0 on VMs with attached GPUs. For more information, see Agent crashes and report mentions NVIDIA.

Install DCGM and verify installation

You must install a DCGM version 3.1 and later and ensure that it runs as a privileged service. To install DCGM, see Installation in the DCGM documentation.

To verify that DCGM is running correctly, do the following:

1. Check the status of the DCGM service by running the following command:

   sudo service nvidia-dcgm status
   

   If the service is running, the nvidia-dcgm service is listed as active (running). The output resembles the following:

   ● nvidia-dcgm.service - NVIDIA DCGM service
   Loaded: loaded (/usr/lib/systemd/system/nvidia-dcgm.service; disabled; vendor preset: enabled)
   Active: active (running) since Sat 2023-01-07 15:24:29 UTC; 3s ago
   Main PID: 24388 (nv-hostengine)
   Tasks: 7 (limit: 14745)
   CGroup: /system.slice/nvidia-dcgm.service
          └─24388 /usr/bin/nv-hostengine -n --service-account nvidia-dcgm
   

2. Verify that the GPU devices are found by running the following command:

   dcgmi discovery --list
   

   If devices are found, the output resembles the following:

   1 GPU found.
   +--------+----------------------------------------------------------------------+
   | GPU ID | Device Information                                                   |
   +--------+----------------------------------------------------------------------+
   | 0      | Name: NVIDIA A100-SXM4-40GB                                          |
   |        | PCI Bus ID: 00000000:00:04.0                                         |
   |        | Device UUID: GPU-a2d9f5c7-87d3-7d57-3277-e091ad1ba957                |
   +--------+----------------------------------------------------------------------+
   

Configure the Ops Agent for DCGM

Following the guide for Configuring the Ops Agent, add the required elements to collect telemetry from your DCGM service, and restart the agent.

Example configuration

The following commands create the configuration to collect and ingest telemetry for DCGM and restart the Ops Agent:

# Configures Ops Agent to collect telemetry from the app and restart Ops Agent.
set -e

# Create a back up of the existing file so existing configurations are not lost.
sudo cp /etc/google-cloud-ops-agent/config.yaml /etc/google-cloud-ops-agent/config.yaml.bak

# Configure the Ops Agent.
sudo tee /etc/google-cloud-ops-agent/config.yaml > /dev/null << EOF
metrics:
  receivers:
    dcgm:
      type: dcgm
  service:
    pipelines:
      dcgm:
        receivers:
          - dcgm
EOF

sudo systemctl restart google-cloud-ops-agent

After running these commands, you can check that the agent restarted. Run the following command and verify that the sub-agent components "Metrics Agent" and "Logging Agent" are listed as "active (running)":

sudo systemctl status google-cloud-ops-agent"*"

Note: If you restarted the Ops Agent by using the command sudo service google-cloud-ops-agent restart and the sub-agents did not restart correctly, then use the systemctl restart command shown in the configuration commands. For some Deep Learning VM Images, the Ops Agent doesn't restart all the dependencies when you restart with service restart.

If you are using custom service account instead of the default Compute Engine service account, or if you have a very old Compute Engine VM, then you might need to authorize the Ops Agent.

Configure metrics collection

To ingest metrics from DCGM, you must create a receiver for the metrics that DCGM produces and then create a pipeline for the new receiver.

This receiver does not support the use of multiple instances in the configuration, for example, to monitor multiple endpoints. All such instances write to the same time series, and Cloud Monitoring has no way to distinguish among them.

To configure a receiver for your dcgm metrics, specify the following fields:

Field	Default	Description
collection_interval	60s	A time duration, such as 30s or 5m.
endpoint	localhost:5555	Address of the DCGM service, formatted as host:port.
type		This value must be dcgm.

What is monitored

The following table provides the list of metrics that the Ops Agent collects from the DCGM service. Not all metrics are available for all GPU models. Metrics are not collected from NVIDIA GPU models K80, P100, and P4.

Metric type
Kind, Type Monitored resources	Labels	Supported GPU models
workload.googleapis.com/dcgm.gpu.profiling.dram_utilization
GAUGE, DOUBLE gce_instance	gpu_number model uuid	All except K80, P100, and P4
workload.googleapis.com/dcgm.gpu.profiling.nvlink_traffic_rate
GAUGE, INT64 gce_instance	direction gpu_number model uuid	All except K80, P100, and P4
workload.googleapis.com/dcgm.gpu.profiling.pcie_traffic_rate
GAUGE, INT64 gce_instance	direction gpu_number model uuid	All except K80, P100, and P4
workload.googleapis.com/dcgm.gpu.profiling.pipe_utilization
GAUGE, DOUBLE gce_instance	gpu_number model pipe uuid	All except K80, P100, and P4. For L4, the pipe value fp64 is not supported.
workload.googleapis.com/dcgm.gpu.profiling.sm_occupancy
GAUGE, DOUBLE gce_instance	gpu_number model uuid	All except K80, P100, and P4
workload.googleapis.com/dcgm.gpu.profiling.sm_utilization
GAUGE, DOUBLE gce_instance	gpu_number model uuid	All except K80, P100, and P4

In addition, the built-in configuration for the Ops Agent also collects agent.googleapis.com/gpu metrics, which are reported by the NVIDIA Management Library (NVML). You do not need any additional configuration in the Ops Agent to collect these metrics, but you must create your VM with attached GPUs and install the GPU driver. For more information, see About the gpu metrics.

Verify the configuration

This section describes how to verify that you correctly configured the NVIDIA DCGM receiver. It might take one or two minutes for the Ops Agent to begin collecting telemetry.

To verify that NVIDIA DCGM metrics are being sent to Cloud Monitoring, do the following:

1. In the navigation panel of the Google Cloud console, select Monitoring, and then select  Metrics explorer:

   Go to Metrics explorer

2. In the toolbar of the query-builder pane, select the button whose name is either  MQL or  PromQL.
3. Verify that MQL is selected in the Language toggle. The language toggle is in the same toolbar that lets you format your query.
4. Enter the following query in the editor, and then click Run query:
   

   fetch gce_instance
   | metric 'workload.googleapis.com/dcgm.gpu.profiling.sm_utilization'
   | every 1m
   

View dashboard

To view your NVIDIA DCGM metrics, you must have a chart or dashboard configured. The NVIDIA DCGM integration includes one or more dashboards for you. Any dashboards are automatically installed after you configure the integration and the Ops Agent has begun collecting metric data.

You can also view static previews of dashboards without installing the integration.

To view an installed dashboard, do the following:

1. In the navigation panel of the Google Cloud console, select Monitoring, and then select  Dashboards:

   Go to Dashboards

2. Select the Dashboard List tab, and then choose the Integrations category.
3. Click the name of the dashboard you want to view.

If you have configured an integration but the dashboard has not been installed, then check that the Ops Agent is running. When there is no metric data for a chart in the dashboard, installation of the dashboard fails. After the Ops Agent begins collecting metrics, the dashboard is installed for you.

To view a static preview of the dashboard, do the following:

1. In the navigation panel of the Google Cloud console, select Monitoring, and then select  Integrations:

   Go to Integrations

2. Click the Compute Engine deployment-platform filter.
3. Locate the entry for NVIDIA DCGM and click View Details.
4. Select the Dashboards tab to see a static preview. If the dashboard is installed, then you can navigate to it by clicking View dashboard.

For more information about dashboards in Cloud Monitoring, see Dashboards and charts.

For more information about using the Integrations page, see Manage integrations.

DCGM limitations, and pausing profiling

Concurrent usage of DCGM can conflict with usage of some other NVIDIA developer tools, such as Nsight Systems or Nsight Compute. This limitation applies to NVIDIA A100 and earlier GPUs. For more information, see Profiling Sampling Rate in the DCGM feature overiew.

When you need to use tools like Nsight Systems without significant disruption, you can temporarily pause or resume the metrics collection by using the following commands:

dcgmi profile --pause
dcgmi profile --resume

When profiling is paused, none of the DCGM metrics that the Ops Agent collects are emitted from the VM.

What's next

For a walkthrough on how to use Ansible to install the Ops Agent, configure a third-party application, and install a sample dashboard, see the Install the Ops Agent to troubleshoot third-party applications video.