DCGM-Exporter
This repository contains the DCGM-Exporter project. It exposes GPU metrics exporter for Prometheus leveraging NVIDIA DCGM.
Documentation
Official documentation for DCGM-Exporter can be found on docs.nvidia.com.
Quickstart
To gather metrics on a GPU node, simply start the dcgm-exporter container:
$ docker run -d --gpus all --rm -p 9400:9400 nvcr.io/nvidia/k8s/dcgm-exporter:2.2.9-2.4.0-ubuntu18.04
$ curl localhost:9400/metrics
# HELP DCGM_FI_DEV_SM_CLOCK SM clock frequency (in MHz).
# TYPE DCGM_FI_DEV_SM_CLOCK gauge
# HELP DCGM_FI_DEV_MEM_CLOCK Memory clock frequency (in MHz).
# TYPE DCGM_FI_DEV_MEM_CLOCK gauge
# HELP DCGM_FI_DEV_MEMORY_TEMP Memory temperature (in C).
# TYPE DCGM_FI_DEV_MEMORY_TEMP gauge
...
DCGM_FI_DEV_SM_CLOCK{gpu="0", UUID="GPU-604ac76c-d9cf-fef3-62e9-d92044ab6e52"} 139
DCGM_FI_DEV_MEM_CLOCK{gpu="0", UUID="GPU-604ac76c-d9cf-fef3-62e9-d92044ab6e52"} 405
DCGM_FI_DEV_MEMORY_TEMP{gpu="0", UUID="GPU-604ac76c-d9cf-fef3-62e9-d92044ab6e52"} 9223372036854775794
...
Quickstart on Kubernetes
Note: Consider using the NVIDIA GPU Operator rather than DCGM-Exporter directly.
Ensure you have already setup your cluster with the default runtime as NVIDIA.
The recommended way to install DCGM-Exporter is to use the Helm chart:
$ helm repo add gpu-helm-charts \
https://nvidia.github.io/dcgm-exporter/helm-charts
Update the repo:
$ helm repo update
And install the chart:
$ helm install \
--generate-name \
gpu-helm-charts/dcgm-exporter
Once the dcgm-exporter pod is deployed, you can use port forwarding to obtain metrics quickly:
$ kubectl create -f https://raw.githubusercontent.com/NVIDIA/dcgm-exporter/master/dcgm-exporter.yaml
# Let's get the output of a random pod:
$ NAME=$(kubectl get pods -l "app.kubernetes.io/name=dcgm-exporter" \
-o "jsonpath={ .items[0].metadata.name}")
$ kubectl port-forward $NAME 8080:9400 &
$ curl -sL http://127.0.01:8080/metrics
# HELP DCGM_FI_DEV_SM_CLOCK SM clock frequency (in MHz).
# TYPE DCGM_FI_DEV_SM_CLOCK gauge
# HELP DCGM_FI_DEV_MEM_CLOCK Memory clock frequency (in MHz).
# TYPE DCGM_FI_DEV_MEM_CLOCK gauge
# HELP DCGM_FI_DEV_MEMORY_TEMP Memory temperature (in C).
# TYPE DCGM_FI_DEV_MEMORY_TEMP gauge
...
DCGM_FI_DEV_SM_CLOCK{gpu="0", UUID="GPU-604ac76c-d9cf-fef3-62e9-d92044ab6e52",container="",namespace="",pod=""} 139
DCGM_FI_DEV_MEM_CLOCK{gpu="0", UUID="GPU-604ac76c-d9cf-fef3-62e9-d92044ab6e52",container="",namespace="",pod=""} 405
DCGM_FI_DEV_MEMORY_TEMP{gpu="0", UUID="GPU-604ac76c-d9cf-fef3-62e9-d92044ab6e52",container="",namespace="",pod=""} 9223372036854775794
...
To integrate DCGM-Exporter with Prometheus and Grafana, see the full instructions in the user guide. dcgm-exporter is deployed as part of the GPU Operator. To get started with integrating with Prometheus, check the Operator user guide.
Building from Source
In order to build dcgm-exporter ensure you have the following:
$ git clone https://github.com/NVIDIA/dcgm-exporter.git
$ cd dcgm-exporter
$ make binary
$ sudo make install
...
$ dcgm-exporter &
$ curl localhost:9400/metrics
# HELP DCGM_FI_DEV_SM_CLOCK SM clock frequency (in MHz).
# TYPE DCGM_FI_DEV_SM_CLOCK gauge
# HELP DCGM_FI_DEV_MEM_CLOCK Memory clock frequency (in MHz).
# TYPE DCGM_FI_DEV_MEM_CLOCK gauge
# HELP DCGM_FI_DEV_MEMORY_TEMP Memory temperature (in C).
# TYPE DCGM_FI_DEV_MEMORY_TEMP gauge
...
DCGM_FI_DEV_SM_CLOCK{gpu="0", UUID="GPU-604ac76c-d9cf-fef3-62e9-d92044ab6e52"} 139
DCGM_FI_DEV_MEM_CLOCK{gpu="0", UUID="GPU-604ac76c-d9cf-fef3-62e9-d92044ab6e52"} 405
DCGM_FI_DEV_MEMORY_TEMP{gpu="0", UUID="GPU-604ac76c-d9cf-fef3-62e9-d92044ab6e52"} 9223372036854775794
...
Changing Metrics
With dcgm-exporter you can configure which fields are collected by specifying a custom CSV file. You will find the default CSV file under etc/default-counters.csv in the repository, which is copied on your system or container to /etc/dcgm-exporter/default-counters.csv
The layout and format of this file is as follows:
# Format,,
# If line starts with a '#' it is considered a comment,,
# DCGM FIELD, Prometheus metric type, help message
# Clocks,,
DCGM_FI_DEV_SM_CLOCK, gauge, SM clock frequency (in MHz).
DCGM_FI_DEV_MEM_CLOCK, gauge, Memory clock frequency (in MHz).
A custom csv file can be specified using the -f option or --collectors as follows:
$ dcgm-exporter -f /tmp/custom-collectors.csv
Notes:
- Always make sure your entries have 2 commas (',')
- The complete list of counters that can be collected can be found on the DCGM API reference manual: https://docs.nvidia.com/datacenter/dcgm/latest/dcgm-api/group__dcgmFieldIdentifiers.html
What about a Grafana Dashboard?
You can find the official NVIDIA DCGM-Exporter dashboard here: https://grafana.com/grafana/dashboards/12239
You will also find the json file on this repo under grafana/dcgm-exporter-dashboard.json
Pull requests are accepted!
Issues and Contributing
Checkout the Contributing document!
- Please let us know by filing a new issue
- You can contribute by opening a pull request
This is the result of the nvidia-smi:
I want to know who uses the 1% SM Utilization of the gpu?
