NVIDIA GPU Prometheus Exporter

This is a Prometheus Exporter for exporting NVIDIA GPU metrics. It uses the Go bindings for NVIDIA Management Library (NVML) which is a C-based API that can be used for monitoring NVIDIA GPU devices. Unlike some other similar exporters, it does not call the nvidia-smi binary.

Building

The repository includes nvml.h, so there are no special requirements from the build environment. go get should be able to build the exporter binary.

go get github.com/mindprince/nvidia_gpu_prometheus_exporter

Running

The exporter requires the following:

• access to NVML library (libnvidia-ml.so.1).
• access to the GPU devices.

To make sure that the exporter can access the NVML libraries, either add them to the search path for shared libraries. Or set LD_LIBRARY_PATH to point to their location.

By default the metrics are exposed on port 9445. This can be updated using the -web.listen-address flag.

Running inside a container

There's a docker image available on Docker Hub at mindprince/nvidia_gpu_prometheus_exporter

If you are running the exporter inside a container, you will need to do the following to give the container access to NVML library:

-e LD_LIBRARY_PATH=<path-where-nvml-is-present>
--volume <above-path>:<above-path>

And you will need to do one of the following to give it access to the GPU devices:

• Run with --privileged
• If you are on docker v17.04.0-ce or above, run with --device-cgroup-rule 'c 195:* mrw'
• Run with --device /dev/nvidiactl:/dev/nvidiactl /dev/nvidia0:/dev/nvidia0 /dev/nvidia1:/dev/nvidia1 <and-so-on-for-all-nvidia-devices>

If you don't want to do the above, you can run it using nvidia-docker.

Running using nvidia-docker

nvidia-docker run -p 9445:9445 -ti mindprince/nvidia_gpu_prometheus_exporter:0.1