Nvidia GPU
Nvidia GPU
Plugin: go.d.plugin Module: nvidia_smi
Overview
This collector monitors GPUs performance metrics using the nvidia-smi CLI tool.
This collector is supported on all platforms.
This collector supports collecting metrics from multiple instances of this integration, including remote instances.
Default Behavior
Auto-Detection
This integration doesn’t support auto-detection.
Limits
The default configuration for this integration does not impose any limits on data collection.
Performance Impact
The default configuration for this integration is not expected to impose a significant performance impact on the system.
Setup
Prerequisites
No action required.
Configuration
File
The configuration file name for this integration is go.d/nvidia_smi.conf.
You can edit the configuration file using the edit-config script from the
Netdata config directory.
cd /etc/netdata 2>/dev/null || cd /opt/netdata/etc/netdata
sudo ./edit-config go.d/nvidia_smi.conf
Options
The following options can be defined globally: update_every, autodetection_retry.
| Name | Description | Default | Required |
|---|---|---|---|
| update_every | Data collection frequency. | 10 | no |
| autodetection_retry | Recheck interval in seconds. Zero means no recheck will be scheduled. | 0 | no |
| binary_path | Path to nvidia_smi binary. The default is “nvidia_smi” and the executable is looked for in the directories specified in the PATH environment variable. | nvidia_smi | no |
| timeout | The maximum duration, in seconds, to wait for an nvidia-smi command to complete. This setting applies differently based on the collector’s mode. Loop Mode: In loop mode, the timeout primarily determines how long to wait for the initial nvidia-smi execution. If the initial query takes longer than the timeout, the collector may report an error. For systems with multiple GPUs, the initial load time can sometimes be significant (e.g., 5-10 seconds). Regular Mode: If the collector is in regular mode, the timeout specifies how long to wait for each individual nvidia-smi execution. |
10 | no |
| loop_mode | When enabled, nvidia-smi is executed continuously in a separate thread using the -l option. |
yes | no |
Examples
Custom binary path
The executable is not in the directories specified in the PATH environment variable.
jobs:
- name: nvidia_smi
binary_path: /usr/local/sbin/nvidia_smi
Metrics
Metrics grouped by scope.
The scope defines the instance that the metric belongs to. An instance is uniquely identified by a set of labels.
Per gpu
These metrics refer to the GPU.
Labels:
| Label | Description |
|---|---|
| uuid | GPU uuid (e.g. GPU-27b94a00-ed54-5c24-b1fd-1054085de32a) |
| index | GPU index (nvidia_smi typically orders GPUs by PCI bus ID) |
| product_name | GPU product name (e.g. NVIDIA A100-SXM4-40GB) |
Metrics:
| Metric | Dimensions | Unit |
|---|---|---|
| nvidia_smi.gpu_pcie_bandwidth_usage | rx, tx | B/s |
| nvidia_smi.gpu_pcie_bandwidth_utilization | rx, tx | % |
| nvidia_smi.gpu_fan_speed_perc | fan_speed | % |
| nvidia_smi.gpu_utilization | gpu | % |
| nvidia_smi.gpu_memory_utilization | memory | % |
| nvidia_smi.gpu_decoder_utilization | decoder | % |
| nvidia_smi.gpu_encoder_utilization | encoder | % |
| nvidia_smi.gpu_frame_buffer_memory_usage | free, used, reserved | B |
| nvidia_smi.gpu_bar1_memory_usage | free, used | B |
| nvidia_smi.gpu_temperature | temperature | Celsius |
| nvidia_smi.gpu_voltage | voltage | V |
| nvidia_smi.gpu_clock_freq | graphics, video, sm, mem | MHz |
| nvidia_smi.gpu_power_draw | power_draw | Watts |
| nvidia_smi.gpu_performance_state | P0-P15 | state |
| nvidia_smi.gpu_mig_mode_current_status | enabled, disabled | status |
| nvidia_smi.gpu_mig_devices_count | mig | devices |
Per mig
These metrics refer to the Multi-Instance GPU (MIG).
Labels:
| Label | Description |
|---|---|
| uuid | GPU uuid (e.g. GPU-27b94a00-ed54-5c24-b1fd-1054085de32a) |
| product_name | GPU product name (e.g. NVIDIA A100-SXM4-40GB) |
| gpu_instance_id | GPU instance id (e.g. 1) |
Metrics:
| Metric | Dimensions | Unit |
|---|---|---|
| nvidia_smi.gpu_mig_frame_buffer_memory_usage | free, used, reserved | B |
| nvidia_smi.gpu_mig_bar1_memory_usage | free, used | B |
Alerts
There are no alerts configured by default for this integration.
Troubleshooting
Debug Mode
Important: Debug mode is not supported for data collection jobs created via the UI using the Dyncfg feature.
To troubleshoot issues with the nvidia_smi collector, run the go.d.plugin with the debug option enabled. The output
should give you clues as to why the collector isn’t working.
-
Navigate to the
plugins.ddirectory, usually at/usr/libexec/netdata/plugins.d/. If that’s not the case on your system, opennetdata.confand look for thepluginssetting under[directories].cd /usr/libexec/netdata/plugins.d/ -
Switch to the
netdatauser.sudo -u netdata -s -
Run the
go.d.pluginto debug the collector:./go.d.plugin -d -m nvidia_smi
Getting Logs
If you’re encountering problems with the nvidia_smi collector, follow these steps to retrieve logs and identify potential issues:
- Run the command specific to your system (systemd, non-systemd, or Docker container).
- Examine the output for any warnings or error messages that might indicate issues. These messages should provide clues about the root cause of the problem.
System with systemd
Use the following command to view logs generated since the last Netdata service restart:
journalctl _SYSTEMD_INVOCATION_ID="$(systemctl show --value --property=InvocationID netdata)" --namespace=netdata --grep nvidia_smi
System without systemd
Locate the collector log file, typically at /var/log/netdata/collector.log, and use grep to filter for collector’s name:
grep nvidia_smi /var/log/netdata/collector.log
Note: This method shows logs from all restarts. Focus on the latest entries for troubleshooting current issues.
Docker Container
If your Netdata runs in a Docker container named “netdata” (replace if different), use this command:
docker logs netdata 2>&1 | grep nvidia_smi