Nvidia CUDA

Cuda

Detailed monitoring of Nvidia GPU with OddEye.

Nvidia CUDA check depends on nvidia-ml python module, so in order to use this check nvidia-ml should be installed.

Install

You can install nvidia-ml with pip or pip3 based on your python version .
Python2:

pip install nvidia-ml-py

Python3:

pip3 install nvidia-ml-py3
Configure

Nvidia CUDA check does not requires any configuration , just enable check_nvidia_gpu module and restart oe-agent

cd ${OE_AGENT_HOME}/checks_enabled/
ln -s ../checks_available/check_nvidia_gpu.py
Restart
${OE_AGENT_HOME}/oddeye.sh restart
Provides
Name Description Type Unit
nvidia_b1_memory_free Retrieves the amount of BAR1 free memory available on the device gauge Bytes
nvidia_b1_memory_total Retrieves the amount of BAR1 total memory available on the device gauge Bytes
nvidia_b1_memory_used Retrieves the amount of BAR1 used memory available on the device gauge Bytes
nvidia_memory_free Retrieves the amount of free memory available on the device gauge Bytes
nvidia_memory_total Retrieves the amount of total memory available on the device gauge Bytes
nvidia_memory_used Retrieves the amount of used memory available on the device gauge Bytes
nvidia_cuda_processes Metrics only about compute running processes (e.g. CUDA application which have active context). gauge Integer
nvidia_graphic_processes Metrics only about graphics based processes (eg. applications using OpenGL, DirectX)" gauge Integer
nvidia_memory_utilizaton Current utilization rates for the device's memory subsystems. gauge Percent
nvidia_gpu_utilizaton Current utilization rates for the device's gpu subsystems. gauge Percent
nvidia_fan_speed The fan speed is expressed as a percent of the maximum, i.e. full speed is 100%." gauge Percent
nvidia_gpu_clock_info Current clock speeds for the device. gauge Integer
nvidia_gpu_temperature Current temperature readings for the device, in degrees C." gauge Celsius
nvidia_power_usage power usage for this GPU in milliwatts gauge Milliwatts