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[!WARNING] This package includes unofficial NVML bindings and utilities. This package is intended for demonstration purposes only. There is no guarantee for long-term maintenence or support.

The official NVML bindings are published by NVIDIA under a different nvidia-ml-py project (see: https://pypi.org/project/nvidia-ml-py/).

Future releases of this project will not include NVML bindings directly, but will instead depend on nvidia-ml-py.

Please migrate to the official package for long-term support. You can still import and use a familar pynvml module after migrating to the official package.

Python bindings and utilities for the NVIDIA Management Library

[!IMPORTANT] As of version 11.0.0, the NVML-wrappers used in pynvml are directly copied from nvidia-ml-py. In a future release, the local bindings will be removed, and nvidia-ml-py will become a required dependency.

This project provides Python utilities and bindings for the NVIDIA Management Library (NVML).

For information about the NVML library, see the NVML developer page http://developer.nvidia.com/nvidia-management-library-nvml

Note that this file can be run with 'python -m doctest -v README.txt' although the results are system dependent

Requires

Python 3, or an earlier version with the ctypes module.

Installation

pip install .

Usage

You can use the lower level nvml bindings provided by nvidia-ml-py

>>> from pynvml import *
>>> nvmlInit()
>>> print("Driver Version:", nvmlSystemGetDriverVersion())
Driver Version: 410.00
>>> deviceCount = nvmlDeviceGetCount()
>>> for i in range(deviceCount):
...     handle = nvmlDeviceGetHandleByIndex(i)
...     print("Device", i, ":", nvmlDeviceGetName(handle))
...
Device 0 : Tesla V100

>>> nvmlShutdown()

Or the higher level nvidia_smi API

from pynvml_utils import nvidia_smi
nvsmi = nvidia_smi.getInstance()
nvsmi.DeviceQuery('memory.free, memory.total')

from pynvml_utils import nvidia_smi
nvsmi = nvidia_smi.getInstance()
print(nvsmi.DeviceQuery('--help-query-gpu'), end='\n')

Functions

Python methods wrap NVML functions, implemented in a C shared library. Each function's use is the same with the following exceptions:

For usage information see the NVML documentation.

Variables

All meaningful NVML constants and enums are exposed in Python.

The NVML_VALUE_NOT_AVAILABLE constant is not used. Instead None is mapped to the field.

NVML Permissions

Many of the pynvml wrappers assume that the underlying NVIDIA Management Library (NVML) API can be used without admin/root privileges. However, it is certainly possible for the system permissions to prevent pynvml from querying GPU performance counters. For example:

$ nvidia-smi nvlink -g 0
GPU 0: Tesla V100-SXM2-32GB (UUID: GPU-96ab329d-7a1f-73a8-a9b7-18b4b2855f92)
NVML: Unable to get the NvLink link utilization counter control for link 0: Insufficient Permissions

A simple way to check the permissions status is to look for RmProfilingAdminOnly in the driver params file (Note that RmProfilingAdminOnly == 1 means that admin/sudo access is required):

$ cat /proc/driver/nvidia/params | grep RmProfilingAdminOnly
RmProfilingAdminOnly: 1

For more information on setting/unsetting the relevant admin privileges, see these notes on resolving ERR_NVGPUCTRPERM errors.

Release Notes