#nvidia #gpu #monitoring #hardware #managment

nvml-wrapper

A safe and ergonomic Rust wrapper for the NVIDIA Management Library

8 breaking releases

0.9.0 Jan 21, 2023
0.8.0 May 27, 2022
0.7.0 Dec 7, 2020
0.6.0 Jun 16, 2020
0.3.0 Jul 20, 2017

#13 in Hardware support

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MIT/Apache

695KB
13K SLoC

nvml-wrapper

Docs.rs docs Crates.io version Crates.io downloads CI dependency status

A safe and ergonomic Rust wrapper for the NVIDIA Management Library (NVML), a C-based programmatic interface for monitoring and managing various states within NVIDIA GPUs.

use nvml_wrapper::Nvml;

let nvml = Nvml::init()?;
// Get the first `Device` (GPU) in the system
let device = nvml.device_by_index(0)?;

let brand = device.brand()?; // GeForce on my system
let fan_speed = device.fan_speed(0)?; // Currently 17% on my system
let power_limit = device.enforced_power_limit()?; // 275k milliwatts on my system
let encoder_util = device.encoder_utilization()?; // Currently 0 on my system; Not encoding anything
let memory_info = device.memory_info()?; // Currently 1.63/6.37 GB used on my system

// ... and there's a whole lot more you can do. Most everything in NVML is wrapped and ready to go

try the basic_usage example on your system

NVML is intended to be a platform for building 3rd-party applications, and is also the underlying library for NVIDIA's nvidia-smi tool.

Usage

nvml-wrapper builds on top of generated bindings for NVML that make use of the libloading crate. This means the NVML library gets loaded upon calling Nvml::init and can return an error if NVML isn't present, making it possible to drop NVIDIA-related features in your code at runtime on systems that don't have relevant hardware.

Successful execution of Nvml::init means:

  • The NVML library was present on the system and able to be opened
  • The function symbol to initialize NVML was loaded and called successfully
  • An attempt has been made to load all other NVML function symbols

Every function you call thereafter will individually return an error if it couldn't be loaded from the NVML library during the Nvml::init call.

Note that it's not advised to repeatedly call Nvml::init as the constructor has to perform all the work of loading the function symbols from the library each time it gets called. Instead, call Nvml::init once and store the resulting Nvml instance somewhere to be accessed throughout the lifetime of your program (perhaps in a once_cell).

NVML Support

This wrapper is being developed against and currently supports NVML version 11. Each new version of NVML is guaranteed to be backwards-compatible according to NVIDIA, so this wrapper should continue to work without issue regardless of NVML version bumps.

Legacy Functions

Sometimes there will be function-level API version bumps in new NVML releases. For example:

nvmlDeviceGetComputeRunningProcesses
nvmlDeviceGetComputeRunningProcesses_v2
nvmlDeviceGetComputeRunningProcesses_v3

The older versions of the functions will generally continue to work with the newer NVML releases; however, the newer function versions will not work with older NVML installs.

By default this wrapper only provides access to the newest function versions. Enable the legacy-functions feature if you require the ability to call older functions.

MSRV

The Minimum Supported Rust Version is currently 1.51.0. I will not go out of my way to avoid bumping this.

Cargo Features

The serde feature can be toggled on in order to #[derive(Serialize, Deserialize)] for every NVML data structure.

License

Licensed under either of Apache License, Version 2.0 or MIT license at your option.
Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in this crate by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.

Dependencies

~0.6–1.2MB
~24K SLoC