rgm_ui

Crates.iorgm_ui
lib.rsrgm_ui
version0.1.0
created_at2025-09-06 02:48:02.908883+00
updated_at2025-09-06 02:48:02.908883+00
descriptionA Rust GPU Monitor with egui UI for NVIDIA GPUs on Linux
homepage
repositoryhttps://github.com/Xlqmu/RGM
max_upload_size
id1826679
size140,896
Parallel Lines (Xlqmu)

documentation

README

RGM: Rust GPU Monitor

Build Status License: MIT / Apache-2.0

A lightweight, command-line utility built with Rust to quickly check your NVIDIA GPU's utilization. Simple, fast, and reliable.

Features

  • Instant Readout: Get the current GPU utilization percentage immediately.
  • Minimalist: No complex UI, just the data you need.
  • Low Overhead: Built in Rust for maximum performance and minimal resource consumption.

Prerequisites

Before you begin, ensure you have the following installed on your system:

  1. Rust & Cargo: If you don't have them, install them from rust-lang.org.
  2. NVIDIA Drivers: You must have the official NVIDIA drivers installed. You can verify this by running nvidia-smi in your terminal.

Installation

  1. Clone the repository:

    git clone https://github.com/your-username/RGM.git
    cd RGM
    
  2. Build the optimized binary:

    cargo build --release
    

The final executable will be located at target/release/RGM.

Usage

Run the compiled application from your terminal to see the current GPU status.

./target/release/RGM

Example Output:

GPU Utilization: 18%

Troubleshooting

Error: libnvidia-ml.so: cannot open shared object file: No such file or directory

This is a common runtime issue on Linux systems. It occurs when the application cannot find the NVIDIA Management Library (NVML), even if nvidia-smi works correctly. It's typically caused by a missing symbolic link in the system's library paths.

Solution:

  1. Find the NVML library path. Use ldconfig to locate the actual library file.

    ldconfig -p | grep libnvidia-ml.so.1
    

    Note the path in the output, which will look something like => /lib/x86_64-linux-gnu/libnvidia-ml.so.1.

  2. Create a symbolic link. Use the path from the previous step to create the link that the application expects.

    # IMPORTANT: Use the path you found on your system.
    sudo ln -s /lib/x86_64-linux-gnu/libnvidia-ml.so.1 /lib/x86_64-linux-gnu/libnvidia-ml.so
    

After creating the link, the application should run without issues.

License

This project is licensed under either of:

at your option.

Contribution

Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in this project by you, as defined in the Apache-2.0 license, shall be dually licensed as above, without any additional terms or conditions.

Commit count: 15

cargo fmt