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AMD NPU Monitoring on Linux: A Beginner’s Guide to AI Chip Tracking!

Posted on February 2, 2026

So you’ve heard about AI, and you know computers are getting smarter. A big part of that smartness comes from special computer chips called NPUs – Neural Processing Units. AMD, a big name in computer parts, now has NPUs in some of their processors. But how do you see what your NPU is doing on a Linux computer? That’s what we’re going to explore!

What’s an NPU Anyway?

Think of your computer’s brain as having different sections. The CPU (Central Processing Unit) is good at general tasks – like running your web browser or playing music. The GPU (Graphics Processing Unit) is amazing at showing you pictures and videos. An NPU is a specialized brain section designed specifically for AI tasks. It’s built to quickly handle the math needed for things like recognizing faces in photos, understanding what you say to your voice assistant, or even helping your games look and feel more realistic.

AMD’s NPUs, part of their Ryzen AI technology, are designed to accelerate these AI workloads. They’re not meant to replace your CPU or GPU, but to work alongside them, making AI tasks much faster and more efficient. The key is that NPUs are designed for parallel processing – meaning they can do lots of calculations at the same time, which is perfect for AI.

Why Monitor Your NPU?

So, why would you want to watch your NPU? Well, it’s useful for a few reasons:

  • Troubleshooting: If something isn’t working right with your AI software, monitoring the NPU can help you figure out if the problem is with the chip itself or with the software.
  • Performance Tuning: You can see how much power your NPU is using and how hard it’s working. This can help you optimize your AI applications for better performance.
  • Understanding Usage: It’s just cool to see what your computer is doing! Knowing when and how your NPU is being used can be fascinating.

The Tools You’ll Need

Monitoring an AMD NPU on Linux isn’t as straightforward as checking your CPU temperature. It’s a relatively new area, and the tools are still developing. Here’s a breakdown of what’s available:

  1. rocm-smi (ROCm System Management Interface): This is the primary tool from AMD for monitoring their GPUs and NPUs. ROCm (Radeon Open Compute platform) is AMD’s open-source platform for GPU computing, and rocm-smi is a command-line utility that’s part of it. It provides a wealth of information, including NPU utilization, temperature, power consumption, and clock speeds.
  • Installation: You’ll likely need to install the ROCm platform first. The installation process varies depending on your Linux distribution (Ubuntu, Fedora, etc.). Refer to the official AMD ROCm documentation for detailed instructions: https://rocm.docs.amd.com/en/latest/
  • Usage: Once installed, you can run rocm-smi in your terminal. Here are some useful commands:
  • rocm-smi: Shows a basic overview of all ROCm devices (GPUs and NPUs).
  • rocm-smi -n <npu_id>: Provides detailed information for a specific NPU (replace <npu_id> with the NPU’s ID, usually 0 or 1).
  • rocm-smi --query-gpu=<metrics>: Allows you to query specific metrics, like utilization or temperature. For example, rocm-smi --query-gpu=utilization.
  1. radeontop: While primarily a GPU monitoring tool, radeontop can also display some NPU-related metrics, especially if you’re running workloads that utilize both the GPU and NPU.
  • Installation: sudo apt install radeontop (on Debian/Ubuntu-based systems) or use your distribution’s package manager.
  • Usage: Simply run radeontop in your terminal. It will show a real-time display of GPU and NPU activity.
  1. Graphical Monitoring Tools (Emerging): As NPU monitoring becomes more common, we’re starting to see graphical tools appear. These often build on top of rocm-smi or radeontop to provide a more user-friendly interface. Keep an eye out for these – they’ll likely become more prevalent in the future. Currently, integration within popular system monitoring tools like GNOME System Monitor is limited but improving.

Understanding the Metrics

When you’re monitoring your NPU, here are some key metrics to pay attention to:

  • Utilization: This tells you how much the NPU is being used. A higher utilization means it’s working harder. It’s usually expressed as a percentage.
  • Temperature: Like any computer chip, the NPU generates heat. Keep an eye on the temperature to make sure it’s not getting too hot. Excessive heat can damage the chip.
  • Power Consumption: The NPU uses power to operate. Monitoring power consumption can help you understand how much energy your AI tasks are using.
  • Clock Speed: This indicates how fast the NPU is running. Higher clock speeds generally mean better performance, but also more power consumption and heat.

Challenges and Future Developments

Monitoring AMD NPUs on Linux is still a relatively new area, and there are some challenges:

  • Limited Tooling: The tools are still under development, and the level of detail they provide can vary.
  • ROCm Complexity: Installing and configuring ROCm can be a bit complex, especially for beginners.
  • Integration with System Monitoring: Better integration with standard system monitoring tools (like GNOME System Monitor) would make NPU monitoring more accessible.

However, things are rapidly improving. AMD is actively working on improving ROCm and providing better tools for monitoring their NPUs. We can expect to see more user-friendly graphical tools and better integration with existing system monitoring solutions in the future. As AI becomes more prevalent on Linux, NPU monitoring will become increasingly important.

Monitoring your AMD NPU on Linux gives you valuable insights into how your AI applications are performing and how your hardware is being utilized. While the tools might require a little setup, the information you gain can be incredibly useful for troubleshooting, performance tuning, and simply understanding your computer better. Start with rocm-smi – it’s the most comprehensive tool available – and keep an eye out for new graphical tools as they emerge!

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